# Welcome to Panorama Block

## Overview 

> Panorama Block was built on a strong academic foundation, with a focus on research and collaboration with top-tier talent. Our partnerships with leading  universities and think tanks drive the development of decentralized data analytics and AI/ML tools, fully aligned with our mission to advance AI technologies, simplify user experiences, democratize data access, and provide action-oriented intelligence that empower participants and investment decisions, supporting the growth of a data-powered, agentic economy.

Panorama Block will be continuously developed in collaboration with prestigious institutions such as University of California Los Angeles - UCLA, Inteli, LMU, and other leading universities worldwide, harnessing the expertise and capabilities of their exceptional students and faculty. We have a dedicated team of experienced traditional finance professionals and blockchain experts from prestigious universities, such as UCLA, FGV, Inteli and MIT among other top-tier schools, overseeing project development and technology. Additionally, we actively seek to secure grants from prominent blockchain protocols, further reinforcing our commitment to innovate alongside the key-players of the industry while combining our expertise in cutting-edge research in data science together with decades of traditional finance experience.


# Our Vision

Our founders have over seven years of experience in the cryptocurrency space, having actively participated in the DeFi Summer of 2019/2020. Their enthusiasm for the sector has only grown since then. Drawing from this deep experience and commitment to innovation, Panorama Block will enable users to deploy automated DeFi strategies, or "money legos," tailored to specific risk profiles, financial parameters, and available capital. These agents will execute several DeFi yield strategies such as lending/borrowing loops, perpetual trading, staking, liquidity provision, and leveraged plays in an automated and interoperable manner across various protocols and blockchains. The AI Agents will prioritize risk mitigation while seeking alpha-generating opportunities.

To bridge the gap further, and recognizing that not everyone in crypto is tech-savvy enough to deploy their own AI agents or bots, Panorama Block will provide custom pre-built agents specifically designed for DeFi automation, composability, and yield strategies, while empowering 3rd party developers to create these solutions on our platform. Developers will also be able to monetize their bots and make them available for other users. Our users will be able to track their positions seamlessly across multiple protocols and different chains while monitoring market trends, identifying emerging narratives, and accessing all critical insights in one single place.

## Our Target Audience

**Developers** who will be able to create, test, and monetize AI-driven DeFi agents and bots. With access to comprehensive on-chain data services and pre-built AI agents, developers will have the tools to build and deploy proprietary solutions while offering them to a broader user base.

**Enterprises & Institutions** that will gain access to reliable on-chain data analytics and AI tools for advanced market analysis, risk management, and portfolio optimization.

**Digital Asset Enthusiasts & Retail Users** who may lack technical expertise or time to navigate the complexities of DeFi can use Panorama Block's AI agents/bots as personal assistants for automating strategies, executing transactions, tracking yield opportunities, and identifying alpha-seeking/risk mitigation plays. Panorama Block will provide an intuitive, all-in-one platform with automated DeFi strategies, real-time market analysis, and seamless position tracking and optimization.


# The Problem

Challenges like cross-chain silos, resource-intensive AI integration, and lack of standardized frameworks for multi-protocol strategies obstruct the current agentic economy.

## 1 - Data Fragmentation and Accessibility

The blockchain ecosystem has evolved into a complex web of independent networks, each generating massive amounts of data. This fragmentation creates several critical challenges:

### Cross-Chain Visibility

Traditional blockchain explorers operate in isolation, forcing users to manually piece together information from multiple sources. This siloed approach:

* Prevents comprehensive understanding of cross-chain interactions
* Makes it difficult to track assets across different networks
* Limits the ability to identify patterns and opportunities spanning multiple chains

### Data Interpretation

Raw blockchain data is abundant but difficult to interpret:

* Complex transaction structures require technical expertise to understand
* Important patterns and trends are hidden within vast amounts of noise
* Real-time decision-making is hampered by data processing delays
* Correlation between on-chain and off-chain events is manual and time-consuming

### Accessibility Barriers

Current tools create significant barriers to entry:

* Technical knowledge requirements exclude many potential users
* Multiple subscriptions needed for comprehensive coverage
* Lack of standardization across different platforms
* Limited integration capabilities with existing systems

## 2 - AI Infrastructure Limitations

Integrating AI into blockchain ecosystems presents a series of challenges that range from technical complexities to resource constraints. Developing AI agents designed for decentralized networks requires a high level of expertise in both blockchain technology and AI development. It also demands substantial investments in infrastructure and ongoing maintenance to ensure smooth integration across multiple blockchain networks. Additionally, the integration process is not straightforward, as it requires extensive testing and continuous optimization to adapt to evolving technological standards and ensure that the AI solutions remain reliable and scalable. While artificial intelligence has made significant strides, its application in the blockchain space remains limited:

### Development Complexity

Creating blockchain-focused AI agents requires:

* Deep expertise in both blockchain technology and AI development
* Substantial investment in infrastructure and maintenance
* Complex integration with multiple blockchain networks
* Extensive testing and optimization processes

### Resource Constraints

Existing solutions face several resource-related challenges:

* Limited access to high-quality training data
* High computational costs for model training and deployment
* Inefficient resource sharing between different agents
* Lack of standardized performance metrics

### Integration Challenges

Current AI solutions struggle with:

* Incompatibility between different blockchain protocols and networks
* Limited ability to execute complex, multi-step operations
* Poor scalability across different use cases
* Insufficient security measures for autonomous operations

## 3 - DeFi Strategy Deployment

The expansion of multi-chain ecosystems presents a key challenge:

While more chains increase total liquidity, it also leads to reduced liquidity per pool, hindering efficiency. This fragmentation is a major obstacle to DeFi’s scalability. For users, developers, and protocols alike, this issue impacts all participants. DeFi thrives on composability, where protocols build on each other. However, executing cross-chain strategies, like leveraged yield farming, remains complex due to bridge risks, differing gas tokens, and inconsistent block speeds.

Current fixes, such as modular liquidity and cross-chain messaging, only address surface-level issues. The solution lies in unified execution layers that enable:

* Automated capital allocation
* Cross-chain position management
* Real-time risk adjustment

Building smarter infrastructure to simplify complexity is the future of DeFi. The focus should shift from connecting everything to everything, to creating intelligent, composable systems that reduce friction. The DeFi landscape is undergoing a fundamental shift as protocols begin enabling direct agent integration. This evolution presents both challenges and opportunities:

### Limited Agent Integration

* Most DeFi protocols lack standardized interfaces for agent connection
* No unified framework for agent-protocol communication
* Missing infrastructure for automated strategy deployment
* Limited ability to monitor and control agent activities

### Protocol Fragmentation

* Each protocol implements different agent integration standards
* Lack of cross-protocol strategy coordination
* Inefficient capital allocation across different protocols
* Limited ability to execute multi-protocol strategies

### Strategy Development Barriers

* High technical requirements for creating agent-compatible strategies
* Complex integration requirements for each protocol
* Limited tools for strategy testing and validation
* Insufficient risk management frameworks for autonomous trading

### Performance Optimization

* No standardized metrics for agent strategy performance
* Difficult to compare strategies across different protocols
* Limited ability to adjust strategies in real-time
* Insufficient tools for strategy optimization

### Market Inefficiencies

* Delayed response to market opportunities
* Manual intervention required for strategy adjustments
* Limited ability to execute complex, multi-step strategies
* High costs of strategy deployment and maintenance

### Emerging Protocol Landscape

* Growing number of protocols enabling agent integration
* Varying levels of agent autonomy across platforms
* Different security models for agent interaction
* Evolving standards for agent-protocol communication


# Our Solutions

Our proprietary blockchain scanners will aggregate and normalize data across multiple chains, enabling users to create intelligent AI agents capable of executing composable DeFi strategies.

### 1. **Proprietary Blockchain Scanners**

**Development of Multi-Chain Data Scanners**\
We will create proprietary blockchain scanners designed to aggregate and analyze data from multiple blockchain networks. These scanners will:

* **Real-Time Data Collection**: Continuously monitor various blockchains to collect transaction data, smart contract interactions, and other relevant metrics, ensuring that users have access to the most current and comprehensive data available across different networks.
* **Data Normalization and Standardization**: The scanners will normalize data from different blockchains into a unified format, making it easier for developers to access and utilize this information without needing to understand the intricacies of each individual blockchain.
* **Integration with AI Agents**: The data collected by these scanners will serve as a foundational resource for AI agents. Developers can leverage this aggregated data to built and train AI models.

### 2. **Unified Data Access Layer**

**Standardized Resource Interfaces**\
To combat the issue of isolated data silos, we will implement a unified data access layer that standardizes how blockchain data is accessed across different networks. This will include:

* **Interface Registration**: Every shared resource must implement a standard interface that defines its capabilities. This interface will specify:
  * **Available Methods and Parameters**: Clearly defined API endpoints for accessing data.
  * **Expected Response Formats**: Consistent data formats (e.g., JSON) to facilitate integration.
  * **Rate Limits and Usage Constraints**: Defined limits to ensure fair access and prevent abuse.
  * **Authentication Requirements**: Secure access protocols (e.g., OAuth) to protect resources.

For example, an agent sharing access to a blockchain dataset would register an interface detailing available endpoints such as `getTransactionData`, `getBlockInfo`, etc., along with their input formats and rate limitations.

### 3. **Cross-Chain Data Aggregation**

**Decentralized Data Aggregators**\
To enhance cross-chain visibility, we will develop decentralized data aggregators that collect and harmonize data from multiple blockchain networks. These aggregators will:

* Continuously pull data from various blockchains, ensuring that users have access to real-time analytics across the major networks and DeFi protocols.
* Standardize data formats across different blockchains to provide a unified view of information, allowing users to query data without needing to understand the underlying differences between blockchains.

### 4. **Advanced Analytics Tools**

**Actionable Insights through AI-Driven Analytics**\
We propose the development of advanced analytics tools that leverage AI and machine learning:

* **Predictive Analytics Models**: Implement machine learning algorithms that analyze historical blockchain data to identify trends and make predictions about future market movements. 
* **Customizable Dashboards**: Users will have access to customizable dashboards that allow them to visualize key metrics and trends across different blockchains. These dashboards will enable users to filter and analyze data based on their specific interests or strategies

### 5. **Reputation Management System**

**Dynamic Reputation Scoring**\
A robust reputation management system for ensuring data quality and building trust among agents. This system will include:

* **Reputation Score Collection**: Reputation scores will be collected from validators at the end of each specific periods. These scores will reflect the subjective ratings of data quality provided by agents during that period. The system will maintain the most recent ten scores for each provider, ensuring that new ratings supersede older ones to reflect current performance accurately.
* **On-Chain Transparency**: Reputation scores will be stored on-chain, allowing users to assess data providers based on historical performance. This transparency will help eliminate low-quality contributors and bad actors from the ecosystem.
* **Incentive Structures**: Validators will earn reputation points for consistently delivering high-quality data. This incentivization mechanism will encourage reliable behavior and discourages attempts to game the system by creating multiple identities or manipulating scores.

**Trust Building Through Direct Experience**\
Agents will build trust through direct interactions, where each transaction contributes to a collective understanding of reliability:

* Every interaction between agents will be recorded with concrete metrics such as bandwidth availability, API functionality, adherence to usage limits, and timely access returns. This data will create a marketplace-like environment where agents can rate each other based on measurable outcomes rather than subjective opinions.
* If an agent fails to deliver on its promises (e.g., providing expired API keys), subsequent users will quickly detect this deception and record negative reputation scores. These scores will propagate through the ecosystem, alerting other agents about unreliable partners.

### 6. **Resource Optimization Strategies**

**Access to High-Quality Training Data**\
To overcome existing resource constraints, we need to ensure that AI agents have access to diverse and high-quality training datasets:

* Panorama Block will establish a decentralized marketplace where users can contribute high-quality datasets in exchange for tokens. This marketplace will encourage data sharing while ensuring contributors are fairly compensated for their efforts.
* Partnerships with reputable data providers will be forged to secure access to valuable datasets needed for training AI models. 

**Efficient Resource Utilization**\
To address computational costs associated with model training and deployment:

* Panorama Block will implement a shared infrastructure approach where multiple agents can utilize the same computational resources efficiently. This model will significantly reduce costs by allowing agents to pool resources for training and inference tasks.
* Panorama Block will utilize algorithms that dynamically allocate computational resources based on demand and workload requirements. By monitoring resource usage patterns, the system will be able optimize allocations in real-time, ensuring that resources are used effectively without over-provisioning.

### 7. **Integration Capabilities with Existing Systems**

**Standardized Integration Protocols**\
To facilitate seamless integration between AI agents and existing blockchain systems:

* Panorama Block will develop standardized API specifications that all shared resources must adhere to. These specifications will define available methods, expected input/output formats, authentication requirements, and rate limits. For example, an agent providing access to a custom blockchain dataset would register an interface detailing endpoints along with their respective input formats.
* Panorama Block will establish frameworks that enable agents to interact across different blockchain protocols without requiring extensive modifications or adaptations. This will include creating middleware solutions that translate between different protocol standards.

### 8. **Automated Testing and Optimization Tools**

**Automated Strategy Testing Environments**\
To ensure that AI strategies are effective before deployment:

* Panorama Block will provide simulated environments where agents can test their strategies against historical market data before going live. These environments will allow for extensive backtesting under various market conditions.
* Panorama Block will develop tools that benchmark agent performance against standardized metrics across different protocols. This benchmarking process will help identify areas for improvement and ensure optimal strategy execution.

### 9. **Facilitating DeFi Strategy Deployment**

**Unified Agent Integration Protocols**\
To streamline the integration of agents with various DeFi protocols, we will establish a set of unified protocols that standardize communication and interaction. This includes:

* **Cross-Protocol Coordination Frameworks**: We will develop a framework that allows agents to coordinate strategies across multiple protocols. This framework will include:
  * **Multi-Protocol Strategy Execution**: Agents will be able to execute strategies that span multiple protocols seamlessly, optimizing capital allocation based on real-time data.
  * **Shared State Management**: A shared state mechanism will be implemented to allow agents to maintain awareness of their positions and actions across different protocols, ensuring consistency in strategy execution.

### **10. Automated Strategy Deployment**<br>

To enhance the efficiency of strategy deployment in DeFi environments, we propose:

* **Smart Contract-Based Automation**: Utilizing smart contracts to automate the execution of strategies based on predefined conditions. This will include:
  * **Trigger Mechanisms**: Smart contracts will listen for specific market signals or events (e.g., price thresholds) to trigger strategy execution automatically.
  * **Dynamic Rebalancing**: Agents will be able to dynamically adjust their strategies based on market conditions without manual intervention, allowing for real-time optimization.
* **Monitoring and Control Interfaces**: User-friendly dashboards that provide real-time monitoring of agent activities across protocols. These interfaces will allow users to:
  * **Track Performance Metrics**: Users can view key KPIs for their strategies in real-time.
  * **Adjust Strategies Dynamically**: Users can make adjustments to their strategies based on live data feeds and performance outcomes.

### 11. **Market Efficiency Improvement**

**Real-Time Market Response Mechanisms**\
To enhance the responsiveness of agents to market changes, we propose implementing advanced systems that enable immediate reactions:

* **Automated Decision-Making Algorithms**: Agents will utilize machine learning algorithms that analyze market data in real-time to make informed decisions about strategy adjustments. These algorithms will consider:
  * Historical performance data
  * Current market trends
  * User-defined risk profiles
* **Event-Driven Architecture**: Panorama Block will implement an event-driven architecture where agents subscribe to market events (e.g., price changes, volume spikes) allowing them to react instantly. This architecture will enable:
  * **Immediate Execution of Strategies**: Agents can execute complex multi-step strategies immediately upon detecting favorable market conditions.
  * **Reduced Latency in Transactions**: By minimizing the time between data acquisition and execution, agents will be able to capitalize on fleeting opportunities.

### 12. **Supporting Emerging DeFi Protocols**

**Adaptation to New Protocols and Standards**\
As new DeFi protocols emerge, our solutions must remain adaptable to support varying levels of agent autonomy and security models:

* **Protocol Agnostic Frameworks**: Panorama Block will develop frameworks that are agnostic to specific protocols allows for easier integration as new protocols are introduced. This includes:
  * **Modular Architecture for Agents**: Agents will be designed with modular components that can be easily updated or replaced as new protocols emerge or existing ones evolve.
  * **Interoperability Standards Development**: Collaborating with industry leaders to define interoperability standards ensuring that our solutions remain compatible with future developments.
* **Continuous Monitoring and Updates**: Establishing a system for continuous monitoring of emerging protocols allows our platform to adapt quickly. This involves:
  * Keeping integration protocols up-to-date with the latest standards and practices from newly launched DeFi projects.
  * Creating a in-house forum for feedback from users and agents on the effectiveness of integrations with new protocols, helping identify areas for improvement.


# Panorama Chain View

Multi-Chain Blockchain Scanners for Agent-Driven Data Insights

The **Panorama Chain View** product integrates a set of highly technical features designed to provide advanced blockchain scanning, data aggregation, and predictive analytics capabilities. These features will support multi-chain data collection, AI-powered insights, and actionable intelligence for developers and end-users navigating several Web3 verticals. Key components include:

### **Proprietary Blockchain Scanners for Multi-Chain Data Collection**

To address the complexities of working with multiple blockchain networks, Panorama Block will develop proprietary blockchain scanners capable of aggregating and analyzing data across diverse networks. These scanners will function as continuous real-time data collectors, gathering a wide range of metrics, including transaction details, smart contract interactions, token transfers, and wallet activities.

* **Real-Time Data Collection:** These scanners will operate continuously, ensuring that the latest transaction data, block information, and network statistics from various blockchains are available for analysis.&#x20;
* **Data Normalization and Standardization:** As data from different blockchains can vary in structure and format, the scanners will implement data normalization protocols. This will ensure that data from multiple blockchain networks is converted into a consistent format, allowing developers to interact with the data without needing deep knowledge of individual blockchains' underlying protocols.&#x20;
* **Integration with AI Agents:** The aggregated data will serve as a crucial resource for training and refining AI models. Developers can utilize this unified data set to build predictive algorithms, anomaly detection systems, or even automated trading strategies.

### **Unified Data Access Layer for Cross-Chain Data Retrieval**

To eliminate the silos that often hinder cross-chain data analysis, Panorama Block will introduce a **unified data access layer**. This layer will act as an abstraction layer, allowing developers and applications to retrieve data from various blockchain networks via standardized protocols.

* **Interface Registration and Standardization:** All data-sharing resources, including blockchain nodes and smart contracts, will register standardized interfaces that define the available data access methods. This includes well-documented API endpoints, several data retrieval methods, and associated parameters that enable efficient data querying.&#x20;
* **Unified Response Formats:** By standardizing data formats, developers can consume blockchain data without worrying about differences in the format between blockchains. This common format will ensure that cross-chain applications can run efficiently and without compatibility issues.

### **Decentralized Data Aggregators for Cross-Chain Insights**

Building on the unified data access layer, Panorama Block will implement **decentralized data aggregators** to enhance visibility across blockchain ecosystems. These aggregators will provide a unified, cross-chain view by pulling and harmonizing data from multiple networks.

* **Real-Time Data Aggregation:** Decentralized aggregators will pull data from diverse blockchains in real time, ensuring that users can analyze activity across multiple chains simultaneously. This capability will support a broad spectrum of Web3 applications, including DeFi tracking, cross-chain transaction monitoring, and multi-chain portfolio management.
* **Standardized Queryable Formats:** Aggregators will standardize data formats across various blockchains, enabling users to access consistent, harmonized data from different networks. By abstracting the differences between blockchains, Panorama Block will simplify the process of querying cross-chain data, allowing users to focus on actionable insights rather than the technicalities of blockchain protocols.

### **Advanced AI-Powered Analytics for Actionable Insights**

One of the core components of Panorama Block's offering is the development of **advanced analytics tools** that leverage AI and machine learning to provide actionable insights into blockchain data. These tools will support predictive analytics, trend analysis, and real-time decision-making.

* **Predictive Analytics Models:** Machine learning algorithms will analyze historical blockchain data to uncover patterns, identify trends, and make predictions about market movements. These models will utilize techniques such as regression analysis, time series forecasting, and anomaly detection to anticipate changes in blockchain activity and offer users the ability to act on emerging trends before they become mainstream.
* **Customizable Dashboards and Visualizations:** Panorama Block will offer fully customizable dashboards that enable users to visualize key blockchain metrics and market trends across different chains. These dashboards will allow users to filter data based on specific criteria (e.g., token performance, transaction volume, wallet activity) and set alerts for specific events. Users will have the flexibility to tailor the dashboards to their unique needs, whether they are tracking DeFi protocol performance or analyzing whale movements across multiple blockchains.
* **Data Utilization for Agent Creation:** The data collected and aggregated through Panorama Block's scanners and data aggregators will provide the foundational resources necessary for creating sophisticated AI agents. Developers will be able to build and train agents that can interact with blockchain data in an intelligent and automated manner. These agents can be employed for a variety of use cases, including automated trading, investment strategies, and anomaly detection.


# AI Marketplace

Empowering Developers and Institutions in a Decentralized Marketplace for AI Models and Tools

The AI Marketplace vertical of Panorama Block is a decentralized platform designed to integrate advanced AI tools, proprietary datasets, and tokenized monetization mechanisms within the blockchain ecosystem. Utilizing the PANBLK token, developers can deploy and monetize AI models, datasets, and analytics tools, while institutional users access tailored solutions for blockchain analysis and decision-making. The platform employs a token-powered structure for access, transactions, and governance, ensuring security, transparency, and scalability. Staking mechanisms validate bot integrity and data quality, while a decentralized marketplace enables peer-to-peer transactions, fostering innovation and streamlined monetization opportunities for AI-driven solutions.

### Primary Participants

* **Developers**\
  Develop and monetize AI bots and analytics tools through the platform’s ecosystem. Developers earn revenue based on the usage, performance, and enterprise adoption of their development of bots & data analytics tools and solutions. They also provide tailored AI services to institutional users, with all transactions powered by PANBLK tokens.
* **Validators (Stakers)**\
  Act as key custodians of data and analytics quality within the ecosystem. Validators stake PANBLK tokens to ensure the quality & validity of data validators provided to the ecosystem. In return, validators earn rewards, incentivizing their contributions to maintaining robust and reliable bots, datasets, AI tools and solutions.
* **Users (Retail and Institutional)**\
  Retail users gain access to affordable analytics tools and AI-based solutions to support their activities in the web3 space. Institutional users benefit from premium services such as custom-tailored AI solutions and proprietary analytics, addressing strategic needs like alpha-seeking and risk mitigation strategies.
* **Ambassadors (Key Opinion Leaders)**\
  Serve as promoters and advocates for Panorama Block, driving platform growth through community engagement, educational outreach, and workshops. They play a pivotal role in fostering adoption and are rewarded with PANBLK tokens for their contributions.

### Value Exchange

* **For Developers**\
  Gain access to premium AI and analytics tools, APIs, and datasets by utilizing PANBLK tokens. These resources empower developers to build and deploy custom AI applications, trading bots and machine learning models.
* **For Validators (Stakers)**\
  Validators stake PANBLK in order to provide data and be rewarded for data contributed.
* **For Users (Retail and Institutional)**\
  Retail users gain affordable access to AI-powered tools and blockchain analytics, leveraging PANBLK tokens for enhanced features and fee reductions. Institutional users utilize advanced datasets, predictive models, and tailored analytics to strengthen alpha-seeking and risk mitigation strategies.&#x20;
* **For Ambassadors (Key Opinion Leaders)**\
  Ambassadors enhance platform adoption by driving outreach, hosting workshops, and engaging communities. In return, they earn PANBLK tokens as rewards, incentivizing their contributions to platform growth and fostering a broader user base.

### **Staking and Accountability Mechanism**

PANBLK tokens are integral to validating and governing the quality of AI bots and the broader data ecosystem.

* **Agent/Bot Creators:** Required to stake PANBLK tokens as a safeguard against malicious activity. This mechanism ensures accountability by creating an economic obstacle against poor-quality or malicious bots.
* **Validators:** Validators stake PANBLK tokens to provide clean, unbiased data and reviews, ensuring bots are trained with high-quality datasets. Validators receive rewards proportionate to their contribution and adherence to community standards.

<figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXf_sCDMXcaZ8JsqSA7lw55LIcsP8wnHvjZOsotHKu3vKD8x4rhXFRI_OxN80BSU6HwPzRsg5cHTS1b19PwZnmJ7Ny4bxRBx9yIg-cn5-ZUmkhQIb8x809Pj3A9Hsk8eRJvn39en6w?key=b5tdwUcvI2_reu4X-V-zaeTR" alt=""><figcaption><p><strong>Staking and Accountability Mechanism</strong></p></figcaption></figure>

### Incentives/Disincentives by Role

* Developers are rewarded with PANBLK tokens based on bot usage and performance. They benefit from discounted platform services but face penalties for deploying harmful bots.
* Validators (Stakers) earn rewards for staking PANBLK tokens to maintain platform integrity. Fee reductions and governance rights are granted, with slashing penalties for malicious behavior or inactivity.
* Users (Retail and Institutional) receive access to affordable tools, with fee reductions for holding PANBLK tokens. Institutional users gain customized solutions for advanced needs. Disincentives for users are aimed at ensuring proper platform engagement. Users who don’t hold or stake PANBLK tokens face higher fees and limited access to tools. Misuse of platform features can also lead to account restrictions or penalties.
* Ambassadors (KOLs) earn PANBLK tokens for promoting platform adoption and engagement through outreach and community activities. For KOLs, disincentives focus on maintaining platform integrity. Failure to meet engagement metrics or misrepresenting the platform can result in loss of rewards, removal from programs, and reputational damage, ensuring responsible participation within the ecosystem.

### **Commercialization of AI Models, Tools, and Solutions**

**Tokenized** **Transactions** **Between** **Developers** **and** **Institutional** **Users**

* Through PANBLK tokens, developers can interact directly with institutional users and enterprises that require custom AI solutions, data analysis, or specialized tools. Users will be able to easily purchase or license AI-driven solutions, data sets, and analytical tools from developers using PANBLK tokens.

**Payments** **for** **Access** **to** **Exclusive** **AI** **Analytics** **and** **Datasets**

* Institutional users or businesses seeking access to proprietary datasets or advanced analytics can pay developers in PANBLK tokens for licensing these assets.
* Developers can offer tiered access to their datasets or tools, where basic access is priced at a lower PANBLK amount, and more advanced or exclusive features come at a higher PANBLK token amount.

***

### **Marketplace Integration for AI Models, Tools, and Datasets**

**Decentralized** **Marketplace** **for** **AI** **Solutions**

* Developers are empowered to list their AI models, tools, datasets, and analytics solutions directly on the marketplace powered by PANBLK tokens. The marketplace provides a decentralized platform where developers can control the listing, pricing, and monetization of their assets without the need for intermediaries.
* The use of PANBLK tokens ensures that all transactions within the marketplace are secure, transparent, and tamper-proof, enhancing trust and reducing the risk of fraud or mispricing. PANBLK tokens are used to pay for listings, purchases, or usage rights of AI tools, datasets, and models.

**Peer**-**to**-**Peer** **Monetization** **Without** **Intermediaries**

* The peer-to-peer marketplace allows developers to maintain full control over their creations, negotiating directly with buyers. Transactions are powered by the PANBLK token, enabling seamless, secure payments without intermediaries.

**Incentivizing** **Ongoing** **Innovation** **and** **Collaboration**

* The platform rewards developers with PANBLK tokens for creating valuable AI tools. These tokens incentivize innovation and enable collaboration, driving continuous improvement and expanding offerings.

***

### **Key Benefits for Developers and Data Scientists**

* Earning Incentives: Developers earn PANBLK tokens through AI bot deployment, custom solutions, and exclusive datasets, directly linking their compensation to the success of their creations.
* Decentralized Marketplace: Developers can list and sell AI models, tools, and datasets in a peer-to-peer environment.
* Flexible Monetization: The ability to offer different pricing tiers for various tools or models enables developers to tailor their monetization strategies, whether it’s through one-time purchases or subscription-based models.
* Increased Control and Ownership: Developers retain full control over their assets, including pricing, licensing, and usage terms.

<figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXdt8EH1CZsWzc7NvVhz87CyTl4NFmQUEZe-e71qbdSi903Jy9C3K1TOBcCoZ0Yvg6dW24k-q2ortiQQ55ck9yDCgCerYCPsxzLg_bEibUI9vSL6GuL3xCj_mtGM9QvOVqPiPfVO6Q?key=b5tdwUcvI2_reu4X-V-zaeTR" alt=""><figcaption><p>Monetization Flow</p></figcaption></figure>


# DeFi Vista

Revolutionizing High-Yield DeFi Strategy Position Management

DeFi Vista is an innovative product within the Panorama Block ecosystem designed to transform how users engage with decentralized finance. It serves as a comprehensive hub for creating, deploying, and managing high-yield strategies, driving the development and optimization of DeFi yield models. The product will allow users to list their strategies, participate in a community-driven leaderboard, and gain access to AI-powered scorecards that identify and highlight the most promising yield opportunities.

Our platform will also offer the possibility of utilizing AI-managed vaults, which will execute a variety of DeFi strategies based on user-defined risk profiles. These strategies could range from meme trading, staking, stablecoin yield farming, and prediction market trading to swing trading, perpetuals, and options. By selecting a risk profile, users will be able to deploy their capital into vaults designed to grow investments by executing these diversified strategies.

DeFi Vista will introduce a unique approach through "agent swarms" — a set of DeFi agents trained to execute strategies with deep backtesting. These agents, which are AI-powered, will issue access tokens to holders, allowing them to participate in the offerings generated by the swarm. Users can deposit funds into vaults managed by the swarm, where each agent implements its specific strategy to generate profits. As these strategies yield returns, the gains will be distributed proportionally among token holders based on their share in the vault.

Furthermore, the swarm’s design includes the implementation of exit fees when users withdraw from the vaults. These fees will be burned, introducing a deflationary mechanism that helps strengthen the ecosystem’s overall tokenomics.

### **Solving Multi-Chain Fragmentation and Enhancing DeFi Scalability**

While the increase in the number of chains enhances total liquidity, it also leads to a reduction in liquidity per pool, which impacts the efficiency of strategies. This fragmentation poses a significant barrier to DeFi’s scalability, affecting users, developers, and protocols alike. While DeFi thrives on composability — where protocols build upon each other — executing cross-chain strategies remains complicated due to issues like bridge risks, differing gas tokens, and inconsistent block speeds.

Current solutions such as modular liquidity and cross-chain messaging address only surface-level issues. These fixes do not provide a comprehensive answer to the underlying complexity that hinders the seamless execution of cross-chain strategies. DeFi Vista is designed to address the complexities of multi-chain DeFi ecosystems by implementing unified execution layers that enhance operational efficiency. These layers will work to automate and streamline capital allocation, position management, and real-time risk adjustments, ensuring seamless execution across different protocols and blockchains.

To achieve this, DeFi Vista's automated AI Agents will dynamically allocate capital across multiple DeFi protocols across various chains based on current market conditions, liquidity availability, and risk factors. Real-time risk adjustments will be powered by AI-driven models that continuously monitor on-chain data and user-defined parameters.&#x20;

### **Plugging AI-Agent Strategies into DeFi Protocols**

At present, many DeFi strategies remain primitive and manual, with users required to actively monitor and manage their positions across different protocols. DeFi Vista will change this by plugging AI-driven agent strategies directly into protocols, allowing agents to connect and trade across different DeFi platforms.

The future of DeFi lies in reducing the friction caused by the complexities of multi-chain and multi-protocol systems. DeFi Vista’s intelligent, composable agent swarm system will not only make DeFi more accessible to a broader audience but will also provide a new level of automation and optimization that current solutions do not offer.


# Technical Architecture

System Architecture

<figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXc2pgeutZP-sg_QB7gI0-dNoffy-oLRKpGfbBs8Ce-BxkMpfFdxArbLHWbVSX0dc4F4xLHSkm_42PffE42xtD9ViEkbYFn7ydF9hdCtJLf9cbL7WqAIWIMeRuPzMXDAXUz3GRnniw?key=KM5v79wuHPVSmzFgMFHWgnUF" alt=""><figcaption></figcaption></figure>

## Overview&#x20;

Panorama Block is designed to transform raw crypto market data into structured, actionable insights. It operates as an ecosystem that seamlessly collects, processes, and distributes data, enabling users and systems to interact with relevant information in real-time with high reliability. By integrating multiple data sources and structuring them effectively, our intelligent agents provide insights, optimize DeFi strategies, and automate on-chain processes.&#x20;

## Data Flow and Processing

The data journey begins with collection, where we aggregate information from APIs, subgraphs, RPCs, and open internet sources. This data is ingested in real-time, ensuring a continuous and structured flow into Panorama Block’s core infrastructure.&#x20;

Once collected, the data undergoes transformation and enrichment. Our processing layer identifies patterns, corrects inconsistencies, and integrates metadata, ensuring uniformity across all datasets. This step standardizes information, making it ready for analysis and allowing for efficient retrieval by different applications and models.&#x20;

The processed data is stored in a structured environment that maintains both raw and aggregated information. This unified repository supports fast access for analytics and AI-driven insights. Organizing data across multiple layers ensures flexibility for different user needs, from automated agents to applications requiring high-performance decision-making.&#x20;

## Intelligent Layer and AI Agents&#x20;

Panorama Block’s intelligence layer comes into play once structured data becomes accessible. The ZICO Smart Agent operates within this ecosystem, interpreting information, responding to queries, and generating strategic insights based on patterns from both on-chain and off-chain data. Users interact with the system through direct prompts or API integrations.&#x20;

These agents do more than provide static responses—they execute strategic actions within the crypto ecosystem, such as monitoring significant transactions, automating swaps, tracking whale movements, and performing predictive market analysis. The goal is to reduce blockchain complexity, making critical insights accessible and actionable for both technical and non-technical users.&#x20;

## User Interaction and Data Distribution&#x20;

Structured information and AI-generated insights are distributed efficiently to users. Queries can be made via APIs, web interfaces, or interactive agents. Developers can integrate directly with Panorama Block’s infrastructure to build applications powered by real-time blockchain data.&#x20;

The architecture is optimized for low-latency queries, ensuring rapid responses. Frontend interfaces interact directly with the system core, enabling clear and customizable data visualization.&#x20;

AI-driven enhancements further refine data interpretation, supporting deeper analysis and actionable recommendations. The system also provides real-time alerts, notifications, and dashboards that track critical market movements.

<br>


# The "ZICO" Agent

Our AI master agent has been affectionately nicknamed Zico, in honor of the legendary Brazilian footballer *Arthur Antunes Coimbra*, who left an unforgettable mark on the sport during the 1980s and is still celebrated today as one of Brazil’s greatest soccer icons. Much like Zico orchestrated the midfield with vision, intelligence, and precision, our master agent is designed to coordinate and interpret complex data flows, driving strategic decision-making across all connected modules. The name reflects not only excellence and legacy, but also the agent’s role as the central "playmaker" in our system architecture.

<figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXfBB1wEC4fcFi6-iuF1P8094K6WCg-fd1VnXr6EN5KXs-ID2y1fdA5B8oyyE1unSo2Lcf1HkU6AkYVwqJ6AL_p-CNLGf1zgr1Pif7GTY3D95oDDhepnm7vKYm0E8sx9fBPmg6KL?key=KM5v79wuHPVSmzFgMFHWgnUF" alt=""><figcaption><p>A system integrating multiple agents to process on-chain and off-chain data, enabling adaptable applications across decentralized and traditional ecosystems.</p></figcaption></figure>

## Overview&#x20;

The ZICO Agent is an integrated system of lightweight, local, and highly extensible agents embedded into the Panorama Block ecosystem. Designed for the emerging convergence of decentralized finance and artificial intelligence — DefAI — ZICO handles advanced AI workflows (NLP, image generation, financial API integration) while offering an intuitive browser-based interface. Its goal is to abstract complex blockchain operations and provide a seamless user experience for interacting with multi-chain DeFi protocols and on-chain data.&#x20;

## How It Works:

### Data Acquisition and Standardization&#x20;

ZICO Agent connects to Panorama Block’s proprietary scanners and databases, capturing and normalizing blockchain data across multiple networks. This standardization abstracts away network-specific technical differences, offering users a unified and fluid interaction model without needing deep protocol-level knowledge.&#x20;

### AI-Powered DeFi Automation&#x20;

Through natural language prompts, ZICO automates DeFi actions such as token swaps and recurring investment strategies like Dollar Cost Averaging (DCA). Private key management and blockchain-specific operational complexity are fully abstracted, allowing users to execute complex actions without interacting directly with low-level blockchain mechanics.

### Multi-API and Data Source Integration&#x20;

ZICO aggregates data from CoinGecko, Coinbase, and other analytic platforms. It interprets user queries — for example, “What is the current XRPL price?” or “Show me the latest XRPL news” — by simultaneously querying multiple sources and consolidating the results into a single conversational reply.&#x20;

## Core Functionalities:

### Image Generation&#x20;

Responds to prompts like “Generate a logo for my XRPL project” using AI-driven image generation models combined with specialized crypto asset libraries.&#x20;

### USDC and Token Transfers&#x20;

Automates token sending operations while embedding security recommendations, such as wallet backup prompts.&#x20;

### Dollar Cost Averaging (DCA)&#x20;

Allows users to configure recurring asset purchases, smoothing out market volatility effects. Wallet setup is required, and operations can be paused or reconfigured at any time.&#x20;

### Tweet Creation&#x20;

Generates creative Twitter content using LLMs trained on crypto and broader financial language models. Example: “Write a tweet about Crypto and AI.”&#x20;

### Real-Time Information Queries&#x20;

Provides up-to-date asset prices, news headlines, and off-chain analysis. Combines on-chain metrics with external news sources for more comprehensive insights.&#x20;

### Crypto Rewards and News Verification&#x20;

Quickly answers queries like “What’s today’s top XRP news?” by aggregating verified reward programs and market updates.&#x20;

### Price, Market Cap, and TVL Retrieval

Connects to CoinGecko to fetch real-time market metrics. Example queries: “What is XRPL’s market cap?” or “How much is XRP trading for right now?”&#x20;

### External Document and PDF Analysis&#x20;

Allows users to upload and query PDFs — ideal for summarizing whitepapers or pulling targeted information — using NLP models that index and search document contents conversationally.&#x20;

### Detection of Trending Tokens Across Networks&#x20;

Compiles activity and liquidity data to identify trending tokens. For example: “Which tokens are most active on XRPL?” returns high-activity assets based on real-time volume analysis.&#x20;

## Architecture and Governance&#x20;

Each ZICO task — from language processing to API queries to on-chain transaction execution — runs independently to minimize process conflicts. Credential and private key management follow Panorama Block’s governance standards, ensuring security through audit logging and continuous reputation monitoring.


# Revenue Streams

Panorama Block operates an on-chain data analytics platform where users can access a variety of data sets, products and services.

### Transaction Fees:

Transaction fees will be a key revenue stream for Panorama Block, supporting the platform’s sustainability and scalability. These fees will be generated from a variety of user actions, such as PANBLK token transfers, bot deployments, and data access.

1. PANBLK Token Transfers: Each PANBLK token transfer, whether buying, selling, staking, or transferring PANBLK tokens, will incur a 1.5% transaction fee. For example, if User A wants to transfer 1,000 PANBLK tokens to User B, a 1.5% transaction fee will apply. This means User A will pay an additional 15 PANBLK as a fee (1,000 × 1.5% = 15 PANBLK). As a result, User A’s account will be debited 1,015 PANBLK in total, while User B will receive 1,000 PANBLK. These fees contribute to the platform’s liquidity and support its operational costs.
2. Custom Data Access: Users and institutions who require access to premium datasets, analytics, and specialized tools will be charged for these services. This fee structure will cater to enterprises, developers, and academic institutions seeking advanced data insights. The revenue from data access will increase as more users engage with premium services.

### Data Subscriptions

Subscription fees will form the backbone of Panorama Block’s revenue generation. These fees will be charged to users, institutions, and enterprises seeking ongoing access to exclusive datasets, APIs, and analytics services.

Tiered Subscriptions

Multiple subscription tiers will be available, each offering varying levels of access to datasets, tools, and support. To gather the advantages of different payment options, both fiat and token payments are accepted. Pricing will be structured as follows:

* Entrepreneur Package (Tier 1): Priced at $100 per month, this tier will provide small businesses, startups, and individual developers with essential datasets, basic analytics tools, and some advanced features.
* Enterprise Package (Tier 2): Priced at $500 per month, this tier will cater to larger institutions, providing extensive datasets, advanced analytics, customizable features, and dedicated support.

In addition, in order to encourage token payment, users paying entirely by PANBLK will receive a discount in subscription price, which follows the formula:

TokenSubscriptionPrice=FiatPrice (1−Discount)

For instance, assuming users paying entirely by PANBLK are receiving a 15% discount in the first year, then Entrepreneur Package would be priced at $85 worth of PANBLK per month, while Enterprise Package would be priced at $425 worth of PANBLK per month. The exact amount of PANBLK paid would be subject to real-time exchange rate between USD and PANBLK. The discount structure is designed to gradually decrease over time, encouraging early adoption while ensuring long-term token engagement.&#x20;

!\[A screenshot of a graph

AI-generated content may be incorrect.]\(<https://lh7-rt.googleusercontent.com/docsz/AD_4nXdaHhcwAv-xOC9no_e4TCNpvyVWWjYG6huhSyST33I2hG4dWOCfnut8EvEoabv5T2bZqsFUBK5wiJ0YW2ujAztPB8FELvzMnf5ZLMitCoT2gs3Y2qcVwGzWWP6xFuazys2ydaaB5QUX6Unvm6Ll_g?key=Z0hgCaOd0ISR6VP7HBQLQgai>)

**Freemium Model**

A freemium approach will allow individual users and small developers to access basic features at no cost. Users will be encouraged to upgrade to higher tiers for access to advanced datasets and premium tools.

**In-App Purchases & Microtransactions**

Panorama Block integrates in-app purchases as an additional revenue stream, allowing users to make one-time purchases for premium features, reports, and exclusive datasets.

**Numerical Formula:**

UIAP = UFree​ x PIAP

* UIAP ​= Number of users making in-app purchases
* Ufree  = Total number of freemium users
* PIAP​ = Portion of freemium users who make IAPs
* ie. If there are 1,400 freemium users in Year 1, and 75% of them make an in-app purchase, then the number of freemium users who make IAPs is: 1,400 × 0.75 = 1050

RIAP ​= UIAP​ x Savg x 12mo

* RIAP​ = Annual revenue from IAPs
* Savg​ = Average spend per user on IAPs
* Calculated Annual revenue by times 12 months
* ie. If 1050 users make in-app purchases and the average spend per user is $50 per year, then the total annual revenue from IAPs is: 1050 × $50 × 12 = $630,000

RTotal​ =RIAP​ +RSubscription

* RSubscription= Annual revenue from subscriptions
* ie. The expected annual revenue from both subscription fee and IAPs would be $630,000 + $1,700,000 = 2,310,000

Revenue Model with different scenarios test:

!\[A screenshot of a computer

AI-generated content may be incorrect.]\(<https://lh7-rt.googleusercontent.com/docsz/AD_4nXdI_C0LtvXjJ-zVuOHaMQgcadeaGY88m6PHDdGQS8OqpfmWnv6ujF44md51LOvBn0npbb9hwnU738IOAEAUcwIAtNCQj68aWlXe6kV2-dQ33dN-DVLi-A4QsA2FlpLPQPJUZYlPPRNlm66DX5Z9Y-Q?key=Z0hgCaOd0ISR6VP7HBQLQgai>)

**Custom Enterprise Solutions:**

Bespoke packages for large enterprises will be priced according to the scale of data usage and customization required. These will include advanced analytics tools and dedicated support for enterprise clients.

### AI Model Licensing

Revenue will also be generated from the licensing of AI models created within the Panorama Block ecosystem. Developers will license their models to institutions and businesses within the platform, generating ongoing revenue for both creators and the platform itself.

* Licensing Fees: Panorama Block will charge a small fee for the licensing of AI models deployed on the platform. By the end of 2025, our internal development team is projected to create 10-20 AI models and agents annually using the platform’s data. Additionally, we expect external developers to build around 50-70 AI models per year as the ecosystem matures.
* Royalty Payments: AI model creators will receive royalties based on the usage of their models.
* Marketplace Revenue: The marketplace is expected to contribute significantly to revenue, with 667,000+ transactions anticipated by the end of 2026, considering an average transaction value of $10 and a 1.5% transaction fee. This growth will reflect increased activity from developers and third-party providers offering custom data solutions and consulting services through the platform.

This fee revenue complements other sources such as licensing fees and royalty payments, contributing to the platform’s overall financial sustainability and scalability. As the ecosystem grows, both the number of transactions and the average transaction value are expected to increase, further amplifying marketplace revenue.

**Additional Revenue Streams**

* Partnerships and Integrations: Panorama Block will form strategic partnerships with other protocols, enterprises, and academic institutions to offer white-labeled solutions, integrated data tools, and AI capabilities.
* Data Sales: The platform will sell non-sensitive aggregated data to third-party businesses, researchers, and analysts interested in Web3 trends, blockchain data, or AI-related metrics.


# Token Details

Our tokenomics model was developed in collaboration with the esteemed team from the Masters of Quantitative Economics (MQE) program at UCLA.

### Token Overview

Our approach entails monthly token minting alongside dynamic daily token buyback and burning. This consistent monthly minting strategy ensures that our users always have an ample supply of tokens to access our platform's modules. The token buyback is linked to demand and circulating supply, which dynamically scales with token circulating supply. To enhance transparency, all burns will be tracked on-chain and published in periodic reports. By striking this balance, we aim to create a sustainable ecosystem where accessibility to our modules remains uninterrupted.

Symbol: PANBLK

Total Supply: 1,000,000,000.

Website: <https://panoramablock.com>

Contract Address: TBA

Decimals: 18.

### Token Features

In designing the economic model for our PANBLK token, we drew on traditional financial principles and innovative cryptocurrency mechanisms. Our economic framework incorporates elements inspired by established economic models, providing a solid foundation for our digital currency:

* We used the concept of a limited supply, similar to Bitcoin, to ensure scarcity and value preservation.
* The logic behind our burning and minting mechanism is derived from the concept of quantitative easing and tightening in monetary policy for Fiat Currency.
* We leverage the scarcity principal that dictate value enhancement through controlled supply, ensuring that PANBLK’s value is supported by its limited availability.
* Employing a Proof of Stake mechanism for transaction validations, our approach mirrors Ethereum’s method, focusing on energy efficiency and stakeholder engagement.

The tokenomics of PANBLK is thoughtfully designed to support and enhance the growth of our business ecosystem while offering significant utility and value to our users. Here's a summary of the key features that define the economic model of our token:

* Appreciating Value: Our tokenomics are designed to stabilize PANBLK in circulation with an increase in demand, ensuring the token’s value is poised to grow. This is achieved through a combination of monthly token minting and burning, supporting a long-term deflationary strategy based on growth and performance.
* Minting and Burning Schedule: Tokens are minted and burned on a daily basis. This is because token burning and minting is based on demand from the previous and current period.&#x20;
* Intrinsically Driven Demand: Beyond staking mechanisms and APY generation, our tokenomics integrate deeply with the expansion of our platform. As more services become token-enabled, the natural demand for PANBLK tokens increases. This demand is further enhanced by financial incentives through APY and staking rewards, making our token an essential asset for engaging with and benefiting from our ecosystem.
* Access Token: Designed primarily as an access token, PANBLK ensures that users can fully engage with our ecosystem’s diverse offerings.
* Blockchain Agnostic: PANBLK operates across multiple blockchain platforms, maximizing accessibility and utility in the decentralized digital economy.
* Supporting Future Development: A portion of the variable rate generated from strategy fees will be donated to institutions and NGOs. This initiative aims to support the education and professional development of young individuals aspiring to pursue a career in technology but facing barriers to access.

As illustrated in the chart, the circulating supply of PANBLK tokens has remained relatively stable over the course of 48 months. The slight fluctuations in supply can be attributed to periodic increases in token emissions tied to growth phases of our platform, countered by planned token burns that aim to mitigate inflationary pressures and enhance token scarcity, thus preserving the value for token holders.

*PANBLK Token Circulating Supply, Minted and Burned Tokens*

![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXfhRk2KyXqYHj8i-QQA0dqS5hs1t0yAR1QdNApS3Y_zfLBy0My8rN-DmEIrqTUuX1nKKcU4jMi9DhGHt02rzMzCTzFwKUKlacwkfiUCwtDV8nkpJFWPNjdKENlA3gjDiw2hD3Pl3MY8f5qIxwZ8LQ?key=Z0hgCaOd0ISR6VP7HBQLQgai)![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXek5OZdZrVglzAc5BaAy0HPyZT8-ijsDSnp_o6vIZmSdHbEEXZ6rCUAfpEvpSNnlHwWHOx0DiqwUXc8GfWIz95iqxNySwt7gNWIlsxLobL3Om5znk9B8uCK3u_Lgt4axpvqWIytVuKXfDIHGcu-N50?key=Z0hgCaOd0ISR6VP7HBQLQgai)<br>

### Dynamic Supply Adjustment Strategy

Our approach entails daily token minting alongside weekly token burning. This method ensures a balanced supply, maintaining token availability for platform access while adapting to shifts in market demand. By striking this balance, we aim to create a sustainable ecosystem where accessibility to our modules remains uninterrupted.

Our model is reactionary to shocks in demand and stabilizes itself through dynamic minting and burning mechanisms. Token burning for PANBLK hinges on increases in supply and demand. This maintains a stable supply in the face of an increasing demand. We stop burning tokens when our supply exceeds our initial target supply and proceed to burn tokens the next week if there is an increase in supply. Our strategy involves minting tokens daily and burning tokens on the last day of each 7-day cycle.&#x20;

Demand and supply are naturally a function of previous demand and supply as well as the amount of tokens minted and burnt. Therefore we approach of maintaining a deflationary supply through creating dynamic minting and burning. The number of tokens minted is determined by the change in demand and the previous day's minted tokens, while the number of burned tokens is adjusted based on supply and demand conditions on the final day of the cycle.&#x20;


# Token Utility

The PANBLK token will play a vital role in maximizing community engagement and driving long-term growth within the Panorama Block ecosystem enhancing governance, incentivization, and user interaction.

Some utilities include, but are not limited to:

* **Token-Based Access to Premium Tools and Features**: PANBLK tokens will grant users access to premium analytics tools, data visualization features, and advanced AI-driven insights within the platform. By holding and using tokens, developers and data scientists can unlock these exclusive features, enhancing their ability to create more powerful AI models and agents.
* **Discounts and Fee Reductions for Token Holders**: Users who hold PANBLK tokens will benefit from discounted transaction fees when utilizing the platform's services, such as licensing AI models or accessing proprietary datasets. Token holders can enjoy reduced costs, incentivizing them to remain active within the ecosystem and further fueling platform growth.
* **Access to Data and Project Listings**: PANBLK tokens will also act as a utility for interacting with the broader Panorama Block platform, granting users access to key data insights and allowing them to list new projects or AI services. Token holders can pull specific datasets, analyze specific market trends, and interact with projects from various blockchains across the platform.
* **Revenue Sharing from AI Bots and Agents**: When AI agents or bots are commercialized through the platform, smart contracts will facilitate automatic revenue sharing between bot creators and stakers. Both developers and participants who stake their PANBLK tokens are rewarded based on the performance and usage of the bots.
* **Staking for Bot Verification and Governance**: PANBLK token holders can stake their tokens to prove the legitimacy and reliability of their AI bots. By staking PANBLK tokens, developers demonstrate that their bots are valuable contributors to the ecosystem and not harmful actors. This staked amount acts as a security deposit, ensuring that bots behave properly and benefit the broader community. In return, bot creators can earn revenue from the bots' performance, and those who stake can share in the revenue generated by these bots.
* **Monetization of AI Models and Agents**: Developers and community members can use PANBLK tokens to create, test, and deploy AI models and machine learning agents on the platform. These agents can then be monetized through offering services or virtual assets powered by the agents. Users can set flexible terms for their AI creations, enabling the community to purchase or license these agents.
* **Engagement Incentives for Testing and Feedback**: Community members who actively contribute by testing AI agents, providing feedback, or using AI-driven solutions will be rewarded with PANBLK tokens. This incentivization aims to promote constant platform growth and engagement, motivating users to help improve and refine the AI models/agents.
* **Marketplace for AI Agents**: PANBLK will serve as the primary currency within the platform's marketplace, where users can create, buy, and sell AI agents or bots. Developers can commercialize their work, while others can easily access pre-built tools using PANBLK.
* **Token-Gated Community Access**: PANBLK holders will gain access to exclusive community spaces, including developer forums, special events, and Q\&A sessions with experts.&#x20;
* **Incentivized Data Sharing**: Users can earn PANBLK tokens for contributing valuable data sets or insights that enhance the platform's machine learning models. This aims to incentivize community-driven data enrichment, improving the quality of AI agents on the platform.
* **Voting on Feature Development**: Token holders will be able to vote on platform features and future enhancements, helping shape the direction of the protocol.&#x20;
* **Token-Fueled Reputation System**: PANBLK tokens will play a role in the platform’s reputation system, allowing users to stake tokens as a form of reputation validation, ensuring trustworthiness, reducing malicious behaviors and improving the overall quality of AI models.
* **Referral and Affiliate Rewards**: Users who refer new members or projects to the platform can earn PANBLK tokens as a referral bonus.&#x20;


# Allocation

| Total supply: 1,000,000,000                      | TGE: Q3 2026                                  |
| ------------------------------------------------ | --------------------------------------------- |
| Investors (Seed + Pre-Sale + Strategic + Public) | ●     300,000,000 tokens (30%)                |
| Team                                             | ●     200,000,000 tokens (20%)                |
| Ecosystem & Growth                               | ●     50,000,000 tokens (5%)                  |
| Community                                        | <p></p><p>●     200,000,000 tokens (20%)</p>  |
| Marketing                                        | <p></p><p>●     100,000,000 tokens (10%)</p>  |
| Liquidity                                        | <p>​</p><p>●     100,000,000 tokens (10%)</p> |
| Treasury & Reserve                               | ●     50,000,000 tokens (5%)                  |


# Development Timeline

Please note that the events are subject to change; our roadmap is dynamic and may be adjusted accordingly.

### Phase 1: Proof of Concept

* [x] **Deploy Multi-Canister Architecture:**

  Utilize a multi-canister architecture in Motoko for scalable and efficient data management in the Bitcoin Blockchain.
* [x] **Retrieve Bitcoin Data:**

  Retrieve and store Bitcoin block data on the Internet Computer initially using Mempool.
* [x] **Analyze the Last 50 Blocks:**

  Focus on accurately analyzing the last 50 blocks by examining addresses, transactions, transaction volume, and the number of addresses in each block.

### **Phase 2: MVP**

* [x] **Backend Enhancement:**

  Refactor backend using Motoko and ICP’s TypeScript Azle CDK for real-time Bitcoin Blockchain data capture, with Rust for system programming. The frontend will utilize React and TypeScript to visualize data.
* [x] **Whale Alert Feature:**

  Real-time notifications on significant transactions by large holders ("whales") across multiple blockchains, identifying potential market movements and liquidity shifts by tracking large-scale transactions and transfers.
* [x] **Open Chat Integration:**

  Integrate a chat box widget into the Panorama Block data feed pages to facilitate community communication and interaction through the OpenChat chat box. This will allow us to develop a long-lasting integration and interaction with the OpenChat community, expanding the product offering to other communities within OpenChat like NFT and Gamefi communities.
* [x] **Scalability Improvements:**

  Enhance the multi-canister architecture supports scalability, ensuring the platform can handle increased user demand efficiently.

### **Phase 3:** Infrastructure Enhancement

* [ ] **System Optimization & Scaling:**

  Address latency issues by caching block, transaction, and address data from the last 2-3 hours in memory heap during Rust refactoring to enhance data retrieval speed.
* [ ] **Design Improvements:**

  UX adjustments to improve overall user experience and performance, including enhancements to the Whale Hunting tab, graphs, and dashboards across the interface.
* [ ] **SQLite Interface in Rust:**

  Develop a scalable relational database for ICP using Stable Variables for persistent storage.
* [ ] **Application Refactoring:**

  Migrate from Azle (TypeScript) to Rust to improve scalability, speed, and memory control.
* [ ] **Node Deployment:**

  Initially run the node externally with data stored on ICP, with future plans to fully integrate into ICP infrastructure.
* [ ] **Direct Blockchain Data Extraction:**

  Post-MVP, all data will be extracted directly from the blockchain, eliminating the need for third-party services.&#x20;

### **Phase 4: Expansion**

* [ ] **Bitcoin Additional Protocol Metrics:**

  Expand the analysis to include additional metrics within Bitcoin's Layer 1, such as active addresses, transaction volume within exchange wallets, token holdings in exchange wallets, miner reserves capital flow, market cap, and overall trading volume.
* [ ] **Expansion to Other Blockchains:**

  After completing BTC data integration, shift focus to Ethereum chain, ICP and Solana protocols.
* [ ] **Direct Blockchain Data Extraction:**

  Post-MVP, all data will be extracted directly from the blockchain, eliminating the need for third-party services.&#x20;

### **Phase 5: AI Systems & Additional Features**

* [ ] **AI Integration and Development:**

  Develop and test an AI-based protocol score system.
* [ ] **AI-Powered Bitcoin Analysis Integration:**

  Create a tool that collects, analyzes, and presents Bitcoin-related information/metrics using OpenAI's chatgpt. The goal is to automate complex data analysis, providing unique, actionable insights for Panorama Block users.
* [ ] **Development of Proprietary Tools:**

  Develop proprietary APIs, metrics, and dev tools to benefit traders, developers, and institutions.
* [ ] **Rank Select Product Connection:**

  Utilize these metrics for predictive neural network modeling on the Rank Select product to connect hundreds of protocols across dozens of blockchains.
* [ ] **Small Cap Tokens Radar:**

  Monitoring and alerting on small-cap tokens on Bitcoin L2, Ethereum, Solana, Arbitrum, BNB, Avax, and Polygon Chain showing unusual activity, growth potential, or sudden increases in trading volume, enabling early investment in emerging assets by highlighting tokens that are gaining traction.
* [ ] **New Projects Launch Radar:**

  Tracking and announcing new projects expected to launch soon across various blockchains, providing early access to on-chain data of promising projects so Panorama Block users can evaluate projects’ potential impact and value.
* [ ] **Sentiment Analysis Dashboard:**

  Utilizing AI for real-time sentiment analysis from social media platforms like Telegram, Discord, and X, as well as forums, providing insights into market mood and potential trends by aggregating and interpreting public sentiment data. This includes major Layer 1 and Layer 2 blockchains, with HTTPS outcalls being used to gather Web2 data.
* [ ] **Developer Toolkit:**

  Comprehensive suite of AI-powered development tools, including Canister Development Kits (CDKs), SDKs, APIs, and debugging resources, to build, test, and deploy blockchain applications.
* [ ] **Network Health Monitoring:**

  Real-time insights into the health and performance of different blockchain networks, with on-chain metrics like transaction speed, network congestion, and node distribution.
* [ ] **Security Alert System:**

  Detecting and alerting on potential security threats, vulnerabilities, and suspicious activities across connected blockchains.

### **Forward-Moving Plans**

* [ ] **Cross-Chain Compatibility and Interoperability:**\
  Design and develop bridge contracts to facilitate asset transfer and data exchange between Internet Computer and other blockchain networks.
* [ ] **SNS DAO and TGE:**
  * SNS Governance Testing and the establishment of Panorama Block’s SNS DAO.
  * Implement SNS SWAP and Token Generation Event.
  * Monetization model deployment including Token Airdrops and DEX Listing.


# Research and Development Collaboration

This whitepaper and tokenomics framework were developed in collaboration with graduate students from UCLA's Master of Quantitative Economics (MQE) program. Additionally, students from other top universities and research centers worldwide are actively contributing to the project.

#### Contributing Institutions

Below is a list of contributors and their academic affiliations:

| Name                        | University                                                | LinkedIn Profile                                                  |
| --------------------------- | --------------------------------------------------------- | ----------------------------------------------------------------- |
| Weiwen Sun                  | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/weiwensun/)                |
| Churongze Wang              | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/churongze-wang-3b253b299/) |
| Tanishq Tiwari              | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/tanishq-tiwari/)           |
| Jiyu (Judith) Zhu           | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/jiyu-judith-zhu/)          |
| Jingyu L.                   | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/jingyuluo0112/)            |
| Yue (Amber) Yu              | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/yue-yu-1b2034351/)         |
| Marcy Guo                   | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/marcyguo/)                 |
| Hiba F.                     | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/hiba-f/)                   |
| Xinyu Gu                    | UCLA – Master of Quantitative Economics                   | -                                                                 |
| Kevin Wang                  | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/jiafan-wang/)              |
| Boxiong Li                  | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/boxiong-li/)               |
| Edith Liu                   | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/edithliuzhihui/)           |
| Kevin Zhao                  | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/kevin-zhao-293096294/)     |
| Lemeng Shi                  | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/lmshi/)                    |
| Karan Mehra                 | UCLA – Master of Quantitative Economics                   | [LinkedIn](https://www.linkedin.com/in/karanmehra24/)             |
| Liza Shuwen                 | Loyola Marymount University – Data Science Studies Center | -                                                                 |
| Sehej Singh                 | Loyola Marymount University – Data Science Studies Center | [LinkedIn](https://www.linkedin.com/in/sehejs/)                   |
| Hugo Noyma (Core Team)      | Inteli – Institute of Technology and Leadership (BRA)     | [LinkedIn](https://www.linkedin.com/in/hugo-noyma/)               |
| Felipe Saadi (Core Team)    | Inteli – Institute of Technology and Leadership (BRA)     | [LinkedIn](https://www.linkedin.com/in/felipe-saadi/)             |
| Gabriel Coletto (Core Team) | Inteli – Institute of Technology and Leadership (BRA)     | [LinkedIn](https://www.linkedin.com/in/gabrielcolettosilva/)      |


# Disclaimer

Engagement on the Panorama Block platform is entirely at your own discretion. We urge you to conduct thorough research and review all accessible information. Keep in mind that cryptocurrencies and project performance come with no assurances, and it's important to avoid unnecessary risks.&#x20;

**Any content provided by Panorama Block should not be interpreted as financial advice.**