🤖Elsa AI Automata

The Elsa AI Automata architecture is a sophisticated, multi-layered system designed to enhance user interaction with blockchain environments. At its core, it consists of:

1. DAO Monitor:

   • Enables community to submit and verify data for processing to be feed into the AI layer through Data Engine.

   • It also accepts and proposes proposals to the community for writing scripts to be used in script-based workflows.

2. User: User will be able to interact with Elsa through NLP, also voice commands.

3. Elsa AI Automata: The central AI unit comprising:

   • User Profile Agent: Manages user-specific data and preferences. Behavioural and risk parameters are stored for inference and suggestions of tokens or ideas

     Example

     • Deposit 100 USD on Aave for 6% interest

     • Yield farm on Kamino by providing LP on Solana

   • Chain Analyser Agent: Scans and interprets blockchain data from realtime data feeds and then feeds to the multi model LLM agents for finding relevent info for the Elsa AI layer to act upon. Notifications are sent to users using the data, which fits our criteria and security params.

     Example

     • New NFTs alert!, there is a NFT released by disney, Do you want to get it

     • New Token listed and has done 5M worth of trades

     • It's a memecoin fever, here are the top memecoins that are trending

   • Intent Agent: Intent agent simplifies blockchain interactions for users. Users can set their intended outcomes, and the system handles the complex steps. This not only reduces the complexity of direct chain interactions but also helps enforce desired outcomes. Plus, users can express preferences for possible outcomes, and the system identifies the best execution.

     Example

     • Buy a pudgy penguin at under 25 eth

     • Create a basket for buying 10 memecoins for $100, newly added on Solana

   • Data Engine: Data engine plays a crucial role in its functionality. It runs data pipelines that transform data into values, enhancing the AI's decision-making capabilities. This engine also incorporates efficient data storage systems to manage and use for future. The key function of the Data Engine is to serve data consistently, which is crucial for training the AI models and making real-time inferences.

   • Risk Management Engine: Evaluates potential risks and offers mitigation strategies. Monitors users portfolio and triggers stop loss. Risk parameters of users are updated as per user activity and knowledge.

     Example

     • Users can set stop loss at 10% for the whole portofolio or say when BTC is down 10% in 1 hour trigger stop loss and sell all.

   • Onchain Script Engine: Automates and executes scripts approved by the DAO, based on the users actions.

     Example

     • Staking 100 USD on the top three Cosmos networks

     • Airdrop Farm Syncswap in the ZK-sync era.

4. Execution Layer: This is the point of interaction with various blockchains, where transaction execution is managed. It ensures efficient transaction execution through batch and intent-based transactions. Securing and monitoring outgoing transactions with data from Chain agent and mitigates any new issue on chain.

   Example

   • Solana network is congested, park the transactions and schedule the less urgent ones for later.

   • Run Simulation and also suggest improvements to tx builder on Elsa AI layer.

External Dependencies:

1. Data Pipelines:

   Data Pipelines play a key role in Elsa AI Automata, ensuring the smooth flow of data through the system. This not only enhances the AI's decision-making capabilities but also ensures the system remains agile and responsive to changing user needs and market conditions.

   • Chain Data Providers: These providers offer data from multiple blockchains, which is then processed and analyzed by Elsa AI Automata.

     • Token Terminal

     • Dune

     • Nansen

     • Arkham

     • Coingecko

     • DeFillama

   • Oracle Providers: Oracle providers offer external data to Elsa AI Automata which is used for various functions like price feeds, events data etc.

     • Chainlink

     • Pyth

     • DIA

   • External Data Providers: These providers offer data that is not directly related to blockchain but is crucial for Elsa AI operations, like user data, market data, etc.

     • Twitter

     • Discord

     • Telegram

     • Web data Analytics

2. External Agents:

   Vision APIs and Voice Agents

   Elsa AI Automata also incorporates Vision APIs and Voice Agents to support diverse user inputs. This enables users to interact with the system using both visual cues and voice commands, offering a more comprehensive and accessible user experience.

   Sentiment Analysis Agents

   Sentiment Analysis Agents are a crucial part of Elsa AI Automata. These agents analyze user sentiments and feedback, providing valuable insights into user satisfaction and preferences. The insights gleaned from this analysis are used to improve and personalize the user experience.