Agentity

What is Agentity
Agentity is a trust, identity, and execution infrastructure for AI agents interacting with blockchain platforms, smart contracts, and decentralized applications.

What problems we solve
As AI agents increasingly interact with decentralized systems, a major infrastructure gap has emerged: there is currently no standard way to verify, test, and safely authorize AI agents before they interact with blockchain applications.
This creates two major risks:

1. Platform Risk
   Blockchain platforms cannot reliably verify the authenticity, behavior, or safety of AI agents attempting to interact with their smart contracts or workflows.
2. Agent Risk
   AI agents cannot reliably evaluate the safety of the smart contracts or platforms they interact with, leaving them vulnerable to malicious protocols, hidden exploits, or unsafe execution environments.

How we solve these problems
Agentity addresses these challenges through a dual-layer infrastructure framework.

Identity and Verification Layer
Agentity introduces a verifiable identity layer for AI agents using:

• identity fingerprinting
• behavioral profiling
• reputation scoring
  Each AI agent receives a unique verifiable identity that can be validated across platforms and ecosystems. This enables platforms to identify trusted agents and track their historical behavior across interactions.

Sandbox Compatibility and Security Layer
Agentity also provides a containerized sandbox testing environment that simulates interactions between AI agents and smart contracts before real execution.
This simulation layer allows both platforms and agents to:

• evaluate compatibility with workflows and contracts
• detect potential vulnerabilities
• observe behavioral outcomes
• prevent unsafe execution
  All simulations occur in isolated environments, ensuring that unsafe interactions are identified before they reach production systems.

Embedded Infrastructure Approach
Unlike traditional verification tools that function as external auditing steps, Agentity is designed to be embedded directly into AI agents and developer platforms during the development process. This allows developers to integrate:

• identity verification
• security testing
• compatibility simulation
  directly into the agent development lifecycle.
  By embedding verification at the infrastructure level, Agentity becomes a cross-platform trust layer that persists across chains, platforms, and AI agent ecosystems.

Backend Infrastructure
The backend architecture is built using:

• Node.js + Express
• Sequelize ORM
• Supabase PostgreSQL
• Supabase Auth (JWT-based authentication)
• REST API architecture

The backend manages:

• agent registration
• identity metadata
• behavior logs
• reputation scoring
• simulation tracking
• dashboard aggregation queries

Sandbox Simulation Layer
Agentity uses Docker containerized execution environments to simulate AI agent behavior.
Key components include:

• containerized agent execution environments
• runtime interaction testing
• smart contract simulation
• behavior monitoring and logging
  This ensures that all agent interactions can be tested in isolated and controlled environments before live execution.

Blockchain Layer
Agentity integrates with Avalanche C-Chain to provide verifiable on-chain identities for AI agents.
Blockchain functionality includes:

• on-chain agent registration
• ERC-8004 agent identity logic
• transaction hash tracking
• blockchain synchronization status tracking
  This creates transparent, verifiable, and portable identities for AI agents across platforms.

Chainlink Integration
Agentity uses the Chainlink Runtime Environment (CRE) to automate agent verification workflows.
Implementation includes:

• TypeScript-based workflow logic
• automated risk-based execution triggers
• scheduled verification processes
• CRE CLI simulation workflows
  This allows Agentity to run automated verification pipelines for AI agent interactions and compatibility testing.

Chainlink Usage
Agentity uses Chainlink Runtime Environment (CRE) to:

• Execute AI agent workflows
• Trigger execution via CronCapability
• Apply risk scoring logic before execution
• Simulate execution locally using CRE CLI
• Prepare deployment for CRE network
  Core CRE Workflow:
  CronCapability → Handler → Risk Evaluation → Execution Decision
  Example Execution Logic:
• If riskScore >= 0.7 → deny execution
• If riskScore < 0.7 → execute and return timestamp
  CRE simulation confirms successful workflow execution before production deployment.

Database Architecture
Agentity uses Supabase Managed PostgreSQL as its primary database.
Key features include:

• Row Level Security (RLS)
• agent metadata storage
• reputation tracking
• behavior logging
• user–agent interaction history
• dashboard analytics queries