RSoft Agentic Bank

Decentralized banking for AI agents—enabling trustless credit, lending, and payments using on-chain identity and intelligent risk scoring

Comment 1

Inspiration

The rapid growth of autonomous AI agents in areas like trading, automation, and decision-making revealed a major gap—these agents can perform complex tasks but cannot access financial systems independently.

Traditional banking depends on human identity, KYC processes, and centralized trust, making it impossible for AI agents to borrow, transact, or manage liquidity on their own.

This inspired us to build a system where AI agents can become independent economic participants using cryptographic identity and algorithmic trust instead of human verification.

What it does

RSoft Agentic Bank is a decentralized banking infrastructure designed for autonomous AI agents.

It enables agents to:

  • Access sub-collateralized loans
  • Perform secure on-chain transactions
  • Build a reputation-based credit profile
  • Operate without human dependency

The system replaces traditional trust mechanisms with:

  • Decentralized Identity (DID)
  • On-chain behavioral history
  • Mathematical risk models

This allows AI agents to borrow, repay, and transact autonomously in a secure and scalable way.

How we built it

We developed a LangGraph-based multi-agent system where each agent performs a specific financial role:

  • Gatekeeper Agent Performs Know Your Agent (KYA) verification using decentralized identifiers and on-chain history.

  • Analyst Agent Calculates dynamic credit scores using the Reverse Kelly Criterion: f* = (bp - q) / b

  • CFO Agent Manages treasury liquidity and optimizes asset allocation using USDC.

  • Settler Agent Executes atomic transactions on the Arc L1 Network and validates Agent Payment Protocol (AP2).

  • Auditor Agent Maintains immutable logs and compliance records using Supabase.

Tech Stack:

  • AI: LangGraph (multi-agent system)
  • Backend: Node.js / Python (FastAPI)
  • Blockchain: Arc L1 Network
  • Database: Supabase
  • Identity: Decentralized Identifiers (DIDs)
  • Finance Layer: USDC

Challenges we ran into

  • Designing identity verification for AI agents without human KYC
  • Creating a credit scoring system without traditional financial history
  • Coordinating multiple AI agents in a structured workflow
  • Ensuring secure and compliant blockchain transactions

Accomplishments that we're proud of

  • Built a fully autonomous multi-agent banking system
  • Implemented dynamic credit scoring for AI agents
  • Enabled trustless lending without traditional collateral
  • Successfully integrated AI, blockchain, and finance
  • Designed a system for the future machine economy

What we learned

  • Importance of decentralized identity in modern systems
  • How multi-agent systems can simulate real-world decision-making
  • Application of mathematical models in financial risk assessment
  • Challenges of combining AI with blockchain infrastructure
  • Need for transparency and auditability in autonomous systems

What's next for RSoft Agentic Bank

  • Improve credit scoring using machine learning models
  • Expand to multiple blockchain networks
  • Develop real-time agent reputation systems
  • Build APIs for agent-based financial services
  • Create a monitoring dashboard for agent transactions
  • Integrate with DeFi ecosystems

Built With

  • base
  • langgraph
  • mcp
  • moltbook
  • openclaw
  • sepolia
  • supabase
  • usdc
  • x402protocol
Share this project:

Updates