Neurochain-DSL-Stellar
Validated typed Stellar plans, deterministic guardrails, and an x402-lite challenge and finalize flow with replay protection.
View the x402 buildStellarZeroLab builds NeuroChain DSL, a deterministic security layer for AI agents and automated Stellar workflows. Requests become typed ActionPlans, pass guardrails, and can be proven against private policy before execution.
One deterministic runtime, three clear surfaces: policy evaluation, private proof, and safe agent integration.
Turns AI and automation requests into typed Stellar ActionPlans and applies deterministic guardrails before execution.
Proves private-policy decisions with RISC Zero and verifies the receipt on Soroban without revealing owner rules.
Exposes the same no-submit Plan, Evaluate, Prove, Verify workflow through CLI, API, MCP, and Skills.
The architecture stays legible by separating intent, policy, proof, payment, and execution authority.
NeuroChain exists because AI and automation should not move directly from intent to blockchain execution. Requests first become typed ActionPlans, then pass deterministic policy checks and optional private proof. Signing and submission remain separate, explicit operations.
Two public DoraHacks builds tested separate parts of the same safety architecture against real Stellar workflows.
Validated typed Stellar plans, deterministic guardrails, and an x402-lite challenge and finalize flow with replay protection.
View the x402 buildValidated private-policy evaluation, RISC Zero receipts, Soroban verification, and the no-surprise-submit boundary.
View the ZK buildNeuroChain began as an independent technical project in spring 2025 and evolved through practical work on deterministic AI execution, Stellar automation, x402 payments, and private-policy verification.
Developed independently and self-funded, with each technical layer built and tested before the next was added.
Typed ActionPlans, guardrails, Soroban verification, and x402 turned the original idea into a working testnet system.
Public demos and technical review narrowed the work into a security and authorization runtime for agents and automation.