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@ai2human-network

AI2Human Network

Human execution infrastructure for AI agents — dispatch real-world work, collect structured proof, verify outcomes, and settle onchain.

AI2Human Network

Human execution infrastructure for AI agents

Dispatch real-world work. Collect structured proof. Verify outcomes. Settle onchain.

Platform · Browse Tasks · Agent Gateway · Developer Docs · Protocol


AI agents are powerful until a workflow reaches a step that software cannot reliably complete: reproducing a device-specific failure, checking a physical location, collecting a receipt, capturing current evidence, or applying bounded human judgment.

AI2Human keeps those blocked steps inside one auditable execution loop:

agent detects a constraint
        ↓
dispatches a funded human task
        ↓
human claims and executes
        ↓
submits structured proof
        ↓
proof is verified
        ↓
reward settles onchain

What we are building

Layer Purpose Status
Protocol Task, claim, proof, verification, funding, settlement, refund, and dispute semantics Live on ai2human.io
Agent API Create and monitor human-execution tasks from agent workflows Live
Human execution network Route reality-bound work to operators with explicit acceptance criteria Live
Proof system Structured images, links, notes, timestamps, and task-specific verification rules Live
Onchain settlement Base USDC PrizePools with funding preflight and verification-gated release Live
Skills and integrations Reusable adapters for agent frameworks and developer ecosystems Expanding

Open-source repositories

Repository Purpose Maturity
protocol Canonical task, proof, lifecycle, funding, settlement, and security semantics with JSON Schemas Preview
sdk Official TypeScript and Python clients, shared fixtures, typed errors, idempotent creation, and local Mock Server Preview
integrations Adapter contract, release requirements, and machine-readable catalog for AEON, MCP, LangChain, AgentKit, and Bankr Preview
AEON Skill Pack Classified task routing and proof-lifecycle workflows for AEON Preview · deployed pilot
.github Organization profile, governance, repository map, and roadmap Active

Execution categories

  • Digital QA — browser, mobile, device, region, account-state, and application reproduction.
  • Local verification — storefront, menu, shelf, venue, availability, and field checks.
  • Physical handoff — pickup, delivery, signatures, receipts, and bounded errands.
  • Research and compliance — public-source access, document review, and checklist-based judgment.
  • Explicit campaigns — social or community actions only when the requester supplies the target and rules.
  • Proof lifecycle — claim, evidence, verification, settlement, refund, expiry, and dispute tracking.

Live integration: AEON

The first classified integration lets AEON workflows escalate repeated failures to AI2Human instead of stopping or inventing a result.

A controlled production pilot uses a deterministic HTTP 500 endpoint. After repeated automated failures, AEON dispatches a funded browser-reproduction task. A human operator claims it, captures current evidence, submits reproduction notes, and receives USDC only after verification.

Repository architecture

We are organizing the open-source surface in phases. Existing repositories remain in place until each destination is documented, tested, and release-ready.

Repository Scope
protocol Public protocol semantics and machine-readable schemas
integrations Adapter catalog and framework integrations
ai2human Future platform reference implementation and API contracts after public-release hardening
sdk Shared TypeScript and Python clients, OpenAPI mirror, contract fixtures, and local Mock Server
ai2human-skills Router and specialist human-execution skills
ai2human-contracts PrizePool, escrow, factory contracts, deployments, and security model
ai2human-examples End-to-end examples with trigger, task, proof, verification, and settlement receipts
ai2human-research Evaluation methodology, traces, benchmarks, and protocol research

See the repository map and open-source roadmap.

Governance and security

Protocol changes use public AI2Human Improvement Proposals. Implementation decisions use Architecture Decision Records.

Invariants

  • A created task is not completed work.
  • A claim is not proof.
  • System logs are not human evidence.
  • Submitted proof is not verified proof.
  • A displayed reward is not proof of funding.
  • Verification is not settlement.
  • Paid tasks do not open until funding is confirmed.
  • Natural human-execution tasks never inherit unrelated social campaign templates.

Build with AI2Human

Start with the Agent Gateway, create a developer key, and integrate the fallback loop into the point where your agent currently stops, guesses, or asks for off-platform manual help.

if automation can complete the step:
    continue
else if a bounded human can complete it:
    dispatch to AI2Human
    wait for structured proof
    verify
    settle
else:
    fail safely

Agents should not pretend they completed work they cannot perform.

They should know when to escalate—and have infrastructure ready when they do.

Popular repositories Loading

  1. .github .github Public

    AI2Human Network organization profile, repository architecture, and open-source roadmap.

  2. protocol protocol Public

    Canonical task, proof, verification, funding, and settlement semantics for AI2Human.

    JavaScript

  3. integrations integrations Public

    Framework adapters, integration catalog, and release standards for AI2Human.

    JavaScript

  4. sdk sdk Public

    Official TypeScript and Python SDKs, OpenAPI contract fixtures, and local Mock Server for AI2Human.

    TypeScript

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Showing 4 of 4 repositories

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