RAILS: Verification-Native Clearing For Agentic Commerce
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Abstract (arXiv)
Autonomous agents negotiate, purchase, deploy code, and move funds, but no neutral mechanism determines whether they met their delegated obligation, who is responsible when they did not, or which settlement action follows. This is the agentic clearing problem. Tool protocols (MCP), inter-agent communication (A2A), payment rails (x402), mandate and network agent protocols (AP2, Visa, Mastercard), and settlement-risk standards each assume that determination and none produce it. Clearing is the missing primitive. Payment is not clearing. Authorization is not clearing. LLM-as-judge evaluation is not clearing. Settlement-risk escrow is not clearing: it consumes clearing decisions. RAILS (Real-Time Agent Integrity & Ledger Settlement) is the integrity and clearing layer for agentic commerce, spanning a per-output reliability score, a published reliability record, and a clearing function that consumes them. The clearing protocol at its core closes that gap. Seven primitives (Obligation Object, Evidence Envelope, Verification Mesh, Clearing Decision, Settlement Instruction, Clearing Passport, Finality Rules), bound by a formal model of admissibility-graded verification, together yield a soundness property: no financially material settlement is supported by evidence below the obligation's admissibility floor. The property is falsifiable against the spec. We are not aware of a prior agent-commerce verification mechanism that states a property of this kind. The approaches nearest to it emit a pass, a delivery guarantee, a bare score, or an equilibrium. This paper specifies that clearing protocol.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 11 of its 29 references that are in the map. First posted on arXiv 7 Jun 2026.
Builds on
11 of 29 references.
References · 11
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
- 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
- 2023AgentBench: Evaluating LLMs as Agentscited by 1,211
- 2024BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systemscited by 26
- 2025Inter-Agent Trust Models: A Comparative Study of Brief, Claim, Proof, Stake, Reputation and Constraint in Agentic Web Protocol Design-A2A, AP2, ERC-8004, and Beyondcited by 8
- 2026Quantifying Trust: Financial Risk Management for Trustworthy AI Agentscited by 8
- 2026A402: Binding Cryptocurrency Payments to Service Execution for Agentic Commercecited by 6
- 2026TessPay: Verify-then-Pay Infrastructure for Trusted Agentic Commercecited by 4
- 2026The Surprising Universality of LLM Outputs: A Real-Time Verification Primitivecited by 3
- 2025A Protocol for Trustless Verification Under Uncertaintycited by 2
- 2026Machine Psychometrics: A Mathematical Psychology of Artificial Intelligencecited by 1
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Citing papers per year: 2026: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
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- 2026Compliance-Aware Agentic Payments on Stablecoin Rails
- 2026A Decision-Centered Reference Architecture for Trustworthy Agentic Commerce
- 2026Zero-Trust Runtime Verification for Agentic Payment Protocols: Mitigating Replay and Context-Binding Failures in AP2
- 2026Agentic Commerce Bench: Measuring Fraud Detection for Agents That Spend Money
- 2026AIP: Agent Identity Protocol for Verifiable Delegation Across MCP and A2A
- 2026Authority-Inference Separation in Agentic Finance: First-Line Control, Blockchain Enforcement, and Replayable Assurance
- 2026A Black Box for Agentic Processes: Blockchain-Anchored Evidence for AI Agent Communication, Human Oversight, and GRC Audits