Restrictledger
A spend-control and attribution layer for nonprofit AI agents that checks scoped budgets and permitted categories, maps approved transactions to restricted-fund subledgers, and preserves reviewable grant-compliance evidence.
Agent wallets can already enforce transaction and period limits, while payment protocols make machine purchases practical. Those controls do not answer the nonprofit accounting question: which award, budget line, purpose, approval, and cost-allocation rule support a particular expense? Restrictledger adds a fund-aware policy and evidence layer between an agent request and payment. Its defensible asset is not payment routing but the reviewed history connecting each request, authorization, settlement, accounting export, exception, and supporting artifact.
The finance, grants, operations, or compliance leader at a nonprofit allowing software agents to purchase paid data, services, or other program inputs.
The supplied transaction and active-agent figures indicate a current adoption window.
Nonprofit finance and grants teams own a concrete authorization, allocation, and audit-evidence job.
The input carries several connected ideas and live infrastructure evidence but moderate independent convergence.
A concrete nonprofit finance buyer, live agent-payment rails, current transaction growth, and a specific fund-attribution gap support the concept.
Fund rules are award-specific, payment authorization does not establish allowability, integrations and review remain difficult, and generic wallet providers can expand.
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