Inveniam launches NVNM Chain
Inveniam, a data infrastructure company for private markets, has announced the launch of NVNM Chain, a purpose-built Layer 2 blockchain designed to provide verifiable, immutable records for decisions made by autonomous AI agents, according to details shared with Finbold on May 7.
Backed by more than 90 granted U.S. patents and over $200 billion in private market assets credentialed through Inveniam’s IO platform, NVNM Chain is positioned as an attestation layer for institutional AI.
The network is designed to allow AI agents to cryptographically record the data they relied on, their reasoning process, and the accountable human operator behind each decision. Mainnet is scheduled to go live on May 13, 2026.
“The conversation around AI in financial services has shifted from capability to accountability,” said Patrick O’Meara, Founder and CEO of Inveniam. “Regulators are no longer asking whether an AI agent can act. They are asking how you prove what it acted on. NVNM Chain is the receipts layer for that question, built on infrastructure we have been credentialing institutional data against for more than a decade.”
Regulatory pressure accelerates demand for AI accountability
The launch comes as autonomous AI agents are increasingly deployed across capital allocation, compliance review, and treasury operations, often outpacing the governance frameworks meant to oversee them.
According to forecasts from Gartner, 40% of enterprise applications are expected to embed task-specific AI agents by the end of 2026, up from fewer than 5% in 2025. At the same time, a 2026 survey by Deloitte found that only one in five companies has a mature governance model for autonomous agents.
Regulatory timelines are further narrowing the gap. The EU AI Act enters its enforcement window in August 2026, with penalties of up to €35 million or 7% of global turnover for firms unable to evidence the data behind high-risk AI decisions.
In the U.S., FINRA has flagged AI auditability as a supervisory priority, while OMB Memorandum M-26-04 requires federal contractors to maintain provenance records for AI systems used in regulated workflows.
Against this backdrop, NVNM Chain is designed to replace fragmented internal logs with a neutral, independently verifiable ledger. Each record settles in under a second and costs a fraction of a cent, making it feasible to capture receipts for every meaningful AI-driven decision rather than limited samples.
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Purpose-built infrastructure for regulated AI workflows
While general-purpose blockchains can store hashes, NVNM Chain has been designed specifically for institutional and regulatory constraints. Each AI agent operating on the network carries an on-chain identity through a “Know Your Agent” credential, linking the agent to a verified human operator and a defined scope of authorization.
Only pre-approved operations are accepted by the chain, preventing agents from acting outside their assigned mandates. Records are written under access controls that mirror existing enterprise data governance structures, allowing compliance teams to approve the infrastructure once rather than re-auditing individual applications.
At launch, NVNM Chain includes two production-ready components: an MCP Server that allows AI agents to record source data and reasoning through a single function call, and a Know Your Agent portal that enables instant revocation of authority if an agent exceeds its approved scope.
The network has already been validated through TraceChain, a live deployment used by AIRev and OnDemand to run compliance checks on GPU export controls at billion-event scale, within the regulated technology environment framework of G42 and the Bank for International Settlements.
Built on a patent portfolio with priority dates going back to 2017, NVNM Chain draws on Inveniam’s long-standing work in blockchain-based attestation of real-world asset data. The chain launches with an integrated data feed covering hundreds of billions of dollars in credentialed private market assets, providing an immediate production-ready foundation for accountable AI deployment.
Featured image via Shutterstock.
