AI PROVENANCE INFRASTRUCTURE
Every AI agent is making decisions. Nobody can show their work.
TrustThread.ai gives every AI agent output a structured evidence chain — a Thread — showing exactly what it's based on, what was inferred, what was assumed, and where the trail goes dark.
Built on MCP · x402 · open provenance standards
OPAQUE
The question nobody can answer
An agent finishes a task. It says done. Somewhere downstream, a person, a company, or another agent acts on that claim — approves a filing, books a vendor, ships a decision.
Ask the obvious follow-up: based on what, exactly?
Right now, nobody can answer that in a way that holds up. Not the agent. Not the platform running it. The output looks confident. The logs say it ran. But "it ran" and "it was right" are different claims — and nothing in the current AI stack tells them apart.
CONFIRMED
Meet the Thread
Every AI output gets a Thread — a structured, visual evidence chain you can pull apart node by node. Every claim is classified by how it's grounded: confirmed against something real, inferred through traceable reasoning, openly assumed, or simply opaque because the agent didn't show its work.
One glance answers the only question that matters: how far down does this actually go before it stops being verifiable?
Typed evidence graph
Every node in a Thread is classified — confirmed, inferred, assumed, or opaque. No hidden guesswork, no black-box confidence score.
Human Validation Gate
A named human reviews and signs off, cryptographically, before a high-stakes output ships. Non-repudiable. Append-only. Impossible to fake after the fact.
Built for agents, not just humans
MCP-native. Priced per call. Machine-readable by design — because the next thing asking "can I trust this" is increasingly another agent, not a person.
THE VOCABULARY
We had to invent the words for this
There was no language for AI accountability, so we built one. This is how the next generation of AI infrastructure will talk about trust.
Groundline
The deepest confirmed node in a chain. How far the evidence actually goes before it stops being verified.
Fade Point
The exact node where a chain of solid evidence quietly turns into assumption.
Provenance Debt
The slow accumulation of ungrounded claims an agent racks up over time. Same shape as technical debt.
Shadow Assumption
A hidden assumption buried inside a claim that looks confirmed but isn't.
Human Validation Gate
A formal, named, cryptographically signed human sign-off. Not "the model said it's fine" — a person did, on the record.
Opacity Ratio
The share of a Thread's evidence that the agent simply didn't show. The single most important number nobody currently measures.
WHY NOW
The window is open. It won't stay open.
$146B+
in AI-related M&A over the past year
$281M
raised in AI governance funding in the last 12 months
40%
of enterprise apps will run task-specific agents by end of 2026 (Gartner)
Live
major AI accountability regulation is now in active enforcement
Every other layer of AI infrastructure has already been built — compute, orchestration, evaluation, observability. The provenance layer hasn't. Whoever builds it first owns the vocabulary, the data, and the trust relationships that come with being first.
HOW IT WORKS
Agent runs
Instrument any agent with the Thread SDK or MCP server. Takes minutes, not a sprint.
Evidence chain builds
Every step is classified in real time — confirmed, inferred, assumed, or opaque — as the agent works.
Quality is scored
Depth, confirmed ratio, and opacity ratio, computed automatically the moment the Thread finalizes.
A human signs off
A Validation Gate closes the loop — a named person, on the record, before anything ships.
EARLY ACCESS
Get in before the category has a name
We're opening early access to a small group of builders, operators, and investors who want to see this before it's obvious.
✓ You're on the list. We'll be in touch.