Build agents you can trust.

Most enterprise agents do not fail loudly. They drift. AttestDB turns policies, tickets, documents, and prior work into a claim system agents can rely on, with traceability, contradictions, timestamps, and corrections built in.

$ ingest knowledge -> extract claims -> answer with sources

Every answer tied to a source. Conflicts stay visible. Changes propagate automatically.

Where it fits Between your data and your agents sits Attest. The trust layer that turns scattered enterprise knowledge into claims agents can cite, update, and retract. See the full picture →
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Interactive
SFDC Gainsight Jira Zendesk LinkedIn Slack 0 1.0
Customer Success

Five say healthy. One says churn.

Interactive
RETRACTED c1 c2 c3 3 downstream claims flagged
Biomedical

Retract the paper. Weaken the rest.

Interactive
DataPipe $47K 12× above per-vendor median
Finance

A $47K line that shouldn't be there.

Interactive
1.0 0.6 0.2 Day 1 Week 6
AI Trust

Agent says yes. Reality says no.

How it works
Your agents do not fail loudly. They drift.
Enterprise AI breaks in subtle ways. A policy changes and the agent keeps using the old one. Two sources disagree and the model picks one without telling you. A bad document lands upstream and the error quietly spreads everywhere else.

Policies change

Your agent keeps answering from last quarter's document because nothing in the stack knows the underlying rule changed.

Sources conflict

Different systems say different things, but the final answer hides the contradiction instead of exposing it for review.

Bad inputs spread

One wrong source becomes many wrong answers because there is no dependable way to retract the claim and flag what depends on it.

No audit trail

When someone asks why the agent answered the way it did, there is no source chain, timestamp, or confidence to inspect.

Foundation
Turn knowledge into agents you can trust.
AttestDB stores knowledge as claims. Each claim carries a statement, a source, a timestamp, and a confidence value. That gives your agents a system that can trace answers, detect contradictions, and respond when reality changes.
attest.answer("Do you support SOC 2 compliance?")
Claim "Company policy requires annual SOC 2 Type II audit" security-policy.pdf
Source "Latest completed audit: SOC 2 Type II" trust-center-report.pdf
Answer "Yes. Supported by current policy and audit evidence." answer trace
Trace "Every answer links back to the evidence chain" claim graph
statement · source · timestamp · confidence
Updates
When knowledge changes, your agents update.
This is the important difference. Most systems help agents access knowledge. AttestDB helps them stay correct over time.

Ingest

Bring in policies, tickets, trust documents, and prior questionnaire responses instead of rebuilding knowledge by hand for every workflow.

Extract claims

Turn those materials into structured claims with provenance so each answer is grounded in specific evidence instead of an opaque retrieval result.

Answer with sources

Let agents respond with citations, timestamps, and confidence so operators can see why an answer is safe to use or where it is uncertain.

Propagate changes

When a policy is revised or evidence is withdrawn, dependent claims are flagged or corrected automatically instead of drifting silently forward.

Use cases
Start with the workflows where drift already hurts.
Agent reliability

Build agents you can trust

Turn enterprise knowledge into sourced claims so answers stay traceable, contradictions stay visible, and bad information does not drift silently forward.

Learn more →
Security questionnaires

Keep trust answers current

Map policies, past responses, and evidence into claims so questionnaire answers stay sourced, update when evidence changes, and expose stale trust statements fast.

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For developers

A database for knowledge that changes

Use sourced claims, retractions, contradiction handling, and time-aware queries as primitives instead of bolting provenance onto rows or embeddings later.

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Under the hood
Ingestion
1.3M claims/sec
Rust engine, single-threaded
Query latency
~12µs indexed lookups
Microsecond queries, sub-millisecond on LMDB
Storage
Single file
No server, no config — like SQLite
Integrations
30 connectors + 106 MCP tools
Slack, GitHub, Gmail, Postgres + Claude Code, Cursor, Windsurf, Codex, Gemini
Why Attest
Built for correctness over time.
Traditional storage layers assume the data is correct. AttestDB assumes knowledge changes, conflicts, and sometimes needs to be withdrawn.
AttestDB Pinecone / Weaviate Neo4j PostgreSQL
Atomic unit Sourced claim Vector embedding Edge Row
Provenance Required on every write Optional metadata Optional property Not built-in
Retraction cascade Automatic Manual Manual
Contradiction handling Evidence-weighted Last write wins Last write wins Last write wins
Confidence scoring Built-in (0–1) Similarity score
Query latency ~12µs ~10ms ~5ms ~1ms
MCP tools 106
Most systems help agents access knowledge. AttestDB makes sure that knowledge stays correct over time.

The pattern shows up everywhere high-stakes knowledge lives across policies, tickets, docs, and operational systems. The hard part is not access. The hard part is keeping answers traceable, current, and safe as the underlying evidence changes.

Start in 60 seconds. No account required.

$ pip install attestdb && attestdb quickstart

Free & open source. Full Rust engine. Runs locally forever.

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