VERITY
A verifiable second brain — audit-grade, governed knowledge infrastructure, delivered as a service.
See how it worksMost "second brains" are a search box over a pile of documents
No guarantee an answer is sourced. No way to tell good data from broken data. No record of what changed. No owner for the AI quietly touching the data.
Verity is built around those gaps, not the demo. Every finding is schema-validated, every source is frozen and traceable, the pipeline reproduces identical output on re-run, and the system audits itself before it's trusted.
Source → schema → validator → migration → roll-up
A pipeline where nothing enters the brain unless it passes the gate
A complete pipeline: raw documents land in an inbox, get validated against a pinned JSON-Schema contract, and migrate into a frozen, read-only canonical store. From there, two independent passes run against the corpus — a stateful spread/fingerprint analysis and a separately-logged closure red-team — each writing only to its own folder, so every stage is re-runnable and auditable on its own. One Bash-orchestrated command runs the full loop and produces identical checksums on every re-run.
Verifiable. Reproducible. Governed.
Three properties most AI knowledge tools can't claim
Gated, not hoped for
Schema conformance is enforced at the door. Malformed data is excluded, never quietly mixed in with good data.
The same answer twice
Run it twice, get identical output. Identical checksums on every re-run — not a chatbot that improvises a new answer each time.
Owned and risk-tiered
Every component is owned and risk-tiered, and an independent adversary attacks the corpus's own findings before anything is declared closed.
Nothing enters the brain unless it passes
Verifiable at the door · reproducible on re-run
Conforming documents pass into the canonical store. Malformed data is deflected at the gate and excluded — never quietly mixed in with good data.
Run the same corpus twice and the pipeline returns identical checksums. The brain gives the same answer twice — not a chatbot improvising a new one each time.
Proven now — and an honest roadmap
A working prototype, single-tenant, run end-to-end on a real corpus
- Canonical instrument with pinned weights and version lineage, enforced by a preflight guard
- JSON-Schema contract and the validator that gates against it
- Idempotent orchestrator — one command runs the full loop
- AI governance register — every system owned, risk-tiered, zero orphans
- Self-audit / teardown pass that blocks closure until limitations are documented
- A multi-document corpus processed end-to-end through every stage
- Per-vertical instrument profiles — same core, swappable domain rules per industry
- Multi-tenant isolation — per-client data and findings separation
- A thin, read-only client-facing retrieval skin — the "ask your brain" front door
- Scheduled per-client runs tied to a retainer, plus billing and SLA
"A system that documents its own limitations is the product thesis, applied to itself."The prototype is real and single-tenant today — the productization path is scoped and sequenced, not speculative.