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A compiler that owns the truth, with AI at the rim.

Everything is a file in Git. Ejadah compiles those files into facts, facts into a typed knowledge graph, and runs deterministic analysis over it. Findings carry their own provenance. AI sits at the rim — proposing edits that return to the repository as ordinary commits a human reviews.

  1. 01

    Repository

    your artifacts, in Git — the only source of truth

  2. 02

    Facts

    what the sources say, extracted 1:1, uninterpreted

  3. 03

    Knowledge

    roles become typed relationships in one compiled graph

  4. 04

    Evidence

    deterministic findings and metrics, with provenance

  5. 05

    Intelligence

    questions answered, impact traced, drift detected

  6. 06

    Git edits

    AI proposals return as commits — reviewed, then part of the truth

The loop closes: step six returns to step one. Nothing enters the truth except through the repository.

Trust

Engineering that can prove itself.

In safety-critical and regulated environments, trust cannot be a promise in a slide deck. It has to be a property of the architecture — something the system is structurally unable to violate.

Evidence, not probability
Engineering decisions require proof. Every conclusion is computed from your artifacts, not predicted from patterns.
Traceable to source
Every finding cites the artifacts, the rule, and the commit that produced it. Why does it say that? always has a mechanical answer.
AI proposes, never attests
Suggestions remain suggestions until deterministic verification accepts them. Inferred results are marked, and excluded from evidence.
Compiled governance
Policy is resolved once, at load, and enforced identically for everyone — not re-interpreted by whoever runs the check.
Reproducible from a commit
One repository state regenerates every report, byte for byte, on any machine. A report that depends on who ran it is not evidence.
Your knowledge stays yours
Git-first and file-based. No proprietary database, no export step, no lock-in. Remove us, and everything you built remains.

Privacy & deployment

Private by design. Deployed on your terms.

Private by design
Deterministic analysis runs entirely in your environment. It needs no cloud to function and no account to start.
You own the data
Your repository is the source of truth. There is no other store, and no proprietary database.
AI on your terms
One gateway, any provider: cloud, local, or customer-hosted models — your endpoint, your credentials, opt-in, and removable.
Runs where your engineering runs
On engineer workstations today, with no server required. Self-hosted and enterprise deployment follow the same file-first architecture.
Air-gap capable
Deterministic analysis is fully functional offline. AI features attach to models inside your perimeter — or stay off.
No silent data collection
Nothing leaves your environment without explicit configuration. Anything that does is visible, yours, and off by default.

Organizational memory

The organization remembers — even when people move on.

Every decision is recorded with its rationale and its rejected alternatives, versioned with the engineering it governs. When the question comes back in three years — and it always comes back — the answer is in the repository, not in a departed engineer's head.

That turns knowledge from a depreciating asset into a compounding one. Every artifact, every decision, every review makes the graph more valuable — and onboarding faster, because the reasoning is finally somewhere a newcomer can read.