ForgingStack · San Antonio, Texas
Systems that
prove their work.
We build evidence-citing AI agents, auditable runs, and contracts that fail closed. If a system cannot show its evidence, it does not ship — that is the whole discipline, and it is the whole product.
- Rule 1
- A claim is not a result.
- Rule 2
- Every run leaves a receipt.
- Rule 3
- Failure closes, it does not drift.
How a run becomes proof
Capture. Freeze. Enforce.
Most systems describe what they should do. ForgingStack captures what actually happened, freezes it as the contract, and enforces it automatically. The diagram below is scrubbed by scroll — it moves only when you move.
01
Capture the run, not the intention. HAR recordings, tool outputs, and evidence records — the raw material, kept.
02
Freeze the contract. What happened becomes the spec, versioned, so a later change is visible as a change.
03
Enforce it in the build. A missing field, a drifted claim, a broken link — a red build, not a customer report.
From the forge
Heat, pressure, and a receipt.
Forging is not decoration here. Heat changes the material, pressure shapes it, and the finished piece can be inspected. The loop below is local, muted, and loads only when it scrolls into view — it never competes with the hero for first paint.
Local files only: /video/hero-loop.mp4 · /video/hero-loop.webm · poster /video/hero-poster.webp. No embeds.
Selected work
Built to be audited.
Agent reliability · Open source
EvidenceForge
An open-source framework for building auditable, evidence-citing AI agents.
Read the case →
API tooling · Developer product
mimicplus
Record a HAR, get a versioned spec, a typed Python client, OpenAPI, and a breaking-change check.
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Multi-agent systems
Governed Agent Engine
A governed multi-agent engine: Termux-installable, stdlib plus PyYAML, with spec binding and audit.
Read the case →
Bring a system that needs to prove itself.
One email, one project, one receipt at the end. Start with what you are building and what “done” has to prove.
Contact ForgingStack