Safeguard's reasoning engine — turns engine output into human-reviewable findings and fix PRs.
Griffin AI is the reasoning layer inside Safeguard. It sits on top of the deterministic engine — which handles SBOM parsing, reachability analysis, signature verification, and policy evaluation — and does the work that determinism cannot: turning structured engine output into something a human engineer can act on, in English, with receipts.
Griffin is a large language model, but it is not a chatbot. It takes typed, schema-validated input from the engine, emits typed output back into the pipeline, and is governed by an eval harness that refuses to ship a new version until it clears a published benchmark suite. The outputs — exploit hypotheses, fix-PR bodies, triage summaries, zero-day narratives — are always grounded in engine facts, never free-generated.
Four architectural commitments separate Griffin from "we wrapped a chatbot around a scanner":
Deterministic engines produce structured facts. Humans need narratives, fixes, and gates. The translation between the two is where most security products lose their users — and where naive LLM bolt-ons produce the confident-but-wrong outputs that have made "AI for security" a suspect phrase.
Griffin is the deliberate, boring answer: a reasoning layer whose scope is bounded by what the engine can prove, whose output is gated by published evaluations, and whose benchmarks are on the internet rather than in a slide deck.
Taint path, exploit hypothesis, disproof, and fix suggestion — assembled into prose a reviewer can approve without becoming a researcher.
Every Griffin-drafted PR carries the engine's evidence trail — so the reviewer approves a fix, not a vibe.
When the engine flags a suspicious publication, Griffin produces the explain-in-English case that gets routed to a human or a customer alert.
Published benchmarks make "the AI got smarter" a claim you can check against data — not a product-marketing adjective.
Policy and reachability stay deterministic; narrative and synthesis come from the model. The combined architecture produces both guarantees and usability.
Every Fix PR, zero-day narrative, and triage summary in Safeguard goes through Griffin. The engine proves; Griffin explains; a human approves.
Point Safeguard at your code. Watch Griffin produce the first three Fix PRs with full taint paths and disproof artefacts.