Same input. Same governed output. Every time.
Most inference is a dice roll. Ask twice, get two answers, with no way to prove why. SAGE runs the models you host on your own compute and makes the governed decision deterministic — same input, same governed output, sealed and signed. Every call is replayable by your auditor, offline.
Solves the problem that keeps AI in pilot: it answered differently in production than it did in the demo.
Same question in. The same governed answer out. Forever.
SAGE runs the models you host on your own compute and locks each governed decision to a single, reproducible answer.
A request comes in to a model you run on your own hardware.
SAGE computes the governed decision deterministically and seals it with a signature.
Ask the identical question next week or next year — you get the identical answer.
Anyone can replay a past call and confirm it, byte for byte, on a clean machine.
Normal inference is a dice roll — ask twice, get two answers. Other “governance” tools sample the output and hope it stays consistent.
SAGE removes the randomness from the governed decision at the source, so the answer is fixed and reproducible — not sampled, not hoped.
Why it’s better: Because every decision reproduces exactly, it’s auditable and replayable, and there’s no drift between the demo and production. See how we build it →
Same input. Same output. Six weeks apart.
The same question, run twice on a clean machine weeks apart, returns the identical governed selection — byte for byte. That is what makes a decision replayable, and what lets anyone reproduce it without us.
It was right in the pilot. In production it drifted.
A probabilistic model gives different answers to the same question — and the change shows up only after the action has fired. SAGE removes the drift at the source. The model is sealed, the selection is deterministic, and every call carries the proof it can be reproduced exactly.
Deterministic selection
The same input returns the same governed output, every call. No drift, no dice, no quiet change between runs.
Sealed and hash-pinned
The model is sealed and fingerprinted. If the weights are swapped, the hash no longer matches and the seal breaks.
Byte-identical selection replay
Re-run any past call and get the same selection back, byte for byte. The decision is reproducible, not remembered.
Signed on every call
Each inference carries a signed record of the input, the seal, and the selection, verifiable with a key we do not hold.
Runs in your environment
A GPU-first engine that runs on your compute, with your keys. Nothing about the call leaves your control.
Embeds inside AICP
SAGE sits under the control plane, so the deterministic call and the pre-action gate share one identity and one receipt.
Hand them any past call and they can replay it themselves — same input, same governed output, byte for byte.
Stop shipping a model that answers differently every time.
A receipt is only possible because the system is deterministic.