Every answer is reviewed
Each model output is read by an independent layer that forms its own judgment — separate from, and not influenced by, the model that produced the answer.
Product
A real-time quality gate for any LLM.
QSI reviews each LLM output, flags the ones likely to be wrong, and fails open — so you know which results to trust without adding a single point of failure.
Risky outputs are flagged
Answers that are likely incorrect are surfaced with a calibrated confidence, so your team and your systems know exactly which results to hold back.
Trustworthy outputs pass through
When an answer reads as reliable, QSI gets out of the way. No friction on the outputs that were going to be right anyway.
Fail-open, always
If QSI is uncertain or unavailable, the answer flows through untouched. It is governance, not a chokepoint — it never adds a new way for your product to break.
Architecture
It runs beside inference — not in front of it.
QSI sits off the critical path. Requests reach your model and responses reach your users exactly as they do today. QSI observes each answer in parallel and attaches a verdict. The user-facing path is never gated by QSI being fast, available, or certain.
That is the whole posture: add a layer of judgment, subtract zero reliability.
Fail-open, explained
The safest governance layer is one that can never take you down.
Most controls you bolt onto inference are gates: if they break, your product breaks. QSI is built the opposite way.
If QSI is confident
It flags likely-wrong answers and passes the trustworthy ones — exactly the value you bought it for.
If QSI is unsure
The answer flows through as a calm, neutral fail-open — never marked as an error, never blocked.
If QSI is unavailable
Your inference path is unaffected. QSI being down is invisible to your users by design.
Where it fits
One layer, wherever answers leave a model.
Reviews every answer
An independent layer reads each model output and forms its own judgment — separate from the model that produced it.
Flags likely-wrong outputs
Outputs that are probably incorrect are surfaced with a calibrated confidence, before they reach a user.
Fail-open by design
QSI never blocks inference. If it is unsure or unavailable, the answer flows through — governance, not a gate that breaks.
Put a quality gate over your AI — without adding a way to fail.
See QSI review live answers across your models and domains.