HyperDecision
Every recommendation shows its work.
HyperDecision is the decision-intelligence engine behind HyperOps: every recommendation carries its reasoning, inputs, and the humans who reviewed it — so people stay in control and the compliance evidence is a by-product, not a project.
Architecture & Mechanics
How it works in practice
Reasoning first, output second.
- A HyperDecision recommendation isn't just an answer — it's the answer plus the specific inputs and logic that produced it, in language a non-technical reviewer can actually follow.
- Below your defined risk threshold, a routine recommendation can execute automatically.
- Above it, a human reviews the rationale before anything happens — and that review is itself recorded.
From rationale to evidence.
- The rationale HyperDecision captures isn't just for the person reviewing it in the moment.
- It's automatically mapped to the specific ISO, NIST, and EU AI Act controls it satisfies, so the same record that justified the decision becomes the evidence an auditor asks for later — with no separate write-up step in between.
Where it shows up.
- HyperDecision powers every AI-assisted recommendation inside the AI & Decision Intelligence pillar, and its output is what HyperAgentOps attributes to a specific agent identity when an agent is the one acting on it.
See a recommendation and its rationale, side by side.
Questions
The short answers
It generates recommendations with full rationale; whether a given recommendation executes automatically or requires human sign-off depends on the risk threshold your governance policy sets.
The same record that explains why a recommendation was made — its inputs, logic, and any human review — is mapped to the specific compliance controls it satisfies, so it doubles as audit evidence without extra documentation work.
Thresholds are set against your governance policy; the exact configurability across decision types is being finalized in the product.
Most recommendation features surface an output. HyperDecision is built to surface the reasoning as a first-class, auditable artifact — that's the specific design choice that makes the rest of the evidence pipeline possible.