Use Cases
Where a wrong answer is expensive, proof beats opinion.
One deterministic engine, pointed at three surfaces — the code an agent writes, the outcomes a model produces, and the actions an agent takes. Below: where that matters most, in the regulated industries where "looks right" is a liability.
One engine, three lenses
Every use case here is the same move: take a rule that must hold, hand it to math, and prove the AI's work against it — applied through three lenses.
Lens 01 · Local / GitHub / PR
AI-generated code
Prove the code an agent wrote does what was claimed — functional equivalence, memory safety, security invariants — before it merges.
Lens 02 · ML / analytics / automation
Model outcomes
Ingest what a model produced and check it against hard constraints — physical, financial, regulatory — that the number must obey.
Lens 03 · Autonomous agents
Agent behavior
Audit multi-step agent runs against their own declared policy, and circuit-break any action that breaches a limit or runs out of sequence.
The lenses below are illustrative applications of the same deterministic core. A use case earns the proved tier only when a checkable invariant is declared for it — math raises the verdict, not the model.
Six regulated domains
Each domain applies the three lenses to its own highest-stakes work. Open a domain for its full set of use cases.
01 Financial services02 Healthcare & life sciences03 Cloud, DevOps & security04 Supply chain & industrial05 Legal & compliance06 E-commerce & gaming
Bring your domain's hardest rule
If you can state the rule that must hold, an authorized TrueVectors evaluation can check the AI's work against it — deterministically, with a receipt. Tell us the invariant that keeps you up at night.
TrueVectors verifies code, outcomes, and agent behavior. Trust through proof.