The evidence
- Mandate, model digest, and workload identity
- Region and data-handling restrictions
- Meter observations and reconciliation differences
AIgenTXS / AI Compute + Inference
AIgenTXS is designed to connect a compute mandate with the permitted workload, evidence of delivery, and reconciliation of the observed result. A provider’s report is an input to review, not independent proof by itself.
Why this workflow needs a record
An inference request carries more than a model name. Budget, region, data-handling restrictions, image identity, and metering all shape the permitted workload. Keep those terms attached through delivery so a reviewer can distinguish what was requested, reported, and independently observed.
Inside the workflow
Choose a scenario to inspect the proposed action, governing rule, evidence, and person responsible.
The proposed action
Illustrative workflow. No live action.
An interactive policy example
Adjust one sample input, declare the evidence, and record a simulated approval. A boundary failure remains a failure even when approval is checked.
Sample compute mandate$20,000
Still needed: independent delivery evidence attached.
Illustrative inputs and one simplified policy rule. Calculated in this browser; no upload, stored decision record, provider call, or external action. This is not a deployed industry workflow.
What stays attached
The tenant defines the permitted workload and spending scope. The model or provider cannot enlarge that mandate.
Reconciliation distinguishes an accepted request, reported completion, and witnessed delivery. Payment or settlement requires its own authorized pathway.
Start with one workflow
Tell us what your team needs to govern, which evidence matters, and who owns the decision.
AIgenTXS’s mandate-to-effect architecture is implemented and tested in-repository with synthetic fixtures. Product runtime deployment, customer use, and independent attestation are separate milestones.