AI Quality Framework
A measurable quality framework covering task success, grounding, safety, escalation, latency, cost and user experience.
Control areas
Task success
Document the applicable requirement, accountable owner, evidence and review cadence.
Accuracy / grounding
Document the applicable requirement, accountable owner, evidence and review cadence.
Safety and policy adherence
Document the applicable requirement, accountable owner, evidence and review cadence.
Escalation quality
Document the applicable requirement, accountable owner, evidence and review cadence.
Latency and reliability
Document the applicable requirement, accountable owner, evidence and review cadence.
Cost per useful outcome
Document the applicable requirement, accountable owner, evidence and review cadence.
User experience
Document the applicable requirement, accountable owner, evidence and review cadence.
Change regression testing
Document the applicable requirement, accountable owner, evidence and review cadence.
Evidence-first approach
Trust claims should be supported by actual controls, records, configuration, testing or contracts. DataLgorithmics does not present unverified certifications or compliance statuses as facts.