Keep the memory, evidence, and records that make AI accountable.
VortexAQ Storage is the data foundation for governed AI systems: retrieval assets, audit records, provenance metadata, evaluation traces, and operational intelligence.
Turn AI activity into durable institutional knowledge rather than disposable prompt exhaust.
Make every AI decision queryable after the fact.
Storage needs its own identity: an evidence substrate that connects prompts, outputs, model versions, policy decisions, human review, and retention into one durable operational memory.
~$ vortex storage query traces --project claims-ops --since 24h[ok] Resolving storage contract...[ok] Bound signal: Durable recordawait vortex.records.write({ collection: "ai_decisions", subject: request.id, links: [model.id, policy.id, evaluator.runId], retention: "regulated-7y", payload: { promptHash, outputHash, reviewerId },});Artifacts: prompt/output hash · retention ledger · evaluation trace- Persist prompts, model choices, policy decisions, and outcomes as linked records.
- Attach retention and access controls at write time.
- Query operational memory for audits, evals, and incident review.
- prompt/output hash
- retention ledger
- evaluation trace
Turn AI activity into durable institutional knowledge rather than disposable prompt exhaust.
Deployment briefing ↗Primitives your teams ship against.
Concrete behaviors and interfaces so security, platform, and product teams share one operational picture.
Governed stores for retrieval, logs, traces, and evaluation evidence
Retention-aware records for regulated operational workflows
Verifiable metadata linking models, prompts, policies, and outcomes
Analytics-ready structures for cost, quality, and risk insight