An AI cache affects more than latency. Reusing an answer can reuse assumptions, sensitive context and an earlier interpretation. Velocize treats caching as a governed runtime choice: the task and effective AI posture determine whether reuse is appropriate, while execution records distinguish cached output from live inference.
Separate exact reuse from semantic similarity
The runtime supports exact-query reuse and embedding-based semantic matching. Matching is bounded by tenant and feature, and entries expire according to the task’s cache lifetime. A semantic hit is a candidate reuse path, not proof that two business decisions are equivalent.
Cache eligibility is checked before using the cache path. Workflow-bound contexts require explicit permission, while jury and disabled/human-only modes do not use that reuse path. Live incidents and code generation are examples of work for which the pipeline does not retain reusable answers.
Keep context access and cached output reviewable
Role, stage, profile, sensitivity and scope define the governed context for AI. A cache hit must not be used as a shortcut around source access or required review. Changes to the matter can make an older answer unsuitable even before its lifetime expires.
The result identifies whether it came from exact cache, semantic cache or the provider. Hit/miss and inference usage statistics support operational analysis. Cache state remains a performance mechanism; approvals and accepted evidence stay in the lifecycle records.
Use bypass and controlled inference when reuse is unsafe
Expired, unsuitable or policy-disabled cache paths lead to live inference or the governed continuation appropriate to the assignment. Embedding and semantic-cache failures can degrade to provider execution; provider restrictions still apply.
Sensitive source material, external uploads and tool results remain subject to access and trust boundaries. Cached text is not an authorization token, and an AI-produced instruction is not permission to execute a privileged action.
Application scenario and operating value
A team repeatedly asks for an explanation of stable project terminology and also requests current incident status. The first task may be eligible for reuse within its tenant and feature context; the second needs live information. Give the two tasks different cache postures instead of using one global performance switch.
A useful caching policy reduces repeated permitted work without making stale or unauthorized answers authoritative. Its success includes accepted output and correction behavior as well as hit rate. Cache statistics and retained work answer different operational questions.
- Separate stable and live tasks.
- Require explicit workflow cache eligibility.
- Review changed source and permission context.