Platform / RiGi Group
AI Inference Creator
Define custom inference endpoints and evaluation steps for specialized workloads.
WWAIOS / AI Inference Creator
The role of ai inference creator in a governed workflow
Define custom inference endpoints and evaluation steps for specialized workloads.
07 / 09
Capabilities
What the layer is designed to handle
Test behavior and cost before production routing.
Version endpoint configuration and supporting evidence.
Operating pattern
A control path you can inspect
- 01Define the input, context, and authorized purpose.
- 02Specify the task, model interface, and expected output.
- 03Test behavior and cost before production routing.
- 04Capture the result, exception, and owner for review.
Questions for architecture review
What would change your decision?
Ask which evidence is current, which control actually executes, who owns an exception, and where a human must approve an action.
Explore
Adjacent layers
AI HarnessBind model interactions into a defined runtime with shared controls and observable behavior.↗AI Decision EngineDescribe decision paths, policy conditions, and approval points as explicit workflow rules.↗AI GuardrailsApply runtime checks around sensitive data, unsafe requests, and output constraints.↗AI Knowledge BaseConnect retrieval to governed sources so answers can point back to what supports them.↗
A closer look / AI Inference Creator
From question to evidence to decision.
Use this framework to discuss the actual workflow and the proof needed to move forward.
01 / Situation
Specialized inference often needs its own task contract and evaluation set.
02 / Approach
Define endpoint inputs, outputs, model configuration, adapters, fallback, and release criteria as a versioned package.
03 / Evidence
Compare candidate behavior, latency, quality, and spend on representative workloads without presenting estimates as operating results.
04 / Next decision
Approve a route only when deployment and evaluation evidence are current.