AI Reliability Engineering
Proven,
or it does
not ship.
Turing Standard builds for teams where a wrong answer is a grounding event.
Three Products
An integrated practice for AI you can prove.
Adaptive Knowledge Engine
The knowledge layer.
Every answer cited, never hallucinated.
·$0 marginal model cost at ingest
·Bi-temporal graph, history preserved
·Deterministic, reproducible answers
Agentic AI Overlay
The reasoning layer.
Purpose-built agents, grounded by AKE.
·Per-client domain intelligence
·Typed, bounded tool calls
·Full decision traceability
Quality Audit & Assurance
The assurance layer.
Proven good, not just looking good.
·Four-layer proof gap verdict
·Reproducible KPI scorecard
·Quality gates on every change
The Proof Gap
Where the model sits determines what can be trusted.
The position of the language model in a pipeline is not an implementation detail. It is the architectural commitment on which every answer either stands or doesn’t.
Hover a row or click a node to see where each architecture places risk.
probabilistic model decides a fact
model used, but not on the answer
deterministic, cited
deterministic step, no model
Why AKE
Not a better retriever. A different architecture.
| Property | Generic Retrieval | AKE |
|---|---|---|
| Page-anchored citation on every fact | often partial | by construction |
| Refuses when it cannot ground an answer | answers anyway | fails loud |
| Per-record model cost at ingest | per-record calls | $0 |
| Reproducible from same input | variable | deterministic |
| Configuration validity decided by solver | not available | cited, deterministic verdict |
| New domain without engine changes | engineering build | data authoring |
AKE Whitepaper