NCE (Neural Context Engine) is the quality engine embedded in KnowWeave. It measures the reliability of every answer across 14 dimensions — and refuses to answer when confidence is insufficient.
A measurable, auditable quality score, communicated without filtering — not an opaque probability.
Architectural traceability: At every step, NCE traces what it extracts, why, and from which document. Traceability is architectural — not added after the fact.
The NCE reliability score aggregates 14 dimensions measured continuously on the knowledge network. Each NCE version is compared to the previous one on these same dimensions. These 14 dimensions are not a final state — they are a permanent R&D axis: each engine iteration is built to surpass the previous one, dimension by dimension, towards an ever-higher reliability score.
Only entities present in the knowledge network can appear in an NCE answer. No interpolation. No extrapolation. If the entity is not in the base, it is not in the answer.
If no source in the network is relevant to the question asked, NCE refuses to answer — without LLM call, without fabrication. The refusal message is explicit and customisable by business domain.
Every generated answer is submitted to an independent verifier that compares the answer to its cited sources. Binary verdict: FAITHFUL or CONTRADICTION. Production deployment in progress.
Layer 4 · deployment in progressPRD and SAS are the two reliability dimensions on which the NCE engine is under active research. Their full integration completes the score to 14/14 and unlocks agentic missions.
An entity connected to the rest of the graph by a single path is a fragile entity. If that path is removed or modified, the answer fails silently. PRD identifies and scores all single-path entities — allowing the agent to qualify the robustness of its own answer.
● Path Reliance DegreeAn entity poorly positioned in the engine's semantic memory will be retrieved on the wrong questions and missed on the right ones. Result: answers that seem correct but are not — a silent cause of errors, difficult to diagnose without this specific score.
● Semantic Alignment Score · ref. academic research 2025Each sector has a set of reference questions with expected answers (ground truth). Standardised format — the same battery is replayed at each NCE version on the same corpus.
Every new version is benchmarked against the previous one. Measured KPIs: average score, pipeline confidence, out-of-domain refusal rate, contradiction detection rate. No figures published without this protocol.
All test sets are documented and available under NDA for clients in evaluation. The evaluation methodology is part of the delivery contract.
Entity and relation extraction from text corpus. Generic relations. First knowledge graph queryable in natural language.
Sector domain schema. Extraction guided by conceptual model. Per-extraction confidence scoring. 12 active reliability dimensions.
Entity deduplication. Noise node filtering. Semantic cache. Anti-hallucination whitelist. Fidelity validation implemented. Structural table parsing.
Full reliability score on 14 dimensions. Autonomous cognitive agents capable of operating on continuously evolving living corpus. End-to-end auditable answers — every assertion traced to its source, ready for regulatory inspection or external audit. The platform that answers the question your teams have been asking for ten years.
Bring a bounded corpus. We show how NCE ingests it, what it extracts, and how it answers your domain questions.
14 reliability dimensions ◆ Anti-hallucination ◆ Complete source traceability