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Concept Engine

Operational Evidence Intelligence

Everyfactgraded.Everyclaimsource-cited.

We turn dispersed technical documentation, legacy systems, codebases and expert know-how into a verified knowledge base — every material fact linked to its source and checked for contradictions.

Stance

Where evidence is missing, we flag the gap or refuse. We never generate a plausible answer.

~110,000

Lines of embedded SQL decoded

24 / 184 / 557

Workflow classes / states / transitions validated against ~24.5M log rows

~466

Database tables attributed to their functions

780 → 0

Validation false positives eliminated across 230 files

Why generic AI fails here

Retrieved is not the same as true.

Generic AI tools treat retrieved content as equally trustworthy. In a complex operational environment that assumption fails — documents contradict each other, versions are superseded, code and logs contradict the documentation, and expert knowledge sits in heads that leave.

Our method starts from the opposite assumption: a claim is only as strong as its evidence, and evidence must be graded, not assumed. Where the record is incomplete, we say so.

The method

A four-step evidence discipline.

The method is not a product feature. It is a set of working rules that keep every fact, table and claim accountable to its origin.

Graded definition: What is operational intelligence?
01

Grade

MEASUREDINFERREDSTAKEHOLDER-CLAIMED

Every material fact is tagged MEASURED, INFERRED or STAKEHOLDER-CLAIMED. The strength of the evidence is recorded alongside the fact itself.

02

Source-link

Every claim is traceable to its source: the exact document, table, log row, code module or interview that produced it.

03

Check

Automated integrity checks surface contradictions, superseded versions and orphaned facts before they become decisions.

04

Refuse

Where evidence is missing, we flag the gap or decline to answer. We do not generate a plausible claim to fill the silence.

Proof

Two enterprise engagements. Measured outcomes.

Both engagements are anonymised. The figures are measured, not inferred from a generic benchmark.

Engagement 01

A global testing, inspection and certification company

A 25-year-old, largely undocumented core system forensically reconstructed: the resulting evidence platform holds 300+ cross-linked documents and ~400 evidence-graded facts, every one source-linked. Automated integrity checks were tuned from 780 false positives to zero across 230 files — and behaviour was validated against ~24.5 million production log rows, not taken on trust.

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Engagement 02

A top-3 German automotive OEM

The same evidence-graded corpus method, applied in a second enterprise context: an agentic software-development-lifecycle platform prototype, delivered in partnership with an established systems integrator. The method was bootstrapped onto this engagement in ~1 day, with zero cross-client content carried over.

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Begin

If your critical knowledge is dispersed across legacy systems, codebases and expert heads — start with an enquiry.