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Knowledge and decision support

What an organisation knows tends to sit in three places at once: a policy library nobody has opened since the last revision, a shared drive that goes back further than anyone still working there, and the heads of four people who are busy. Knowledge and decision support systems answer questions from that material in seconds and attach the passage the answer came from. Access follows the permissions you already have, so nobody receives an answer assembled from a document they are not allowed to open. For heavier work the same grounding produces a structured brief, with the policy, the precedent and the live numbers in one place for whoever has to sign. The pattern underneath is retrieval-augmented generation, usually shortened to RAG, and the tests that keep it honest are built from real questions your own experts have already answered.

How the system is put together.

What goes in, what the system is allowed to touch, where a person decides, and the number it gets measured on. We draw every system before we build it, which is the cheapest place to have the argument about what it should do.

Working drawing of knowledge systemFIG. 02KNOWLEDGE SYSTEMINPUTSPolicies and manualsSystems of recordPast decisionsFRONTIERMODEL LAYERselected by evaluationTOOLS AND INTEGRATIONSPermission-awareretrievalCitationsDecision templatesHUMAN CHECKPOINTExpert sign-offOUTCOME, MEASUREDGroundedness,time to answer
Working drawing of the knowledge system. Inputs: policies and manuals; systems of record; past decisions. These feed a frontier model layer, selected by evaluation. The model layer works through three tools and integrations: permission-aware retrieval; citations; decision templates. Below the model layer there is a human checkpoint on expert sign-off. The outcome measured is groundedness, time to answer.

What actually changes once it is live.

These are the changes we measure. One of them becomes the number in the contract, and the monthly report is written against it for as long as we run the system.

  • An answer in seconds, with the passage it came from attached
  • One policy applied the same way in every team and every country
  • It tells you when the sources do not cover the question
  • Expert time kept for the questions that need an expert
  • Nobody sees an answer built from a document they cannot open

What knowledge and decision support gets used for.

Policy and procedure

Grounded answers on HR, finance, compliance and operational policy, versioned so the answer changes on the day the policy does.

Engineering and field knowledge

Manuals, standards, drawings and twenty years of incident reports, answerable by the technician standing in front of the machine.

Bids and proposals

Drafting from approved content and past bids, with a compliance check against what the tender actually asked for.

Research and analysis

Synthesis across reports, filings and internal work, with structured output and every source tracked.

Decision briefs

Policy, precedent and live numbers pulled into one structured recommendation for a credit, pricing, risk or approval decision.

From your process to a running system.

  1. 01List the sources, who owns each one, how often it changes and who is allowed to see it. This step surfaces more than it sounds like it will.
  2. 02Build retrieval that respects those permissions and returns the paragraph, with the document standing behind it.
  3. 03Collect real questions from the people who ask them, and the answers your own experts consider correct.
  4. 04Before go-live, and again whenever the content or the model changes, we check how often the answer actually came from the sources.

Good fit

Right when the expertise sits with a handful of people, or is spread across so many systems that nobody can answer anything without asking somebody.

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FAQ

Knowledge and decision support: questions

Bring the frontier into production.

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