KC-01Foundational
Technical Knowledge Assistant (RAG)
Ask a question about your own field in Persian, Arabic, English or Spanish and get an answer with the report and page it came from.
Knowledge & CopilotAI
KC-06IntermediateWave 2DomainAI
Expert Knowledge Capture
In one sentence
Captures what the experienced engineers know before they retire, in a form the next engineer can actually find.
The problem
A significant share of operational knowledge in this industry is unwritten and held by people close to retirement. Lessons-learned databases exist and are not used, because a free-text list of two thousand entries is not searchable in any practical sense.
How it works
Structured interviews and post-job debriefs are captured and converted into indexed decision records: the situation, the options considered, the choice made and the outcome. These are linked to the wells, equipment and capabilities they concern, so the knowledge surfaces when someone is working on the same problem rather than only when they go looking.
Data required
- Access to experienced staff for structured interview sessions
- Existing lessons-learned and incident databases
- Well and equipment master data for linking
- A facilitator to run the capture sessions — this is not self-service
What you get
- Indexed decision and lesson records linked to entities and capabilities
- Contextual surfacing of relevant lessons inside the operational workflow
- Coverage map showing which knowledge areas depend on which individuals
What it cannot do
Knowledge capture needs the expert’s time, and experts are the busiest people in the organisation. Without management commitment to protected time, capture sessions get cancelled and the programme quietly stops — this is the most common failure mode and it is organisational, not technical.
Every capability page states a real limitation. If a vendor cannot tell you where their product stops, you are not being told the truth about where it starts.
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