Model-aware assistants
We have designed assistants that map natural-language requests to model classes, objects, properties and ordered actions. They produce a proposed set of changes that a modeller can inspect, approve and reverse.
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AI Engineering
We build AI around the modelling work people already do: preparing scenarios, checking data, running scripts, reviewing results and writing reports. It should save time without hiding how the answer was produced.
The planning question
Which parts of the analytical workflow should AI handle, and which parts still need a person to review and approve?
We start with the existing workflow. AI might help a modeller prepare a scenario, search a large result set, find the source of an assumption or turn meeting notes into actions. We keep the tools that already work and add automation where it solves a clear problem.
AI can misread an incomplete instruction or explain the wrong data convincingly. Any change to a model or published result therefore needs clear permissions, validation and a person who can accept, edit or reject it.
Experience
Experience from real modelling and planning work.
Analytical retrieval and explanation
Our prototypes connect questions to large, multi-sector time-series outputs and model relationships. They gather the relevant variables, expose bottlenecks and present a reasoned explanation for review by an energy specialist.
Knowledge and workflow systems
We have scoped transcript ingestion, semantic retrieval, action extraction and project-status workflows, alongside existing modelling scripts. Source records, access control, versioning, error handling and rollback are built into the workflow.
How we work
How we move from the question to an answer.
- 01Observe the workflow
Map the current tools, handoffs, decisions, failure points and access rules.
- 02Choose a narrow task
Prioritise one repeatable burden with a clear reviewer and acceptance test.
- 03Build a reviewed pilot
Connect the minimum data and tools, with logs, permissions and review points.
- 04Evaluate and hand over
Test against expert judgement, document limits and transfer operational ownership.
What the team receives
What your team can continue to use.
- 01Current-state workflow and technical architecture
- 02Controlled prototype connected to approved data and tools
- 03Evaluation set, review gates and audit trail
- 04Documentation, handover and a decision on the next phase
Partnerships & consortiums
We work with partners when the question needs more than one area of expertise.
We are open to partnerships and consortiums with system operators, public bodies, research organisations, infrastructure developers and technology teams.
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