The energy world
Projects, turbines, solar, storage, grid, organisations and markets. Start with connected records and source context — not a blank conversation.
INTELLIGENCE ENGINE · PRODUCT CONCEPT · IN DEVELOPMENT
The world keeps changing.
Your intelligence should too.
A connected intelligence layer for the entire renewable energy picture — designed to discover what matters, investigate why, and explore what it could mean for your next opportunity and existing exposure.
This page describes the intended system, not a currently running autonomous service. The database and Atlas remain separate, available entry points.
ONE CONNECTED PICTURE
From a single turbine.
To the forces shaping a market.
The ambition is not another chat window. It is a system that connects physical assets, commercial commitments and changing conditions — with your organisation’s own context.
Your world
Bring your portfolio, pipeline, technical and legal due diligence, agreements, operating data and financial assumptions into the same context, subject to permissions.
The analytical picture
Link resource and power curves to production scenarios; prices and PPAs to revenue; inflation, delivery and counterparties to project economics. Models make assumptions explicit.
- 01Projects & assets
- 02Resource & climate
- 03Grid & infrastructure
- 04Markets & prices
- 05Agreements
- 06Economics
- 07Organisations
- 08Documents & evidence
Conceptual relationships. Source-backed connections are required in use.
The market / INVESTIGATION SCOPE
Discover the connections you didn’t think to look for.
The proposed engine looks across projects, organisations and markets for emerging patterns — then investigates which ones have supporting evidence.
A QUESTION THE ENGINE COULD OPENWhich changes form a wider pattern?
Market context → emerging patterns → evidence to investigate
Look across the connected picture for changes, shared dependencies and unexpected patterns — not just answers to a search.
PROACTIVE BY DESIGN
Not one question.
A system of investigations.
Proposed specialist workflows work together across technical, commercial, legal and financial questions. They share evidence, challenge assumptions and identify what needs further investigation.
Discover without a prompt
Search for patterns across the connected picture: shared dependencies, conflicting records and changes that might matter before anyone has formulated a question.
Follow the evidence further
An investigation can open new branches, delegate specialist questions and compare competing explanations. Its depth should follow the evidence and importance of the issue — within agreed time and cost limits.
Trace consequences across domains
Test how a change could travel from equipment, grid or contracts into output, revenue and financial assumptions. A relationship is a lead to investigate, not proof of cause.
Revisit the whole picture
Follow new evidence across prospective projects and existing exposure. Reuse relevant work without losing source dates, access boundaries or the assumptions behind a conclusion.
Resource & climatePower curves & productionGrid & curtailmentPower prices & forecastsPPA & offtakeInflation & financingLegal & technical DDCounterparties & ownership
INTELLIGENCE YOU CAN QUESTION
Every conclusion needs
something behind it.
The intended evidence model separates source statements, calculations and hypotheses. Missing data is visible. Disagreement is preserved for investigation, not quietly merged away.
What the evidence says.
Trace a statement to a registry, document, page or customer record, with its date and scope. A source citation is not independent verification.
What the assumptions imply.
Inspect inputs, methods and scenario results. Estimated generation is not actual production; financial outputs depend on the inputs available.
What still needs an answer.
Keep inferred relationships, conflicting evidence and missing measurements visible. Show what would confirm or disprove a hypothesis.
DESIGNED TO IMPROVE THROUGH EVALUATION
Learn from what actually happens.
Not from repeating an answer.
Where outcomes become available, compare them with earlier forecasts and findings. Evaluate which sources, matching rules and models performed well — then review and version improvements before applying them.
Customer-private evidence stays within its access boundaries. No promise of automatic accuracy gains, and no unrestricted cross-customer learning.
BUILDING TOWARDS THIS — WITH A REAL FOUNDATION
Your data. Your exposure.
A much wider field of view.
Tell us what you need to understand, which assets you follow and where the evidence lives. Help shape a system that goes beyond waiting for the next question.
Discuss your use case