// case study
EOS Omnia
An energy data platform that brings together projects, assets, organisations, supply chains, news and market data, designed from day one to be used by people and by AI. It's an early-stage venture at Offshore Digital Engineering, who bring the offshore and energy transition expertise, and I head up engineering as their technical partner.
- with
- Offshore Digital Engineering
- timeline
- Feb 2026 – now
- role
- Head of engineering
- sector
- Offshore & energy
EOS Omnia: the globe, offshore wind farms, generation data and grid congestion
// context
Scattered information, slow decisions
The offshore energy industry runs on information that is spread across press releases, registers, supplier websites and market feeds. Teams spend a lot of time just finding it, reconciling it and keeping it up to date.
EOS Omnia pulls that into one connected, well-maintained platform, and makes it available wherever people work: in the web app, through APIs, or by simply asking their AI assistant.
// how it fits together
01 sources
- Public announcements
- Registers & filings
- Supplier information
- Market & grid feeds
02 research
- AI research agents
- Editorial review
- Change sets
03 platform
- Connected data model
- Staging → production
- Time-series store
04 access
- Web app
- APIs
- MCP for AI assistants
// what we built
One connected data model
Projects, assets, organisations and supply chains are related records rather than separate lists, so you can follow a wind farm to its developers, its suppliers and the news about all of them.
Market and grid time series
Daily market and grid data sits alongside the project data, so analysis and context live in one place instead of spread across spreadsheets.
AI-native access
Customers can work with the platform through their own AI assistants via the Model Context Protocol, asking questions in plain English and getting answers grounded in the records, with sources attached.
A safe editorial pipeline
Changes are planned as change sets, applied to staging, verified and previewed, and only then promoted to production, which keeps a fast-moving dataset trustworthy.
// my role
More than writing the code
The offshore and energy expertise comes from the business, and I look after the technical side, from the first cloud resource to the latest feature. Just as much of the job is being their technical partner: shaping the product together, testing ideas and talking to customers.
- setup
- Environments, cloud infrastructure, CI/CD and the staging-to-production workflow.
- architecture
- The data model, APIs and how AI agents read and write data safely.
- build
- Hands-on development across the web app, admin tooling and MCP servers.
- product
- New ideas, prioritisation and turning them into shipped features.
- customers
- On calls with customers, understanding how they work and what they need next.
// stack
- Model Context Protocol
- LLM agents
- APIs
- Data modelling
- Time series
- Cloud infrastructure
- CI/CD
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