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Three pieces of work, each with the problem, what we built and what changed.
Secure data platform for a UK utilities operator: several teams, several data environments and nobody with the full picture. We surveyed the estate, fixed least-privilege access and the data-source approval process, made GDPR requests actionable, and rebuilt the platform as a data lake maintained through infrastructure as code and CI/CD.
Faster trading decisions for a commodity trading business: the existing platform could not keep up with the decisions the business had to make. We designed and delivered a data lake on AWS with near-real-time processing from many sources, meeting the industry’s compliance rules, on time and within budget.
Forward deployed engineer for an agentic workflow: a production line run by AI agents with a human at three gates, built by embedding with the client rather than handing over a spec.
A UK energy business was struggling to manage its data platform. DataPhoenix replaced it with a new data lake.
Commodity trading depends on fast decisions, many integrated data sources, flexibility and compliance. See how DataPhoenix helped a trading business decide faster.
Tell DataPhoenix about your data and AI goals and we will work with you on where to start and what to build first.
Ready to put AI to work on your data? Get in touch with the DataPhoenix team.