Mercury Labs · Applied AI
Senior-led delivery · London
We design, build and operate AI systems for organisations where a promising prototype is only the beginning.
Strategy without delivery becomes slides. Delivery without operating discipline becomes another pilot. Mercury Labs brings the whole path together with a senior team that stays close to the work.
01
We identify where AI can change the work, test the underlying data and constraints, and turn the strongest opportunities into a practical delivery plan.
Opportunity map · evidence audit · technical roadmap
02
We design and build complete products around the people who will use them—from specialist internal tools to customer-facing services and decision support.
Product design · full-stack engineering · AI integration
03
We connect fragmented documents, databases and APIs into reliable data products that give people and AI current, permission-aware business context.
Data pipelines · semantic search · governed knowledge
04
We build agents that can retrieve evidence, use approved tools and move work forward within explicit limits, reviews and escalation paths.
Tool use · approval flows · systems integration
05
We make quality, safety and accountability testable with representative evaluations, access controls, evidence trails and release gates.
Evals · guardrails · auditability · human oversight
06
We deploy into the environment that fits the organisation, then monitor, support and improve the system once it meets live users and changing data.
Cloud deployment · observability · managed support
Available now
New from Mercury Labs · MLX
Mercury Labs has launched MLX, our governed Business Twin. It constructs approved business context from the systems you already run, ready for the AI tools and workflows you choose.
Xero
SunSystems
Stripe
GoCardless
Microsoft 365
SharePoint
Google Drive
Google Docs
Google Sheets
Notion
HubSpot
Gmail
Calendar
Outlook
Slack
Teams
Granola
GitHub
Linear03 — Selected work
01
IfATE
Operating context
Expert-led assurance inside a national standards system.
Supporting the Institute for Apprenticeships and Technical Education with systems designed around expert review and public-sector assurance.
Delivery focus
02
Skills England
Operating context
Policy and planning teams working across national skills evidence.
Turning complex labour-market and skills evidence into practical tools for policy, planning and delivery teams.
Delivery focus
03
MTC
Operating context
Innovate UK-funded workforce foresighting across UK manufacturing.
We built the WFH Datacube for capability mapping and map-and-gap analysis, alongside OrCa Explorer—a public portal for semantic discovery of organisations and capabilities.
Delivery focus
04
Forestreet
Operating context
High-volume specialist research with evidence at its core.
Product and engineering work for a market-intelligence platform designed to make specialist research faster and more accessible.
Delivery focus
Clear evidence, explicit decision gates and an operating model from day one. Speed matters, but only when it lowers the time to a useful, supportable system.
Phase 01
Map goals, constraints, current systems and delivery risks. Validate the data reality and establish success measures.
Phase 02
Define the architecture, security model, evaluation plan and smallest useful pilot with clear acceptance criteria.
Phase 03
Prove value before scaling. Senior engineers build the production system with tests, evals and regular stakeholder demos.
Phase 04
Move into production with runbooks, monitoring and accountable support tied to the outcomes agreed at the start.
Start with the hard part
We will help you determine whether AI is the right tool, what must be true for it to work, and the fastest responsible path to a live system.
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