Mercury Labs · Delivery method
Senior-led · Evidence-first
Discover first. Prove before scale.
We turn ambiguous AI opportunities into useful, supportable systems through evidence, explicit decision gates and senior engineering from day one.
- Start with
- A real operating problem
- Decide with
- Evidence and explicit gates
- Finish with
- A live, owned service
Four phases. A decision at every boundary.
Each phase reduces a different kind of uncertainty. Work advances when the evidence supports it—not because a roadmap says it should.
Phase 01
Discovery
Map goals, constraints, current systems and delivery risks. Validate the data reality and establish success measures.
- Question
- Is there a problem worth solving?
- Primary output
- Scope, evidence map and delivery guardrails
Decision gate
Evidence, constraints and success measures agreed
Phase 02
Solution design
Define the architecture, security model, evaluation plan and smallest useful pilot with clear acceptance criteria.
- Question
- What is the smallest useful system?
- Primary output
- Architecture and pilot plan
Decision gate
Architecture and acceptance criteria approved
Phase 03
Validation and build
Prove value before scaling. Senior engineers build the production system with tests, evals and regular stakeholder demos.
- Question
- Does it work with real users and data?
- Primary output
- Working system and measured results
Decision gate
Measured value clears the go or no-go review
Phase 04
Deployment and support
Move into production with runbooks, monitoring and accountable support tied to the outcomes agreed at the start.
- Question
- Can it be safely owned and operated?
- Primary output
- Live service, monitoring and ownership
Decision gate
Production readiness and service handover complete
Built for ownership, not dependency.
The method is designed to expose risk early, keep decisions legible and leave the organisation stronger than we found it.
- 01
The people who win the work do the work.
- 02
Frontline knowledge comes before solution hypotheses.
- 03
Data reality is tested before benefits are modelled.
- 04
Pilots have explicit go or no-go gates.
- 05
Every system is designed for ownership and continued operation.
Useful on day one. Operable for the long term.
Delivery is complete when the system works, its limits are understood and somebody can confidently own what happens next.
01
A working system
Production code, integrations and infrastructure built around the real operating environment—not a disconnected prototype.
02
Evidence and controls
Evaluations, decision records, access controls and monitoring that make quality and accountability visible.
03
An operating model
Runbooks, ownership, support routes and a clear path for the client team to operate and improve what has been built.
Have a difficult system to build?
Start with the operating problem, the evidence and the people closest to the work.