Four phases.
Zero hype.

Our 4-phase methodology to ship AI

We work with an auditable, predictable, production-first method. No endless "discovery phases". A deliverable every week. Every decision backed by data.

04 phases
4–12 weeks to production
Weekly deliverables
[ Principles ]
/ 01

Production first

We start from the end-state: what should happen in your system when a real user interacts with the solution. Then we work backwards.

/ 02

Measured ROI

Every use case enters with a quantified hypothesis. If we can't measure the impact, we don't build it.

/ 03

Radical transparency

Shared repo, logged decisions, recorded standups, live metrics. Zero black box.

/ 04

Your team, not ours

We co-build so your team can operate, maintain and iterate without us. We train them on every release.

[ The 4 phases ]

From idea to production
in four moves.

We don't sell endless workshops or canned demos. Each phase has a fixed duration, concrete deliverables and exit criteria before moving to the next.

Week 01 — 02 01

Discovery & priority

We map your processes, identify candidate use cases and rank them by impact vs. effort. You walk away with an actionable roadmap, not a PowerPoint deck.

Deliverables

  • Process map with bottleneck analysis
  • Prioritised list of 5–10 use cases with estimated ROI
  • Audit of available data and gaps to fill
  • Rollout plan for the top 2 use cases
2 wk/ duration
Week 03 — 04 02

Working prototype

We build a working version of the priority use case on your real data. No mockups — code that works, integrated with your sandbox systems.

Deliverables

  • End-to-end prototype connected to real sources
  • Baseline metrics vs. post-AI projection
  • Technical documentation and proposed infrastructure
  • Quantitative go/no-go decision
2 wk/ duration
Week 05 — 08 03

Production pilot

Controlled rollout to 10–20% of real traffic, with continuous monitoring, feature flags and a kill switch. We adjust with feedback from real users, not from meeting rooms.

Deliverables

  • Blue-green deployment with operational kill switch
  • Live KPI dashboard
  • Documented and tested rollback plan
  • Weekly iteration with your team + scaling criteria
4 wk/ duration
Week 09 — ∞ 04

Scale & handover

100% rollout, team training, runbook and a monthly iteration plan. We stay as your technical partner, not as a dependency.

Deliverables

  • 100% rollout, SLA and 24/7 monitoring
  • Operational runbook + handover documentation
  • Technical training for your team (4 sessions)
  • 6-month continuous-improvement roadmap
/ ongoing
[ The team ]

Four roles. One goal.

Every project has a dedicated team of four roles. No "managers of managers", no rotating resources. Whoever starts, finishes.

Strategy lead

Project owner. Measures ROI, aligns with stakeholders and blocks any scope creep that doesn't add measurable value.

/ Focus · business

ML/AI engineer

Designs models, prompts, RAG pipelines and evaluators. Decides which model, which architecture and which guardrails.

/ Focus · models

Data engineer

Builds the pipelines, integrates with your systems and owns data quality, governance and production monitoring.

/ Focus · pipelines

Product / UX

Makes sure the solution gets used. Designs the interaction, the screens, fallback flows and end-user training.

/ Focus · user
[ How we work ]

Three decisions that make the difference.

/ 01 · Cadence

Weekly sprints

Friday demo with live metrics. If something isn't working, we know in 7 days, not 7 months. Your team has continuous visibility.

/ 02 · Decisions

RFC + data

Every meaningful technical decision goes into a short RFC with alternatives, trade-offs and metrics. Versioned, auditable, reviewable.

/ 03 · Communication

Shared Slack + Notion

A joint workspace, not ghost emails. Your team reads and writes in the same place where the product is being built.

Ready to
get started?

Book 30 minutes. We walk away with a concrete map of how to apply our process to your business, with timelines and deliverables.