Start from the outcome, not the service menu.
Most teams come to us with a goal, not a shopping list. Pick the outcome closest to your situation and we will shape the team, services, and plan around it.
Use case 01
Build an MVP
- The problem
- You need to validate a product idea with real users before the runway runs out — without burning the budget on throwaway code.
- How we approach it
- A senior squad shapes the smallest revenue-ready slice, ships it to production weekly, and instruments it so you learn fast and keep what works.
Outcome
A launchable V1 in weeks, not quarters — built on foundations you can scale.
Where we start
Scope this outcomeUse case 02
Modernise legacy software
- The problem
- A critical platform is slowing the roadmap, expensive to change, and risky to touch — but a big-bang rewrite would bet the company.
- How we approach it
- We modernise in safe slices: characterise the system, carve seams, migrate behind feature flags, and keep the business running through every cutover.
Outcome
Lower operational risk every quarter, with a roadmap that finally moves again.
Where we start
Scope this outcomeUse case 03
Add AI to operations
- The problem
- Promising AI prototypes never reach production because accuracy, governance, and trust are unsolved.
- How we approach it
- We wire retrieval, evaluation, observability, and human review loops into your real data so AI becomes a measured, monitored product capability.
Outcome
AI features your users — and your auditors — can actually trust.
Where we start
Scope this outcomeUse case 04
Reduce cloud cost
- The problem
- Cloud and platform spend is climbing faster than revenue, and nobody is sure which architecture decisions are driving the bill.
- How we approach it
- We rework architecture, delivery pipelines, and FinOps controls so reliability and unit economics move together — not against each other.
Outcome
Predictable spend tied to value, with reliability that improves as cost falls.
Where we start
Scope this outcomeUse case 05
Extend engineering capacity
- The problem
- Your internal team is stretched beyond capacity and hiring senior engineers fast enough is not realistic.
- How we approach it
- We embed senior engineers who lead discovery, write production code, and raise delivery quality from week one — inside your cadence, not beside it.
Outcome
More throughput and a higher bar, without a multi-month hiring cycle.
Where we start
Scope this outcomeWhat changes when delivery gets serious.
Composite outcomes from across our portfolio — anonymised, but representative of the patterns we see repeatedly.
- 6-week release cycles with manual QA gates
- 45% of sprints slip due to unplanned rework
- P95 latency > 1.2s on core transaction path
- Cloud spend growing 40% YoY without proportional traffic
- Daily deployments with automated regression
- 94% on-time milestone delivery, zero rollbacks
- P95 latency < 280ms after architecture rework
- Cloud spend flat while handling 3× traffic growth
- GPT demo impressive in slides, unusable in production
- No evaluation framework — quality measured by anecdote
- Hallucination rate unknown, no guardrails
- Legal and compliance team blocking launch
- RAG pipeline serving 12k queries/day with < 2s latency
- Automated evaluation suite running on every commit
- Hallucination rate < 1.8%, human review loop for edge cases
- Compliance sign-off achieved with audit trail
Not sure which fits?
Tell us the outcome you need next.
A senior engineer will help you frame the problem and the right first step — within one business day, no sales handoff.