Three capabilities, written down properly.
Most services pages list nouns. This one lists what actually happens, what you get at the end, and how long it takes: the two questions every buyer has and almost nobody answers in public.
AI product engineering
Agents, tool-calling, retrieval and evaluation, built as products with real error budgets and cost ceilings, not demos that fall over in week two.
Most AI features fail after the demo because nobody decided what happens when the model is slow, wrong, or expensive. We design those answers first: what the fallback is, what the per-request ceiling is, and how you will know when quality drops. Then we build the thing.
Typical activities
- · Model and provider selection against your actual data
- · Evaluation harness before feature work begins
- · Tool and MCP server design
- · Streaming, queueing and durable execution
- · Cost, latency and failure budgets
What you end up with
- · A feature that survives real traffic
- · Measurable quality you can regression-test
- · A per-request cost you can forecast
Full-stack product build
The whole system: schema, API, interface, billing, deploys and the boring operational work that decides whether a product survives its first hundred users.
A product is not a set of screens. It is a data model, a permissions story, a billing story and a deployment story. The ones that get skipped early are the ones that force a rewrite later, so we build all of it, in the order that keeps options open longest.
Typical activities
- · Data model and tenancy design
- · API and interface implementation
- · Billing, subscriptions and entitlements
- · CI, migrations and environment separation
- · Logging, tracing and error tracking
What you end up with
- · A product in production, not a prototype
- · A codebase your next hire can read
- · Deployment and rollback you can run without us
Embedded engineering
Senior capacity inside a team you already have. We join the standup, review the pull requests, and leave the people who were already there stronger than we found them.
Sometimes the problem is not that you need a product built. It is that the team you have is one senior engineer short of moving properly. We work inside your process rather than beside it, and we optimise for the day we are no longer needed.
Typical activities
- · Architecture and code review
- · Pairing and mentoring
- · Technical hiring support
- · Incremental modernisation of existing systems
What you end up with
- · Throughput that survives our departure
- · Decisions written down, not held in one head
- · A team that levels up rather than one that depends on us
How an engagement is shaped.
Every engagement opens with a shaping sprint. We publish the durations because they are the honest part; the price depends on what the sprint finds.
Shaping sprint
2 weeks
A written spec, a system architecture and a build plan that belongs to you, whether or not you build it with us.
Best for: Founders who know the problem but not yet the shape of the solution.
- · A written specification
- · System architecture and data model
- · A sequenced build plan with estimates
- · The three decisions that will be expensive to reverse
0→1 product build
8–16 weeks
Design and engineering through to a production launch, with weekly demos and your team in the repository throughout.
Best for: Teams taking a shaped idea to a first real release.
- · A product running in production
- · Weekly demos against a live deployment
- · Commit access from day one
- · Runbooks and architecture notes at handover
Embedded engineering
3 months min
Senior engineers working inside your existing team on your board, your codebase and your review process.
Best for: Funded teams who need depth, not headcount.
- · Senior engineering capacity in your team
- · Architecture and code review
- · Mentoring for the engineers you already have