Long term, owning capability in-house is often right. The question is sequencing — and what the first eighteen months actually cost.
Nobody knows your domain like your own people, retained knowledge compounds, and a product that is your competitive core deserves a permanent team eventually. If AI-driven systems will be your business's beating heart for a decade, you should own the capability — we'll say that to your face.
A minimum credible team — a senior AI engineer, a platform engineer, a delivery lead — runs £250K–£400K a year fully loaded in the UK market, assuming you can hire them at all: the best candidates have their pick, and joining a company with no existing AI estate is a hard sell. Add three to six months of recruiting, onboarding and tooling before the first line of production code, and the honest cost of "we'll build it ourselves" is £150K–£300K before anything ships — with delivery risk still ahead of you, and key-person risk forever after.
The sequencing that works: buy the first build, hire into a running system. We deliver the platform fixed-price in weeks, hand over the code and documentation, and train your first hires on a working estate — so your in-house team starts at velocity instead of at a whiteboard. Several of our best clients' engineering teams began exactly this way.
| 1Tech | Hiring in-house | |
|---|---|---|
| Time to first production system | 6–10 weeks | Typically 6–12 months incl. hiring |
| Cost to first system | Fixed quote (builds from £8K) | £150K–£300K salaries/tooling before launch |
| Key-person risk | None — documented handover, code is yours | High until the team reaches 3–4 people |
| Knowledge retention | Transferred at handover + optional support | Excellent, once the team is stable |
| Best for | Getting systems live now; de-risking the hire | Long-run ownership of core capability |
Build first, hire second — and make the hires easier by giving them something real to join. Comparing other routes? See vs the Big-4 and vs offshore agencies.