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AI automation, shipped.

Three engagement types. All of them produce running software, not slide decks. Pick the one that matches where you are.

1. AI product builds

You have an idea — or a problem worth productising — and you want it shipped, not architected. We pick it up at concept and hand it back as a paying product: backend, frontend, mobile if it needs one, billing, observability, and the LLM glue that makes it real.

Typical engagement: 6–12 weeks from kickoff to a customer paying. We start with a single, deliberately narrow first slice and ship it in week two. Each subsequent week adds one feature that earns its keep.

  • What you get: a live product, source code, deployed infrastructure, and runbooks.
  • What we own: design, engineering, AI prompt and eval work, deployment.
  • What you own: product strategy, customer conversations, the brand voice.

2. Automation retrofits

You already have a SaaS or internal tool. Somewhere in the workflow is a person doing repetitive language work — triaging, drafting, summarising, classifying, extracting. That’s where AI earns its rent. We bolt it in without rewriting the world.

Typical engagement: 2–6 weeks. We map the workflow, identify the highest-ROI insertion point, build the AI feature behind a feature flag, run an eval against your real data, and roll it out gradually.

  • Common retrofits: support deflection, lead enrichment, contract clause extraction, content classification, smart drafts.
  • How we measure: success rate against your historical data, time saved per ticket/lead/case, model cost per successful action.

3. AI infrastructure

The reason most AI features collapse isn’t the model — it’s the plumbing. We build the unsexy layer that decides whether your AI feature still works at 3am: LLM gateways, prompt versioning, evals, queue workers, billing meters, observability, and structured fallbacks.

Typical engagement: 3–8 weeks, often delivered as a building block your team owns afterwards.

  • LLM gateway: route across providers, fail over, cap spend, log everything.
  • Evals & prompt CI: regressions caught before they hit users.
  • Billing & metering: usage-based pricing wired to Stripe without invoking finance.
  • Observability: traces, tokens, latencies, costs — per feature, per tenant, per model.

How we work

Async-first. Daily written updates, weekly demo, one live call a week if you want it. We commit to specific outcomes per sprint and we tell you when something isn’t working before you have to ask.

We pick a small number of client engagements each quarter so the work we take on actually gets the attention it deserves. If we’re a fit, the first sprint usually starts within a week of first contact.