SERVICE 02 — AI INTEGRATION

From demo to production in weeks.

We wire AI models — Anthropic Claude, OpenAI, fine-tuned, on-prem — into the systems your team already uses. With evals, monitoring and guardrails built-in.

Built for the teams who can't wait for results.

This engagement is for operators who already know they have a problem worth solving — and want a senior team to ship the fix in weeks.

  • Teams with a working AI prototype that needs to scale to real users.
  • Operators stuck with vendor 'AI features' that don't actually fit their workflow.
  • CTOs who need a partner who understands eval, observability and the boring 80% of production AI.

Deliverables

  • Production integration in your stack (no vendor lock-in unless you choose it).
  • Eval suite — runnable in CI, so quality regressions block deploys.
  • Observability: latency, cost, quality dashboards.
  • Runbook: failure modes, escalation paths, kill-switches.
  • 30 days of post-launch support included.

A focused engagement.

Six things we ship inside this track. Some clients use a subset; most use all.

01

LLM-powered features

Chat assistants, summarisation, classification, extraction — wired into the product, not bolted on the side.

02

RAG pipelines

Embeddings, vector DBs, retrieval, ranking. Built on your data, scoped to your access model.

03

Agentic workflows

Multi-step agents with tool use — booking, ticketing, data enrichment. With guardrails and human-in-the-loop.

04

Evals & monitoring

Deterministic test suites, regression checks, latency/quality dashboards. So you know when a model drifts.

05

Prompt & cost ops

Prompt versioning, A/B testing, model routing, token budgeting. Most of our clients halve cost in 60 days.

06

Governance & PII

PII redaction, audit logs, role-based access, data-residency. Enterprise-ready by default.

How a typical engagement runs.

Async-first. Senior-only. Weekly demos.

01

Scope

Pick the integration. Lock the eval set. Agree the guardrails. One week of design, one signed scope.

02

Build

2–4 weeks of build. Daily Looms. Friday previews. Eval scores published every Monday.

03

Harden

Load test. Pen test. Fail-mode test. Cost test. Hand-over to your ops team.

04

Operate

Optional: we run the system for 30/60/90 days post-launch and tune as it sees real traffic.

Numbers our clients care about.

3wks
Avg. time to production
71%
Avg. ticket deflection
48%
Avg. cost reduction
99.5%
Uptime target

Pair it with another track.

Most clients combine two or three of these. We'll recommend the right combination on the first call.

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Common questions.

Five things people ask before signing.

Which models do you work with?+

Anthropic Claude (default for production text), OpenAI, Google Gemini, open-source via Together/Replicate. We pick by use-case, not by allegiance.

Will I be locked into a vendor?+

No. Our integration layer abstracts the model. Swap providers without rewriting product code.

How do you handle hallucinations?+

Eval suites, retrieval grounding, structured outputs, human-in-the-loop on risky paths, and confidence routing. We treat hallucinations as engineering, not magic.

Can you work with our existing engineers?+

Yes. About half our integration projects pair with an in-house team. We document everything and hand over cleanly.

How much does it cost?+

Most integrations land between $20k and $80k for the build, plus inference + infra costs. We share a fixed-fee proposal in the first week.

Ready to ship?

Tell us what you're trying to do. We'll send a proposal within two business days.