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Prototype to production
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Claude workflow implementation — from prototype to production

We build the prioritized workflows against your own systems, with guardrails, evaluation and escalation defined before anything goes live — then hand them over with the runbook.

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Target audience

For organizations that already know what to build

You have a prioritized workflow — from your own analysis or from a discovery engagement — and you need it running in production rather than demoed in a sandbox.

Who owns this engagement

  • CTO / Head of Engineering — accountable for what ships and what it touches.
  • COO / operations leadership — owns the workflow being changed.
  • Platform and integration teams — own the systems it has to connect to.
  • Risk, security and compliance — own the guardrails it runs inside.

What we need from you

  • A named workflow owner who can make decisions
  • Access to the systems it reads from and writes to
  • An agreed definition of an acceptable result
  • A security position on data handling

Delivery modes

The business problem

The demo worked. The rollout did not.

Most AI pilots fail somewhere between a convincing prototype and a system the business will depend on — not because the model is incapable, but because nobody defined what happens on the bad path.

Where pilots die

  • No agreed definition of a correct output
  • No evaluation, so quality drift is invisible
  • No escalation path when the model is unsure
  • Integrations stubbed in the demo, real in production
  • Nobody named to operate it afterwards

What production actually requires

  • An evaluation set built from real cases
  • Guardrails and an explicit human escalation line
  • Logging of every decision the workflow makes
  • Real integrations, with failure handling
  • A runbook and a team trained to use it

What we build

Workflow types we take to production

Scoped as workflows rather than as products — a bounded task with an owner, an input, an output and a definition of done.

Workflow patterns

Bounded, measurable, owned

  • Document processing
  • Triage and routing
  • Retrieval over internal knowledge
  • Drafting with human approval
  • Extraction and structuring
  • Multi-step agents with guardrails

A workflow running against real inputs, with measured quality.

Engineering foundations

What makes it supportable

  • Evaluation harness
  • Observability and logging
  • Escalation and fallback paths
  • System integrations
  • Access and data handling
  • Runbook and handover

Something your own team can operate, debug and extend.

Process

How implementation runs

Four to twelve-plus weeks depending on integration surface. Capability transfer is a goal from day one, not a phase at the end.

  1. 01

    Scope and success criteria

    What a correct result is, agreed in writing.

  2. 02

    Prototype

    Built small, against real inputs.

  3. 03

    Evaluation

    Measured on cases you recognise, not benchmarks.

  4. 04

    Hardening

    Guardrails, escalation, logging, integrations.

  5. 05

    Production rollout

    Live, monitored, with a rollback position.

  6. 06

    Handover

    Runbook, docs and your team trained to operate it.

Expected outcomes

What is running, and who owns it

Delivered

  • The workflow live against real inputs
  • An evaluation set you can re-run
  • Guardrails and escalation rules you approved
  • Observability into every decision made
  • Code, docs and runbook handed over

Ownership

  • Work built under a delivery engagement is handed over to you
  • Your team is trained on the runbook before we step back
  • Ongoing support is optional, not structural

Related

Before you ask

Implementation, answered plainly

Can you start here, without the discovery work?

Yes, if you already have a workflow chosen and an owner who can define what a correct result looks like. The scoping stage will test that definition fairly hard, because everything downstream — evaluation, guardrails, rollout — depends on it.

What does the workflow do when it is not confident?

Whatever you decide it should, agreed before anything goes live. In practice that usually means escalating to a person with the context attached, rather than guessing. Where that line sits is your decision, not ours, and it is written down.

How long does it take?

Four to twelve-plus weeks, driven mostly by integration surface rather than by the model work. A workflow touching one system with clean access moves quickly; one that needs four internal systems and a security review does not.

Who owns the code?

Work we build for you under a delivery engagement is handed over with the code, the docs and a runbook. Our own products — Restro20, Cafe20 and ReEngage20 — are licensed platforms and separate from this.

Do you stay involved afterwards?

Only if you want us to. The handover is designed so your team can operate the workflow without us; ongoing optimization is a separate, optional engagement.

Start here

Start a Claude Adoption Assessment

Tell us the workflow you want built and the systems it touches. We come back with a scope, the open questions, and an honest view of the integration effort.

Talk to an AI Expert

hello@focus20labs.com