How is AI Transformation different from AI product development?

AI product development builds a new product around AI. AI Transformation puts AI inside the business you already run - the workflows, documents and decisions your teams handle daily - in 6-12 weeks, measured against the hours it gives back.

Which workflows are good first candidates?

High-volume, rule-informed, document-heavy work: triaging enquiries, drafting responses, extracting data from documents, summarising records, first-pass review. The best first candidate is frequent, boring and measurable.

How do you measure whether it worked?

A baseline before we build (time per task, volume, error rate), an evaluation suite on real cases, and the same numbers after. If the workflow is not measurably better, that is a finding we report, not hide.

Services · AI transformation

Your workflows, with the boring parts removed.

Most businesses do not need an AI product; they need their existing work to take less of everyone’s life. AI Transformation is our 6–12 week engagement that puts ChatGPT, Claude or Gemini inside the workflows you already run - measured, guarded, and priced against the hours it returns.

The shape of an engagement

Workflow audit (week 1). We watch how the work actually happens and pick the first candidate: frequent, boring, measurable. A baseline is recorded - time per task, volume, error rate.
Feasibility spike (week 1-2). A working proof against your real documents and data - not a slide. If the model cannot do the job reliably, you learn it for the price of a week.
Build with guardrails (weeks 2-8). The integration, the job pipeline behind it, schema-constrained outputs, citations where trust needs them, and human checkpoints where stakes demand them.
Evaluation and rollout (final weeks). An eval suite of real cases gates the release; the team adopts it with training and a feedback loop; the baseline is re-measured and reported honestly.

What typically transforms first

Enquiry triage and drafted replies (support, sales, operations inboxes)
Document extraction - invoices, reports, applications into structured data
Summarisation of long records for faster human decisions
First-pass review and classification with human final say
Internal knowledge answers via RAG over your documents

Common questions

How is this different from AI product development?

That service builds a new product around AI. This one puts AI inside the business you already run, measured against hours returned.

Which workflows make good first candidates?

Frequent, boring, measurable: triage, drafting, extraction, summarisation, first-pass review. We help you pick in week one.

How do you measure success?

Baseline before, eval suite during, same numbers after. A workflow that did not measurably improve is a finding we report - see the readiness guide.

Which inbox eats your team’s week?

Name it. We will tell you within 24 hours whether AI genuinely helps - including when it does not.

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