Foundry

What changes

Less waiting. Less re-keying. Less cloud AI exposure.

Foundry savings are clearest when a business already has repeatable AI-shaped work and a reason not to send it to a third-party AI provider.

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Three savings pillars.

Time

Staff stop doing the first read by hand. The human still checks the work, but they start from a prepared first pass.

Evidence examples
  • Document review time reduced to 20–30 seconds per document in the source workflow.
  • Support routine response time reduced to 12–15 minutes in the source workflow.
  • Internal knowledge answers begin in 30 seconds–3 minutes in the source workflow.

Money

Suitable workloads stop paying per cloud AI call once configured processing is moved local.

Evidence examples
  • Document-processing example avoided £21,600/year in OpenAI API costs.
  • Support example avoided £5,400/year in Intercom AI/OpenAI-style costs.
  • Knowledge-search example avoided £7,200–10,800/year in cloud AI usage.
  • Code-review example avoided £9,600–14,400/year in OpenAI API costs.

Risk

The value is also being able to use AI on work otherwise blocked by confidentiality, client contracts, professional obligations, or procurement concerns.

Risk reductions
  • Less third-party AI exposure for client or business-sensitive data.
  • Clearer audit trail for configured workflows.
  • Fewer manual re-keying errors where extraction is checked by humans.
  • Better visibility into what the system is doing.

Example workflow outcomes from the source cases.

WorkflowBeforeAfterCommercial meaning
Document processing8–13 minutes per document20–30 seconds reviewAdmin time moves from reading/re-keying to checking exceptions
Conveyancing intake15–20 admin hours/week chasing documents4–6 hours/weekFee earners see what is missing earlier
Client support4–6 hour routine response12–15 minutesRoutine tickets stop blocking urgent cases
Internal knowledge25–45 minutes searching30 seconds–3 minutesStaff find firm knowledge faster and with citations
Code review3–5 hour PR wait15–25 minutesSenior engineers review a prepared first pass

Use as illustrative case-study evidence, not as guaranteed results.

The economics depend on volume.

Foundry makes the strongest case when you have enough repeatable work to justify hardware, setup, and support. A low-volume business may be better off staying manual or using a standard cloud tool.

The Fit Review compares your current staff time, cloud AI spend, confidentiality requirements, and hardware position before recommending a path.

Good fit signals.

  • You process many similar documents, tickets, queries, matters, or PRs.
  • The data is sensitive enough that cloud AI creates a real concern.
  • You are already paying meaningful AI API or AI-tool bills.
  • The workflow can tolerate seconds, not milliseconds.
  • You want drafts and review queues, not unsupervised automation.
  • You can accommodate Apple Silicon hardware on-site.

We will say no when the numbers do not work.

  • Your volume is low and manual handling is already manageable.
  • You are happy sending the data to cloud AI providers.
  • You need massive concurrency or sub-second public-user responses.
  • You want image/video generation rather than document, text, support, knowledge, or code workflows.
  • You want AI to make final legal, financial, HR, medical, or operational decisions without human review.

Book a Foundry Fit Review

A useful no is better than an expensive AI project.