What we do

Services

AI consulting services across strategy, automation, chatbots, machine learning, data engineering and document processing — scoped, built and supported end to end.

Services

AI Services We Deliver

Every Pearl Lemon AI engagement below is delivered by our in-house consultants, engineers and data scientists. Filter by category or search to find the right fit.

Showing 49 services

More AI Services

Pricing

What AI projects cost with us

We publish bands so you can size the work before you speak to anyone. Projects start from £5,000; the exact quote follows a 30-minute scoping call and depends on workflow volume, data readiness and how many systems we integrate with.

Proof of concept

From £5,000

Prove one use case on your real data before you commit to a build.

  • Use-case and data readiness review
  • Working prototype on a slice of your data
  • Accuracy and cost-per-outcome measurement
  • Typically 2–4 weeks

Production build

From £15,000

The system built, integrated and running inside your existing tools.

  • Full build with your CRM, ERP or helpdesk integrated
  • Human-in-the-loop and escalation rules
  • Testing, rollout and team training
  • Typically 6–12 weeks

Ongoing partner

Monthly retainer

Continuous improvement once the first system is live.

  • Model, prompt and workflow tuning
  • New use cases delivered in sprints
  • Monitoring, accuracy reviews and reporting
  • Rolling monthly, quoted on scope

Pearl Lemon AI

Book a scoping call

We map the workflow, the data and the cost, then tell you what AI can realistically automate — and what it cannot.

Your next project decision

Choose an AI service by the outcome you need

Use the service directory to match a real requirement. Strategy establishes priorities; development builds a solution; integration connects it to your stack; analytics supports a decision. These stages can be scoped separately rather than bought as an undefined programme.

  • For manual work, map the workflow and exceptions first.
  • For a customer-facing feature, define the user and permission boundary.
  • For a data problem, establish quality and a baseline before modelling.

If more than one service seems relevant, describe the desired outcome in your enquiry. The scoping call can clarify dependencies and which stage should come first.

Discuss your project