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Four ways we put AI to work.

Pick one, or combine them. Every engagement ends with something running in production — and the evidence that it is safe to rely on.

01

AI agents & automation

Agents that read, decide and act across your email, documents and internal systems — with guardrails, audit trails and human approval where it matters.

What you get

  • Working agent on your real data
  • Evaluation suite with pass/fail criteria
  • Permissions, limits and audit log
  • Runbook and owner training

Typical scenarios

  • Inbound order processing
  • Supplier and customer email triage
  • Invoice matching and exception handling
  • Internal helpdesk for policies and procedures
See how it works
02

Vision & robotics validation

Inspection models for quality control, and independent testing for robots and warehouse automation — simulation before deployment, acceptance checks before go-live.

What you get

  • Test plan agreed with you and the vendor
  • Simulation results and failure log
  • Safety and acceptance checklist, completed
  • Written findings and sign-off pack

Typical scenarios

  • Goods-to-person and grid storage systems
  • Autonomous mobile robots (AMRs) in mixed traffic
  • Visual quality inspection on a production line
  • Pre-purchase comparison of vendor claims
See how it works
03

Data & ML engineering

Clean pipelines, evaluation harnesses and models you can monitor — the foundation that decides whether AI keeps working after launch.

What you get

  • Documented pipelines and data contracts
  • Benchmark and eval set you own
  • Monitoring dashboards and alerts
  • Handover and team training

Typical scenarios

  • Demand and inventory forecasting
  • Classification and extraction models
  • Retrieval over internal documents
  • Cost and quality tracking for LLM features
See how it works
04

AI strategy & governance

Find the use cases worth doing, size the risk honestly, and set up the policies, controls and reviews your regulators and your board will ask about.

What you get

  • Ranked use-case shortlist
  • Risk register with controls
  • Policy templates ready to adopt
  • Roadmap and funding case

Typical scenarios

  • Board-level AI roadmap
  • Vendor and tool selection
  • Pre-deployment risk assessment
  • Staff guidance and acceptable-use policy
See how it works
Engagement

Start small. Scale what works.

Scoped, fixed-outcome engagements. No open-ended retainers unless you want one.

Explore

AI Readiness Sprint

2 weeks · fixed scope

Find the use cases worth pursuing and know exactly what it takes.

Talk to us
Most chosenBuild

Pilot to Production

4–8 weeks · milestone-based

One workflow, taken from prototype to a monitored production system.

Start a pilot
Assure

Independent Validation

3–6 weeks · per system

A second opinion on an AI or robotic system before — or after — it goes live.

Request a review

Let’s make AI work for you

Tell us about the workflow you’d like to improve. We’ll reply within one business day.

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