Bespoke AI solutions.
Five builds, five outcomes.
Pick what you want to walk away with — a strategy your team trusts, hours back in your team's week, a tool your team uses, a capability your engineers call, or a product you sell. Ordered by commitment; same builder method behind all five.
Ferrous Labs is a London AI engineering studio. We build and run bespoke AI solutions for UK businesses — systems designed around one organisation's own processes, data and constraints rather than bought off the shelf and configured to fit. They take one of five forms: a documented AI strategy, an automated workflow, an internal tool your team uses, an AI service your engineers call, or a SaaS product you sell.
Every build applies The Science of AI™ — a four-stage method that scopes and costs the work before you commit. Each one starts with the same Architecture R&D Sprint, and you can stop at that boundary. Based in Streatham, London; delivering across the UK. See what we have delivered → · What counts as "bespoke"? →
Get the strategy your
whole team trusts.
When you need clarity before commitment. A documented AI strategy with prioritised opportunities, build briefs ready to commission, and a phased roadmap. Your team aligns on what to build first.
What's included
- ✓ Opportunity Finder — pattern-matched against our library
- ✓ Facilitated workshop with your team
- ✓ Written strategy with prioritised builds
- ✓ Build briefs for the top 1–2 opportunities
- ✓ Optional Strategy Advisor retainer
Hours back in your
team's week, in 8 weeks.
Repeat work running on autopilot. Agent-driven automation handles invoice processing, document triage, supplier coordination, status chasing, report generation. The work that follows clear rules and eats senior time.
What's included
- ✓ Workflow mapping + automation scoping
- ✓ Agent flows built (n8n, Make, agent frameworks)
- ✓ Integration with your existing systems
- ✓ Team training + supervisor handover
- ✓ Application Maintenance
Put an AI-powered tool
in your team's hands.
A standalone application your operational team uses every day. Built around how the team actually works. Integrated with your existing systems. Used, not shelved.
What's included
- ✓ Workflow analysis + UI/UX design
- ✓ Prototype + production app
- ✓ Optional custom AI inside
- ✓ Rollout + team training
- ✓ Application Maintenance
Get the AI capability
your engineers can call.
A production AI service in your stack, accessed via MCP server or API. Your engineers integrate it the way they integrate any other service. Production-grade, observable, cost-engineered.
What's included
- ✓ Architecture R&D Sprint
- ✓ Data assessment + candidate models
- ✓ Production model + service layer + deployment
- ✓ Clean handover + observability
- ✓ Model + Application Maintenance
Turn what you do
into a product you sell.
A recurring-revenue SaaS product, built on your expertise and your data, sold to your existing customers or to new ones. Co-built and (typically) co-owned with us — our return depends on the product working, not just delivering.
What's included
- ✓ Product vision + business model
- ✓ MVP + production product (multi-tenancy, payments)
- ✓ Launch + ongoing model evolution
- ✓ Equity Partnership available
- ✓ Maintenance + Dev Sprints
Three partnership models. Applicable to any build.
Any of these builds can be structured under one of three partnership models — Delivery, IP, or Equity. The model is decided at the end of the R&D Sprint, when scope is clear.
How partnerships workBespoke AI solutions
by sector.
The five builds stay the same; what changes is the problem they are pointed at. If your sector is below, we have delivered into it before.
Specialist technical firms
Accountants, lawyers, surveyors and engineers — bespoke AI that cuts review and drafting time. Usually a Tool Build or Workflow Automation.
Document-heavy operations
Intelligent document processing, extraction and triage at volume. Usually Workflow Automation or a Service Build.
Industrial & engineering
Predictive maintenance, anomaly detection, sensor and signal AI. Almost always a Service Build.
Client-service businesses
Agencies and service firms where margin lives in delivery hours. Usually Workflow Automation, or a SaaS Product Build — see how consultancies build recurring revenue.
Data & forecasting
Demand forecasting and decision support built on your own history. Usually a Service Build or Tool Build.
Not listed?
The method does not change with the sector. Take the free Opportunity Finder and we will tell you honestly whether we are the right team for your problem.
Choosing a bespoke AI build:
questions answered.
Who builds bespoke AI solutions in London?
Ferrous Labs is a London-based AI engineering studio that builds and runs bespoke AI solutions for UK businesses, working from 1 Empire Mews, Streatham, London SW16 2BF and delivering nationwide. A bespoke AI solution here takes one of five forms: a documented AI strategy, an automated workflow, an internal tool your team uses, an AI service your engineers call via API or MCP server, or a SaaS product you sell. Every build follows The Science of AI™, a four-stage delivery method that scopes and costs the work before you commit. For the difference between configured software and a genuinely custom build, see what counts as bespoke →
Which AI build should we start with?
It depends on what you want to walk away with. Start with Lean AI Strategy if you need clarity before commitment. Start with AI Workflow Automation if your team is losing hours to repetitive work. Start with an AI Tool Build if a specific team needs something to use daily. Start with an AI Service Build if your engineers need a capability you cannot hire for. Start with a SaaS Product Build if you want to turn existing expertise into a product you sell. The free Opportunity Finder produces a personalised shortlist in about five minutes.
How much does a bespoke AI solution cost in the UK?
Lean AI Strategy starts from £8,000 and runs for four weeks. Build engagements are scoped and priced after the Architecture R&D Sprint, which is the first stage of every build — this means you see a costed plan before committing to a full build, and you can stop at that boundary. Cost is engineered deliberately rather than accepted: for ExtremeReach, Ferrous Labs delivered vector retrieval at roughly 10× cheaper than the off-the-shelf alternative. More on what AI tools actually cost →
Who owns the AI system you build for us?
That is set by the partnership model, which is chosen at the end of the R&D Sprint once scope is clear. There are three: a Delivery Partnership, where you commission and own the build outright; an IP Partnership, where ownership and upside are shared; and an Equity Partnership, where Ferrous Labs takes equity in the resulting product. The model is decided when the work is understood, not before — see how partnerships work.
What happens after the AI system goes live?
Maintenance is part of the model, not an upsell. Every build ends in Execution — a live system with monitoring and a documented hand-off — and Model + Application Maintenance keeps it running: model retraining as your data changes, infrastructure tuning, and iterative improvement. Ferrous Labs treats a build as a live system it stays accountable for, not an artefact handed over and abandoned.
Take the Opportunity Finder.
Get clarity in 5 minutes.
Talk it through with Catalyst, our AI guide — or type. Personalised AI build shortlist. Free, no commitment.