What we build

Bespoke AI solutions.
Six builds, six 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, a product you sell, or proof that the AI you already shipped works. The first five are ordered by commitment; the sixth fixes what is already live. Same builder method behind all six.

Bespoke AI solutions, built in London

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 six forms: a documented AI strategy, an automated workflow, an internal tool your team uses, an AI service your engineers call, a SaaS product you sell, or measured reliability for an AI feature you have already shipped.

Every build applies The Science of AI™ — a four-stage method that scopes and costs the work before you commit. Each one starts with a scoping call with a co-founder, and nothing is committed until the work is scoped and costed. Based in Streatham, London; delivering across the UK. See what we have delivered → · What counts as "bespoke"? →

Where are you now?

Three situations. Six ways in.

You need a starting point. You know AI matters but not what is worth building. Lean AI Strategy gives you a costed decision; the Opportunity Finder gives you a first shortlist in five minutes.

You have a defined need. A workflow to automate, a tool your team needs, a capability for your product, or a product to sell. Go straight to the build — workflow, team tool, AI capability or SaaS product.

You have AI already live. An agent, RAG pipeline or prompt chain in production that you need to trust. AI Reliability measures it.

Service For you if You get First step
Lean AI Strategy You need a costed decision before a build A documented strategy, build briefs, a phased roadmap A four-week strategy engagement See the strategy engagement →
Workflow Automation A repetitive workflow is eating your team's week The workflow automated end to end, with human review where it matters A scoping call with a co-founder See workflow automation →
Tool Build Your team needs a tool no vendor sells An internal tool your staff use every day A scoping call with a co-founder See team tool builds →
Service Build You need an AI capability inside an existing stack An AI service your engineers call — see ExtremeReach A scoping call with a co-founder See AI capability builds →
SaaS Product Build You have expertise and customers who would pay for it as software A product you sell, co-built and yours to own, with a Revenue or Equity Partnership available from the production build onwards A scoping call with a co-founder See SaaS product builds →
AI Reliability An agent, RAG pipeline or prompt chain is already live A reliability specification, an evaluation suite, a baseline and a regression gate A scoping session, then one feature in four weeks See reliability reviews →

If you need to decide first Lean AI Strategy

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.

→ A documented strategy. Build briefs. A phased roadmap.

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
Build · a workflow AI Workflow Automation

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.

→ Senior time recovered. Margin restored.

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
Build · a team tool AI Tool Build

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.

→ A live tool. Your domain knowledge codified. Used daily.

What's included

  • ✓ Workflow analysis + UI/UX design
  • ✓ Prototype + production app
  • ✓ Optional custom AI inside
  • ✓ Rollout + team training
  • ✓ Application Maintenance
Build · an AI capability AI Service Build

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.

→ A working AI service. Live in your stack. Documented.

What's included

  • ✓ Hypothesis stage: scope and plan
  • ✓ Data assessment + candidate models
  • ✓ Production model + service layer + deployment
  • ✓ Clean handover + observability
  • ✓ Model + Application Maintenance
Build · a product AI SaaS Product Build

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 with us and yours to own — or, from the production build onwards, funded through a Revenue or Equity Partnership, so our return depends on the product working, not just delivering.

→ A live SaaS product. Paying customers. Growing MRR.

What's included

  • ✓ Product vision + business model
  • ✓ MVP + production product (multi-tenancy, payments)
  • ✓ Launch + ongoing model evolution
  • ✓ Equity Partnership available
  • ✓ Maintenance + ongoing development
If AI is already live AI Reliability

Make your AI feature
measurable.

For teams who have already shipped AI. We identify what “good” means for your agent, RAG pipeline or prompt chain, decompose it into measurable variables, choose the metrics, and build the tests that tell you whether it actually works.

→ A reliability baseline. A gate that protects it.

What's included

  • ✓ A reliability specification — the variables that define success
  • ✓ A small set of metrics that quantify them
  • ✓ An evaluation suite built around your feature
  • ✓ A quantified reliability baseline
  • ✓ A regression gate in your deployment workflow
How you engage with us

Three partnership models. Applicable to any build.

Any of these builds can be structured under one of three partnership models — Delivery, Revenue, or Equity. The model is decided before the Formulation stage, once the scope is clear.

How partnerships work
Where these builds land

Bespoke AI solutions
by sector.

The six 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.

Common questions

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 six 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, a SaaS product you sell, or measured reliability for an AI feature you have already shipped. 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. Start with AI Reliability if you have already shipped an AI feature and cannot prove how accurate it is. 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 Hypothesis stage, 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 before the Formulation stage, once the Hypothesis and Experiment stages have made the scope clear; Revenue and Equity Partnerships are available from Formulation onwards. There are three: a Delivery Partnership, where you commission and own the build outright; a Revenue Partnership, where you pay less up front and we take a share of the revenue; 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.

Not sure which build fits?

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.