Custom AI software
your team actually uses.
A standalone application shaped around how your operational team works: an internal copilot, a decision-support dashboard, an intelligent workflow tool or a client-facing portal. Prototyped with your team, live in eight to twelve weeks, and maintained as their needs change.
Designed with your team · Built on your data · Maintained after launch
Expertise that lives in people’s heads.
- Questions only one or two seniors can answer
- The same judgement made over and over, by hand
- Years of case data nobody can search
A tool designed with the people who’ll use it.
- Their workflow mapped in the Hypothesis stage
- A prototype piloted with a small group, on real work
- Rebuilt from what the pilot taught us, integrated with your systems
- Your know-how built in as guidance, checks and examples
Software your team opens every day.
- Answers in the tool, with the source cited
- New starters working to the senior standard sooner
- Trained during rollout, not after
- Application Maintenance as the work changes
Everything you need to put your expertise in everyone’s hands.
Built around how your team really works.
We sit with the people who do the work, map their decisions and the data behind them, and design the tool around that, not around a generic template.
- role
- senior analyst
- the decision
- approve, amend or escalate a case
- what they reach for
- the case file, a precedent, the policy
- where the time goes
- finding the precedent — 25 minutes a case
A prototype your team tries first.
A minimum viable tool goes to a pilot group on real workflows, so their feedback shapes the product before production scope is locked.
- users
- 6, from the team that will live in it
- sessions
- 214 on real cases
- feedback
- 37 items, three of them scope changes
- decision
- scope agreed with the team, then production
Your domain knowledge, codified.
What lives in five people’s heads becomes guidance, checks and examples inside the tool, so newer team members work to the same standard.
A production app in your stack.
The tool is rebuilt from what the pilot taught us and integrated with your existing systems, with custom AI inside where it earns its place.
Rolled out, then kept current.
Your team is trained during rollout, not after. Application Maintenance keeps the tool fresh and adds features as the work changes.
- features shipped
- 4, from the team’s own requests
- requests open
- 6
- sources refreshed
- monthly, outdated documents flagged
- adoption
- 41 of 45 people, weekly
Stop relying on memory.
Start relying on the tool.
Your expertise is the asset, but it sits in people’s heads. The same kind of work comes round again and again, years of data go unused, and every new starter takes months to reach the standard of the people who trained them.
See how bespoke AI is changing the way UK professional services businesses work →
- Know-how held by a few senior people
- The same questions answered by hand, over and over
- Years of case data nobody can search
- New starters taking months to get up to speed
- Off-the-shelf software the team works around
- Know-how built into a tool everyone uses
- Routine questions answered in the tool, with sources
- Your own data searchable and put to work
- New starters working to the same standard sooner
- Software shaped to how your team actually works
The Science of AI Specialisation™
From workflow analysis to a tool your team uses daily, in four clear stages. The same method runs through every Ferrous Labs build.
workflow analysis → UI/UX vision → build brief
HypothesisAnalyse the workflow
Workflow analysis, UI/UX vision and scope. The output is a build brief and a design direction your team can sanity-check.
ExperimentBuild the prototype
A minimum viable tool, piloted with your operational team. Real workflows, real users and real feedback before production scope locks.
integrated with the systems your team already runs
FormulationProduction app
Reconfigured from the prototype data and integrated with your existing systems, with optional custom AI inside. Ready for organisation-wide rollout.
weekly active users · trained during rollout
ExecutionRoll out + maintain
Your team is trained during rollout, not after. Application Maintenance keeps the tool fresh and adds features as your team’s needs evolve.
How the build runs
Scoping call first · 8–12 weeks · Maintained after launch
Scoping call
A co-founder learns how your team works, and whether a tool is the right answer.
Hypothesis → Experiment → Formulation → Execution
Analyse the work, pilot a minimum viable tool with your team, then build the production app.
Rollout + maintenance
Your team trained during rollout; Application Maintenance adds features as needs change.
What you walk away with
A tool your team uses every day, with your expertise built in, and a partner who keeps improving it.
Custom AI software development:
questions answered.
What is custom AI software development?
Custom AI software development is the design and build of an AI-powered application around one organisation's own processes, data and domain language, rather than configuring an off-the-shelf product. The output is a working tool your team opens and uses — typically an internal copilot, a decision-support dashboard, an intelligent workflow interface, or a client-facing portal. It differs from buying an AI product in that the interface, the model behaviour and the integrations are all shaped by how your team already works.
What is an AI Tool Build?
An AI Tool Build is a standalone application your operational team uses every day. Common examples include internal copilots that answer questions using your company knowledge, decision-support dashboards that surface AI-generated recommendations, client-facing portals, and intelligent workflow interfaces. Every tool is built around how your team actually works, not a generic AI template.
How long does it take to build a custom AI tool?
A typical AI tool build takes eight to twelve weeks from kickoff to a working tool in your team's hands. Timeline depends on integration complexity and data requirements rather than feature scope — we scope tightly to what your team actually needs rather than building for hypothetical future requirements.
What is the difference between an AI Tool Build and AI Workflow Automation?
An AI Tool Build produces an interface your team interacts with actively — a copilot they query, a dashboard they use to make decisions, or a portal clients access. AI Workflow Automation runs in the background without requiring active interaction, handling process steps end to end with minimal human involvement. Both can be complementary: a tool build might feed outputs into an automated workflow.
Do we own the custom AI software you build?
Under a Delivery Partnership you commission and own the build outright, including the source code. Two other models are available — 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 chosen before the Formulation stage, once the Hypothesis and Experiment stages have made the scope clear, rather than agreed before anyone understands the work; Revenue and Equity Partnerships are available from Formulation onwards. — see how partnerships work.
Which company builds custom AI software in the UK?
Ferrous Labs is a London-based AI engineering studio that builds custom AI software for UK businesses — internal copilots, decision-support dashboards, intelligent workflow tools and client-facing portals, each scoped, built and maintained end to end. Using The Science of AI Specialisation™, a typical tool goes live in 8 to 12 weeks and integrates with the systems your team already uses. Ferrous Labs works with UK specialist technical firms, client-service businesses and document-heavy operations across London and nationwide — see delivery case studies →