Nobody can say where it fits
Leadership sees the potential but cannot name the workflows that would move the numbers. Budget gets spread across tools nobody adopts.
Our fix
A review that ranks use cases by return, not novelty.
AI consulting and engineering · UK and US
Make your businessAI-native.
We find the work worth handing to AI, train your team to run it, and build the agents that do it. For businesses of 10 to 250 people.
- 10 to 250
- the company size we work with
- 2 to 3 wks
- from kickoff to a ranked roadmap
- 100%
- of code, prompts and docs are yours
The readiness gap
The problem is rarely the technology.
Ambition is not the bottleneck. Execution is. Four things stop AI leaving the pilot stage. We fix all four.
- 35%
- of UK businesses with 10 or more staff now use AI, up from 12% in late 2023
- 1.6
- AI technologies used per adopting business, barely up from 1.4 in 2023
- 11%
- have trained more than half their workforce on AI
Source: Office for National Statistics, Artificial intelligence in UK businesses: 2023 to 2026, published 20 July 2026. Figures cover UK businesses with 10 or more employees.
PilotProduction
The team is not fluent
The people closest to the repetitive work are the least equipped to spot what AI could take off their plate. Skills stall adoption faster than budget.
Our fix
Role-based training that turns your staff into the people finding use cases.
No one in-house to build it
Off-the-shelf tools stop at the edge of your process. Anything valuable has to be built against your systems, and there is no AI engineer on the payroll.
Our fix
We build and integrate it, against the stack you actually have.
Pilots never reach production
A demo that works once is not a system. Without evaluation, monitoring and ownership it quietly degrades, and confidence goes with it.
Our fix
Production standards from day one, and we can run it long term.
What we do
Diagnose. Train. Build. Run.
One engagement, four stages. Most clients start at the review and stay through build. You can enter at any stage and stop at any stage.
Typical first valueWeek 3
01Weeks 1 to 3
AI Operating Review
We map how work really moves through your business, then rank every use case by what it is worth.
- Workflow mapping
- Use-case ranking
- ROI model
- Board-ready roadmap
OutputA costed roadmap
02Ongoing
Team Training
We show individuals how to use LLMs and AI tools to do their actual work faster, then train them on the agents we build together.
- Individual LLM fluency
- Role-based sessions
- Internal champions
- Playbooks
OutputTeams who can specify
03Weeks 4+
Custom Agents
Agents that qualify, research, draft, route and act inside your CRM, inbox and docs.
- Agent design
- Integrations
- Voice agents
- Evaluations
OutputWork leaving your queue
04Continuous
Run and Scale
Live systems need an owner. We host, monitor and improve them, or hand the lot over.
- Monitoring
- Model upgrades
- Security
- New workflows
OutputSystems that stay working
Engagement model
Embedded AI Lead
A senior AI lead inside your business one to two days a week, owning the roadmap, running the vendors and keeping delivery honest. The function without the six figure hire.
Capabilities
What we actually build.
Not chatbots bolted onto a website. Systems that read, decide and act inside the tools you already run on.
Work in, decision out, action taken
An enquiry, invoice, CV or ticket arrives. The agent enriches it, applies your rules, then writes back into the system of record. Humans stay in the loop exactly where you want them.
Agents that pick up the phone
Inbound answered and qualified around the clock. Outbound follow-up that never forgets.
Inside your stack
CRM, inbox, docs, ERP, telephony. We build against what you already pay for.
Proof before production
Every agent scored against a real test set before it touches a customer.
Your documents, searchable
Contracts, SOPs and history turned into a retrieval layer agents can cite.
Live systems, watched
Quality, cost and latency tracked per workflow. Drift and failures surface to us before they surface to your customers, and model upgrades ship without drama.
AI fluency programme
The agents are half of it. Your people are the other half.
Skills, not software, is the number one blocker to AI in mid-sized businesses. We work alongside your teams to show individuals how to use LLMs and AI tools to boost their own output, not just how to operate the agents we build. That fluency is what makes adoption stick.
- 01
Leadership
Half-day session for the people signing off budget and risk.
- What AI can and cannot do in your sector
- Reading an AI business case
- Risk, data and governance in plain English
- 02
Managers
The people who own processes learn to spot and specify the work.
- Mapping your own team's week
- Writing a usable automation brief
- Deciding what stays human
- 03
Frontline teams
Hands on keyboards, working on their own real tasks with the LLMs and AI tools they already have access to.
- Using ChatGPT, Claude and Copilot for real daily work
- Prompt patterns and workflows that hold up
- Spotting tasks to hand off before an agent even exists
- Where to escalate and when not to trust it
Embedded
Internal champions
We coach two or three people inside the business properly, so someone owns AI when we are not in the room. They join build sessions, review agent behaviour with us and run the internal show-and-tell.
Individuals
LLM fluency for daily output
Most teams already have access to powerful AI and barely use it. We sit with individuals in their actual roles, show them how to get real work done faster with LLMs, and build habits that raise output long before any agent is deployed.
Afterwards
Playbooks that outlive us
Every session leaves written guidance for the role it covered: what to use, what to avoid, worked examples from your own workflows and the escalation path. Good enough to onboard a new starter six months later.
“
If the goal is cutting headcount, we are the wrong firm. The businesses that win with AI give the same people more capacity, not fewer colleagues.
How we work
Understand. Enable. Build. Operate.
Small senior teams, no layers of account management, and one rule: nothing ships that your team cannot own, question or switch off.
Step 01
Understand
We sit with the people doing the work and map exactly where time, margin and quality leak out.
Step 02
Enable
Your teams get fluent first, so new use cases keep surfacing long after the review work ends.
Step 03
Build
We ship the highest-return workflow first, integrated and evaluated, then work down the roadmap.
Step 04
Operate
Monitoring, upgrades and new workflows for as long as it is useful. No lock-in, handover on request.
Selected work
Systems in production, not slideware.
A sample of what we have built for mid-sized teams in the UK and US. Business outcomes, not hours saved.
B2B services
Outbound research and qualification agent
Manual prospect research replaced by an agent that builds account briefs, scores fit against the ideal customer profile and drafts the first outreach for a human to send. Built straight onto the existing CRM.
OutcomeMultiple new contracts signed since launch.
- 01 Inbound enquiry received CRM
- 02 Company enriched, 14 signals resolved
- 03 Fit scored against ICP 0.82
- 04 Brief written to record CRM
- 05 Draft outreach queued for human review
QA and release agent
Automated regression triage and release notes inside an existing engineering workflow.
OutcomeMore features shipped per sprint, same team size.
Candidate ranking
Structured screening and shortlisting against role criteria, with reasoning a human can audit.
OutcomeRoles filled weeks faster, better-matched shortlists.
Voice agents on the front line
Inbound calls answered, qualified and routed around the clock, with transcripts written back into the CRM.
OutcomeNo missed enquiries outside office hours.
brep ran AI training across our executive and C-suite teams and the shift was immediate. People left the room spotting use cases in their own workflows instead of asking what AI might one day do for us. It changed how we think about operating the group.
Before you book
A good fit for some businesses, a bad one for others.
Worth thirty seconds now rather than thirty minutes on a call.
✓ Book the call if
You run a business between 10 and 250 people with real revenue.
You know AI should be doing something here and want it ranked properly.
You have someone internal who can own it for an hour a week.
You would rather build capability in your team than rent a tool forever.
✕ Skip it if
You want the lowest bid rather than a roadmap you can act on.
You want a prototype for a pitch deck rather than a working system.
The goal is cutting headcount.
Nobody internally has capacity to be involved at all.
How we are set up
A practice built around four disciplines, not one generalist.
brep runs as a senior practice: strategy, enablement, engineering and operations, each with its own standards and its own owner. UK based, working with clients across the UK and US, with specialists brought in where an engagement needs them.
Strategy practice
Operating reviews, opportunity ranking and business cases. Where AI pays, and in what order.
Enablement practice
Leadership, manager and frontline tracks, champion programmes and the playbooks that outlast us.
Engineering practice
Agents, integrations and evaluation harnesses built to production standards inside your stack.
Operations practice
Monitoring, model updates and workflow changes once systems are live and carrying real work.
Who leads the work
Mike Bank
Founder · Strategy and enablement
Mike leads strategy and enablement. He works with leadership teams to turn a vague sense that AI matters into a ranked plan with numbers attached, then stays close to delivery so the roadmap and the build never drift apart.
Steve Franco
Founder · Engineering and operations
Steve leads engineering and operations. He sets the standard every build is held to: integrated properly, evaluated before launch, observable once live, and maintained long after the first release.
Senior only
No junior bench, no handover after the sale
UK and US
Based in the UK, working with SMEs on both sides of the Atlantic
Partner network
Specialists added per engagement, held to our standards
Questions
The things people ask first.
If yours is not here, email info@brep.ai and you will get a straight answer.
No. We only work with teams of 10 to 250. Enterprise consultancies price for organisations with an in-house data team. We work with businesses where the ops director is also the AI sponsor.
An AI Operating Review. Two to three weeks, then a ranked list of use cases with cost, effort and return against each one. The roadmap is yours whether you build with us or not.
We train them before we automate anything around them. People map their own week and choose what to hand over. Adoption fails when it is done to a team rather than with them.
No. Most clients start with messy systems and no AI experience. We build against the stack you have and handle the engineering.
The AI Operating Review takes two to three weeks. A first agent is typically live two to four weeks after that, longer only where an integration needs access we do not control. You get dated milestones in the proposal, not a range.
We can run it: hosting, monitoring, evaluations, model upgrades and new workflows. Or we hand over the code and playbooks and step back. Both are fine.
Yes. Code, prompts, evaluations and documentation, all yours.
Not the brief we take. We target the repetitive work that stops your team doing what you hired them for. If the goal is cutting headcount, we are the wrong firm.
Start here
Find out where AI actually
pays in your business.
Thirty minutes, no deck. We will tell you where we would start, and whether it is worth doing at all.