AI is easy to start and hard to run well. The difference is the people.
Technically smart. Commercially experienced. Built to put AI to work.
Many providers advise, and many sell tools. We are a team of people who have run businesses, built the technology and led transformation, from very different backgrounds. That mix is why our advice reaches the work, and why the work stands up in front of a board, a customer or a regulator.
What a report or a tool alone cannot give you.
Our engineering and architecture leadership comes from financial services and capital markets, with cloud-native delivery behind it. We build and deploy what we recommend.
We have led businesses, engineering and growth. We know what a board, a budget and a customer ask, so the work is aimed at outcomes you can measure.
Our careers span banking, consumer credit, collections, capital markets, technology, engineering, manufacturing, property and professional services. Different sectors teach different lessons, and we bring them to yours.
It starts with people who have done the work before.
Our founders have led technology at UK banks and lenders, run engineering inside large groups, taken a regulated credit business from concept to authorisation, and led go-to-market for technology and property businesses, with an engineering and manufacturing mindset running through the work. Around them is a team of agents, each with a named owner, permitted actions and a record of its decisions, working the way we ask clients to work. Our advisers are human and agentic, and both are accountable.
Different careers, one method, applied across sectors.
Banking, credit, technology, engineering, manufacturing, property and professional services, brought together on every engagement.
- Advises, then hands you a report to act on.
- Sells a tool and leaves the rules to you.
- Brings deep knowledge of one tool or one sector.
- Advises, then builds and deploys the controls and agents that act on it.
- Brings the tools, the rules and the evidence together.
- Brings experience across sectors, so lessons from one reach another.
Both advice and tools are useful. The gap is the work in between, and the people who have done it.
From running regulated businesses to putting AI to work in control.
The mindset behind the work.
We prove ideas on real jobs such as letters, calls, invoices and content, because the application is where AI proves its worth or does not.
A defined process, quality checks at each stage, a named owner and a record, so results are consistent and traceable.
We start from what AI makes possible for your business, then add the control that lets you say yes with confidence.
We try new models and methods early in a sandbox of our own, and test every model release before it reaches a client.
We work where AI is changing fastest, including agents that already run parts of GenWA itself.
We have led technology change in banks and lenders, and we bring that experience of change that lasts to AI.
The same method, applied where the rules differ most.
Pick a sector to see where AI is used, the rules we can load into Guard and Evidence, and how we help.
Financial services
Where AI is used
Collections, complaints, customer communications and onboarding checks.
Rules we can load
Financial Conduct Authority Consumer Duty and Prudential Regulation Authority expectations, and UK GDPR (UK data protection law).
How we help
Controls designed against the rules, with evidence a regulator can read.
Legal and accountancy
Where AI is used
Research, drafting and review, and invoice processing, with client material kept out of public AI tools.
Rules we can load
Solicitors Regulation Authority, accountancy bodies and the Financial Reporting Council.
How we help
Supervision records and managed accounts, so accountability stays with the firm.
Healthcare and care
Where AI is used
Consultation notes, letters and patient communications, with clinical judgement left to people.
Rules we can load
Care Quality Commission expectations, the NHS Data Security and Protection Toolkit and special-category data rules.
How we help
Control over where health data goes, and inspection evidence kept ready.
Retail and consumer
Where AI is used
Customer contact at peak, product content and promotions.
Rules we can load
Consumer law, Advertising Standards Authority codes and marketing consent rules.
How we help
Brand and compliance checks on content, and a record of what went out.
Engineering and manufacturing
Where AI is used
Quoting, quality records, technical documentation and design review, with drawings and design files kept out of public AI tools.
Rules we can load
Customer security requirements such as Cyber Essentials (the UK government-backed security scheme), export controls and the quality records customers audit.
How we help
Rules that stop design files reaching public tools, and evidence for customer questionnaires and audits.
Technology and software
Where AI is used
Customer onboarding, support and security questionnaires, and AI features inside your own product.
Rules we can load
ISO/IEC 42001 (the international standard for managing AI), UK GDPR and customer security questionnaires.
How we help
Evidence packs that answer questionnaires, and visibility of model spend.
AI arrived without a plan. Eight things went wrong at once.
Each one is measured. Visibility is where the chain breaks.
The bill you can’t see
AI is now a metered bill. It compounds.
KPMG UK, 2026
Premium by default
People use the most expensive AI for everyday work.
Ramp, 2026
Accounts you don’t own
Company data leaves through personal accounts.
Microsoft UK, 2025 · vendor survey
The same work, twice
Teams build the same thing separately, then redo the output.
HBR, 2025
Skill stuck in individuals
The gains are personal. The business never sees them.
Cornerstone, 2025 · vendor survey
Spend without proof
Money went in on fear. Now someone wants the return.
PwC, 2026
Nothing to show the regulator
The rules already apply. The evidence doesn’t exist.
DSIT Cyber Security Breaches Survey, 2026
The ground keeps moving
Models are retired, re-priced and changed under you. Someone has to decide.
Anthropic model deprecations, 2026
AI does not move accountability. The regulators have now said so, one by one.
UK GDPR and the Data (Use and Access) Act already cover what your AI does with personal data. Sector regulators have gone further: a named person stays accountable for what AI produces. Only 24% of UK businesses using AI have practices that address the risk (DSIT, 2026), and the ICO issued £32.4m of penalties last year.
- Organisations “remain responsible for their use of agentic AI systems”. Clicking approve on an AI ranking without independent analysis is not meaningful human involvement.
- “UK consumer law applies whether decisions are made by people or by AI.”
- “AI has no separate legal personality; solicitors … remain accountable for their work and outputs, regardless of how that work has been prepared.”
- Model risk, including AI and vendor models, sits with a named Senior Management Function holder (SS1/23).
- AI “can enhance, but not replace human decision making”. Providers need accountability procedures for when AI causes harm.
- Auditors remain accountable for work produced with generative and agentic AI.
of organisations have had an AI agent exceed the permissions it was given.
have a named owner for most of their agents.
data protection complaints to the ICO last year, up from 42,315.
New models arrive every few weeks. Old ones are switched off. Someone has to decide.
A handful of companies and governments reshape the AI market month by month. Models are retired with weeks’ notice, change behaviour without a version change, and three vendors hold most of the enterprise market. Today that decision is made by whoever is at the keyboard.
models retired by one leading vendor in six months, on 60 days’ notice.
notice before four models were removed from ChatGPT.
use of the previous model, one month after a new release.
We watch the market, test every relevant release against your jobs in our sandbox, decide where it may and may not be used, set that as the default in your rules, and manage every change as a controlled event with a way back. Your staff do nothing. How Change Control works
Control belongs with the board, not with whoever is using the tool.
Today, employees decide how and when they use AI. GenWA gives the decision back: what the business uses, what it costs, what it is for, and what it returns.
Usage Insight. Every tool, account, pound and breach, monthly.
The forecast: headcount, roles, and the investment they will need.
AI Strategy and Planning: where it pays, where it must not be used.
Value register and evidence pack: to shareholders, auditors, regulators.
Seven questions most boards can’t answer.
Nothing leaves this page. For the full picture, take the AI health check.
See your own numbers.
Upload your usage export. A first read in your browser now; the full report within 48 hours of your upload.
Start the checkBecause AI deserves better than fear or hype.
We have seen new technology reach a business faster than the habits around it. We are here to close that gap: to help businesses say yes to AI with confidence, put it to work on real jobs, and show anyone who asks how it is controlled. Control is what lets a business move fast, and that conviction runs through everything we build.
Meet the people, and read what we stand for.
Keep reading
Straight answers.
What makes GenWA different from other AI providers and consultancies?
We are technically smart and commercially experienced, from very different backgrounds. We advise and then build and deploy the controls and agents that act on the advice, with a named person accountable for every job.
Who is behind GenWA?
GenWA is led by three founders and executives who have led technology, run a regulated credit business and led go-to-market for technology and property businesses. You can read about each on the team page.
Do you only work in financial services?
No. Financial services is a specialism, where controls had to be real first, but the method applies to legal and accountancy, healthcare, retail, engineering and manufacturing, technology and other sectors.
What do you mean by a manufacturing mindset?
We treat AI work like good production: a defined process, quality checks at each stage, a named owner and a record, so results are consistent and traceable.
Are your advisers people or AI?
Both. Our advisers are human and agentic. Agents have a named owner, permitted actions and a record of their decisions, and people approve anything consequential.
Do you only advise, or do you build too?
We do both. We advise on policy, controls and strategy, and we deploy products and build and run agent functions, so advice reaches the work.
Is GenWA certified?
No. Our products are control-mapped to frameworks such as ISO/IEC 42001 (the international standard for managing AI), and we prepare the evidence. Accredited bodies issue certification. This is not legal advice.
Do you work with engineering and manufacturing businesses?
Yes. Engineering and manufacturing is one of the sectors we cover, with its own sector page and rules that keep design files, drawings and pricing out of public AI tools. A manufacturing mindset also shapes how we run AI work: a defined process, quality checks and a named owner.
Talk to the people who will do the work.
Control-mapped, not certified. We prepare the evidence; accredited bodies issue certification. This supports compliance and is not legal advice.