Rapid Validation

Prove what AI can do for your business in 10 working days.

Bring us the problem, pilot or AI investment you most need to prove. We agree what proof looks like before we start, build a working proof on your real data and measure the result by day 10.

One agreed measure

Built on your real data

Scale, change or stop

THE OFFER

ยฃ15k

fixed price

10

working days

Money-back guarantee

If we canโ€™t deliver the proof we agreed at the start within 10 working days, weโ€™ll give you your ยฃ15,000 back.

The problem

Why AI value is hard to prove

Most organisations now have AI in some form: pilots, copilot licences, an agent or a platform. Few can show what it returns. Pilots stall on legacy systems and messy data. Success is tracked by demos and logins rather than outcomes. And without a baseline, deciding what to back becomes a debate.

The question isnโ€™t whether AI can work. Itโ€™s where it creates value for you, and how to prove it.

Mark Simpson, Chief AI Officer at Griffiths Waite

โ€œYou donโ€™t need more technology. You need more value from the technology you have, and clarity on what you need next.โ€

Mark Simpson, Chief AI Officer

Where it helps

Which of these sounds like you?

Every Rapid Validation follows the same 10 days. What we set out to prove depends on where youโ€™re stuck.

REDESIGN THE WORK

Find the AI advantage your competitors canโ€™t replicate.

โ€œWeโ€™ve got ideas, but it takes forever to get anything out of the door.โ€

Adding AI to the way you already work makes tasks faster, but competitors can make the same gains. Advantage comes from redesigning the work around your own expertise, data and client knowledge.

IN 10 WORKING DAYS

We redesign one process around AI, build a working agent on your data and measure the value against an agreed baseline.

WORK WITH YOUR ESTATE

Donโ€™t let your existing estate dictate how much value you get from AI.

โ€œWeโ€™ve proven value in pilots, but we canโ€™t scale them.โ€

The prototype works, then systems that were never built for AI stop it scaling. Modernising everything first puts the value years away, and a separate AI stack adds cost without fixing the real constraint.

IN 10 WORKING DAYS

We prove your highest-value AI opportunity within the systems you already have, then show what needs to change for it to scale. No rip and replace.

CHOOSE THE RIGHT PILOT

Find the AI pilot worth scaling.

โ€œEvery pilot team believes theirs is the one to back.โ€

Each pilot has a promising demo and its own champions, but few have consistent success measures, an owner or a route to production. The value usually sits in one or two of them. The hard part is proving which.

IN 10 WORKING DAYS

We judge every pilot on the same evidence, then rebuild the strongest one and prove it on your real data.

PROVE THE RETURN

Prove what your AI investment returns.

โ€œWe know what AI costs us. We canโ€™t say what it returns.โ€

AI spend shows up every month in licences, tokens and platforms. The return rarely does, because baselines werenโ€™t captured and success is tracked by usage. That makes AI budget an easy cut.

IN 10 WORKING DAYS

We measure the true return on one live AI investment, and give finance a method to measure the rest.

HOW IT WORKS

Ten working days, from an agreed problem to evidence you can act on.

We agree the problem and the success measure before we start, so the sprint can move quickly. Within 10 working days youโ€™ll have a working proof on your real data, the measured value and the evidence to decide.

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DAY 1

Agree what matters

Agree the problem, the baseline and the success measure that would make solving it worthwhile. Map how the work happens today.

Output: one problem, a baseline and an agreed success measure.

DAYS 2โ€“3

Design for production

Define the data, systems and decision boundaries. Agree the integration route with security and architecture, and set the guardrails and ownership.

Output: a redesigned process, agreed with the people who run it.

DAYS 4โ€“8

Build, test and learn

Build the smallest working version on your real data and systems, test it against how the work happens today and improve it with every cycle.

Output: a working proof, tested on real data, not a controlled demo.

DAYS 9โ€“10

Prove and decide

Measure the result against the baseline and set out the owner, the cost and what it would take to scale.

Output: measured value and a clear decision to scale, change or stop.

A small, cross-functional team

Product, design and engineering working as one, alongside your people.

Design before build

We redesign the work around what AI makes possible, rather than automating the process you already have.

Evidence over opinion

A baseline agreed on day one, a working proof tested against it and a decision based on what we measured.

What it looks like

Rapid Validation in practice

Four client examples, one for each of the situations above.

Atradius

Maybourne

Simple Life Homes

Swissport

CLIENT EXAMPLE ยท REDESIGN THE WORK

Atradius: reinventing broker sales with AI

The situation

Atradius is a global trade credit insurer. Brokers are its most important route to market, driving more than 80% of revenue. Broker intake was manual and fragmented: credit requests arrived on paper and were re-keyed by hand, communication was split across emails, calls and documents, and brokers had little visibility of where a case stood.

The real constraint

With no standard process, intake could not be automated or scaled. Every manual step added latency and compliance risk, poor transparency was damaging broker trust, and account managers spent their time re-keying rather than with clients.

What we did

We acted as adviser and builder, proving the change before Atradius committed to a full product. We agreed the measures that matter, time-to-quote and manual preparation time, co-designed a self-service route with brokers, and prototyped AI that reads paper credit requests and pre-fills core systems, tested on real broker forms.

What happened next

With the change proven, we rolled out Atrium Acquire in phases, with secure enterprise integration that maintains compliance and governance. The result was a redesigned sales process, not just a portal, and a blueprint for future AI-enabled change.

60โ โ€“โ 70%

reduction in time-to-quote once scaled

80%

less manual sales preparation time

ONCE SCALED

Account managers freed from re-keying to focus on client engagement.

Improved governance and data integrity, reducing compliance risk.

Stronger broker loyalty, positioning Atradius as a modern, responsive partner.

Who we are

Thirty years of making enterprise technology work. Now applied to AI.

For more than 30 years, Griffiths Waite has built custom technology for large enterprises. For most of that time, our closest partners were IT leaders. They trusted us with complex, enterprise-grade systems where reliability, security and technical excellence were never optional.

We earned that trust one delivery at a time, in an industry better known for running late and over budget.

WHY WE CAN HELP WITH AI

Most organisations arenโ€™t short of AI ideas. Theyโ€™re short of proof.

The decisions that matter about AI now sit with leaders in operations, product, digital, finance and strategy, who are accountable for showing that technology delivers commercial results. Three decades of enterprise delivery give us what that takes.

We know where AI stalls

In legacy systems, messy data, governance and security reviews. Weโ€™ve worked on that ground for 30 years, so we design for it from day one.

We start with a measurable outcome

Every engagement begins with a baseline and a success measure. You get evidence a board can act on in weeks, not years.

We bridge business and IT

We speak both languages, so a proof that works for the business is one your IT team can support, scale and sustain.

Large enough to deliver complex enterprise outcomes reliably.

Small enough to move faster, go deeper and care more.

Trusted by enterprise leaders for over 30 years of custom software delivery.

Trusted by enterprise leaders for over 30 years of custom software delivery.

Wave Background

BRING US YOUR BIGGEST PROBLEM

Start with one problem.

Tell us the problem, pilot or AI investment you most need to prove. Weโ€™ll agree whether it suits a 10-day Rapid Validation, what success looks like and who needs to be involved.

THE GUARANTEE

Your problem. Two weeks. ยฃ15,000.

Before we start, we agree the problem, the outcome you need and what proof looks like. Then give us 10 working days.

If we canโ€™t deliver the proof we agreed at the start within 10 working days, weโ€™ll give you your ยฃ15,000 back.

Tom Shepherd

Tom Shepherd

Business Development Director

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