Use case and metric
We agree the one business metric the pilot must move and how we will measure it, before any build starts.
AI Pilot to Production
Get your AI pilot out of the demo and into daily work.
We take one use case from proof of concept to a production system that real people use, typically in about eight weeks for a fixed fee. It ships with evaluation sets, guardrails, integration into your systems and adoption tracking, and it is measured against one business metric we agree upfront.
The problem
Why AI pilots so often stall before production.
01
A demo that never ships
The proof of concept impressed everyone in a meeting. Months later it still runs on a laptop and nobody uses it.
02
No way to know if it is good
Without evaluation sets, quality is judged by a few people trying it. Nobody can say whether a change made it better or worse.
03
Built beside the work, not in it
The pilot lives in a separate tool. Staff have to copy and paste between systems, so they stop using it.
04
Success never defined
Nobody agreed what the pilot should change, so there is no number to show leadership when the budget is reviewed.
What we deliver
Everything a pilot needs to become a product.
A new use case or a pilot that has stalled. Either way we take it to production and measure it.
Evaluation sets
Test sets built from your real cases and edge cases, so quality is measured on every change, not guessed.
Guardrails and security
Input and output checks, access controls and human review where the risk calls for it.
Integration into daily work
The AI runs inside the systems your staff already use, connected through secure APIs.
Adoption tracking
We track who uses it, how often and where they override it, so you can see if it is landing.
Stalled pilot rescue
We review a pilot that has stopped, find what is holding it back and either fix it or tell you honestly to stop.
How we deliver
From proof of concept to production.
Weekly demos throughout, and a founder signs off before anything goes live.
Always included
- One business metric agreed upfront and reported every week
- A senior squad of two to four people, with a demo every week
- Evaluations, guardrails and security built in from day one
- All code, models and documentation owned by you once invoices are settled
Typical tools
01
Weeks 1 to 2
Frame
We agree the use case, the metric and what production means for you.
- Baseline for the agreed metric
- Users, systems and data mapped
- Evaluation set started from real cases
02
Weeks 3 to 5
Build
We build the working system against the evaluation set.
- Model, retrieval and prompt choices tested
- Guardrails and access controls in place
- Weekly demos with the people who will use it
03
Weeks 5 to 7
Integrate and harden
We connect it to your systems and prepare it for real traffic.
- Integration with your existing tools
- Security review and load testing
- Monitoring for quality, latency and cost
04
Week 8
Launch and measure
Real users start using it and we report against the metric.
- Staged rollout to a first group of users
- Founder sign-off before production
- Metric and adoption report with next steps
Where we apply it
Industries we know well.
Further reading
From the blog.
Why AI Projects Fail Between Pilot and Production, and How to Fix It
Most AI pilots stall before production for predictable reasons. Here is how to spot them early and design pilots that are built to ship.
Enterprise AI Agents: How to Build Them for Production
A practitioner's guide to taking enterprise AI agents from demo to production: scope, architecture, guardrails, evaluation, security and rollout.
RAG vs Fine Tuning: How to Choose for Enterprise GenAI
RAG gives a model the right knowledge; fine-tuning changes how it behaves. A clear comparison and decision guide for choosing between them, or using both.
FAQ
Questions we hear a lot.
Why do most AI pilots never reach production?
Usually for three reasons: the data behind them is scattered, the workflow around them never changed and nobody owns the outcome. A demo can hide all three. We fix them together: we connect the data, build the AI into the way people already work and agree one owner and one metric before we start.
How long does it take to move an AI pilot to production?
Typically about eight weeks from kickoff to a production pilot used by real people, for a fixed fee. That depends on the state of your data and how many systems need connecting, which we check in the first two weeks. If something will take longer, we tell you then, not at the end.
Can you rescue a pilot another team or vendor built?
Yes. We start with a short review of the code, the data, the evaluation approach and why usage stalled. Then we recommend one of three things: fix and ship it, rebuild the parts that will not hold up in production, or stop. Sometimes stopping is the right answer, and we will say so.
How do you measure whether the AI is good enough to launch?
With an evaluation set built from your real cases, including the hard ones, agreed with the people who will use the system. We run it on every change and track accuracy, safety and cost. Launch happens when the results meet the bar we agreed, and a founder signs off before production.
What does a production AI pilot cost?
It is a fixed fee agreed in writing before we start, based on the use case, the data and the integrations involved. You know the cost upfront and you own all the code, models and documentation once invoices are settled. After launch, you can run it yourself or move to a monthly retainer for scale and run.
AI implementation services
Every part of implementation, covered.
AI Readiness Assessment
Use cases ranked, data and systems reviewed, and a costed roadmap in about two weeks.
AI Integration Services
AI connected to your ERP, CRM, core systems and product, with permissions and audit built in.
AI Adoption and Training
Process redesign, role-based training and an AI usage policy, so people actually use what you build.
Managed AI Operations
AI in production kept accurate, safe and affordable, fully managed or co-managed.
Our services
AI strategy, GenAI and agents, data platforms, analytics, MLOps and transformation.
Talk to a founder about AI Pilot to Production.
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.