From AI CuriosityTo Real Results
Assessment, proof of concept, custom models, and production build, all from the senior engineers who'll actually build it. We work out where AI genuinely fits your business, prove it on your data, and put it to work in your daily operations.
AI consulting that ships
Most consultancies hand you a strategy deck. We hand you working systems, along with the strategy that tells you which ones are worth building, and the engineering to run them.
AI Strategy & Opportunity Assessment
We map your workflows, measure where time and money are lost, and give you a prioritised AI roadmap with expected return, cost, and risk for each opportunity.
Proof of Concept
A working prototype on your real data in two to four weeks, with success criteria agreed upfront. See real accuracy and savings before committing to a build.
AI Pipelines & Automation
Production-grade pipelines that read documents, clean data, make routine decisions, and hand exceptions to people, all wired into your existing systems.
Insights & Reporting
Turn scattered operational data into answers. Ask questions in plain English, spot trends early, and get alerted when something needs attention.
Team AI Adoption
Practical workshops, clear usage guidelines, and the right tools, so your whole team uses AI safely and effectively every day, not just the enthusiasts.
Custom Model Training
When off-the-shelf models aren't accurate enough, we fine-tune and train models on your own data for your documents, products, and decisions, then run them securely in production.
From Idea to Impact in
Four Steps
Assess
1–2 weeks
Prove
2–4 weeks
Build
Under 90 days
Scale & Evolve
Ongoing
What you walk away with
Concrete, documented outcomes at every stage. No slideware.
From the AI Opportunity Assessment
A clear, costed view of where AI will pay off, usually within two weeks.
- A map of your key workflows and where time is lost
- A ranked shortlist of AI opportunities with estimated savings
- A data readiness review: what's usable now and what needs work
- Build cost, running cost, and risk for each opportunity
- A practical 90-day roadmap you can act on, with us or without us
From a production build
A system your team uses every day, engineered to the standard of the business software we've built since 2016.
- A live system integrated with your ERP, CRM, or data sources
- Human review for sensitive decisions, so AI drafts and people approve
- Security by default: SSO, role-based access, and audit logs
- Model-agnostic design, so you're never locked into one AI vendor
- Dashboards tracking accuracy, usage, cost, and savings
- SLA-backed support and ongoing model tuning
Consultants Who
Actually Build
Senior & Hands-On
The people who scope it build it:
Vendor-neutral:
Built to fit:
Results & Speed
Fast, visible progress:
Measured outcomes:
Adoption built in:
Safe & Reliable
Your data stays yours:
Production-grade:
Clear commercials:
Why Not a Big Consultancy
or DIY?
Time to first result
Weeks. An assessment in one to two weeks and a working proof of concept in two to four.
Months. Long discovery phases, or experiments squeezed in between everyone's day jobs.
Who does the work
Senior engineers. The people who scope it build and support it.
Whoever is available. Partners sell it and juniors deliver it, or your busiest people learn AI on the side.
What you get
A working system running in your daily operations.
A strategy deck, or a generic tool that doesn't fit your process.
Integration
Built in. Wired into your ERP, CRM, and documents, with custom software where off-the-shelf falls short.
Someone else's problem. Left for later, or handled by copying and pasting between tools.
Cost
Fixed and capped. Fixed fees, capped budgets, and running costs modelled upfront.
Open-ended. Day rates that roll on, or subscriptions and usage bills that creep up.
After launch
Looked after. Monitored, tuned, and improved under SLA.
Left to drift. Handed over and forgotten, or broken when a model or API changes.
Proof, not Promises
AI-Powered eCommerce Content
Productify.ai10x faster listing creation and 98% attribute accuracy across more than 10M products.
Delivered
Automated Receipt Processing
95–98% data extraction accuracy and 85% less manual review time.
Delivered
Logistics Claims
40% faster claim resolution and less revenue leakage through automated policy checks.
Delivered
Automated CRM Data Cleansing
Up to 80% fewer duplicates and far more accurate reporting.
Delivered
Retail Deal Extraction
80% less manual data capture, with better accuracy.
Delivered
Want the full picture?
Get in touch and we'll send you detailed case studies relevant to your use case.
Ready to put AI to work?
Start with a free 30-minute strategy call. We'll talk through your operations and point out where AI could save you time and money, whether or not we work together.
- Senior engineers, never trainees
- Vendor-neutral: no lock-in
- EU/regional data residency
FAQs
Over one to two weeks we interview the people doing the work, review your processes and data, and measure where time and money go.
You get a ranked shortlist of AI opportunities, each with estimated savings, build and running costs, risks, and a practical roadmap. It's yours to act on, with us or without us.
Then we'll tell you. Sometimes the best fix is a simple automation, a better integration, or a small piece of custom software, and we build those too. We'd rather recommend the right tool than sell you an AI project that won't pay back.
Yes, when it's worth it. Many problems are solved well by today's leading models with the right data and prompts. When accuracy, cost, or privacy demands more, we fine-tune or train models on your own data, measure them against agreed benchmarks, and run them in your environment.
We agree the numbers before we build: hours saved, error rates, turnaround times, or cost per transaction. The proof of concept is measured against them, and in production, dashboards track accuracy, usage, cost, and savings, so you can see the return rather than take it on trust.
Yes. We help you choose the right tools, set clear usage guidelines (including what data can and can't go into them), and run practical workshops built around your team's real tasks. That way the whole team gets the benefit, not just the enthusiasts, without putting client data at risk.
No. We handle the engineering end to end, from data and integration to hosting and support. If you have an IT team or provider, we work with them on access, security, and integration.
No. We build exclusively on enterprise-grade services and configure zero-retention policies where available, so your data is processed for the request but never stored or used for training by the AI vendor.
We don't rely on the model's memory. We use retrieval-augmented generation (RAG), which means the AI answers only from the data we give it: your documents, databases, and policies. If the answer isn't there, it says so instead of guessing.
For anything sensitive, a person reviews the output before it's used.
No. We build model-agnostic systems, so we can switch the underlying engine (for example from OpenAI to Anthropic or Google) without rebuilding your application. We simply move to the best model for the price and performance.
We model them for you during the assessment, so there are no surprises. In production they're bundled into a predictable managed-service fee, with usage caps to prevent runaway bills.