AI that ships
From opportunity discovery to production deployment, we help you adopt AI that actually works. We find the highest-value use cases, design the solution, build it, and train your team to use it — no slideware, just systems running in production that earn their keep.
We audit your workflows and data to find where AI will genuinely pay off — and, just as importantly, where it will not.
We scope the highest-value use case and design a solution that fits your existing tools and the way your team already works.
We build the system and integrate it into your stack, with clear guardrails on data, access, and governance.
We ship to production and train your team, so adoption sticks long after we hand over.
AI Product and Lead Generation
AI psychometric SaaS
Challenge. An AI psychometric assessment product needed to be built into a credible SaaS and put in front of the right enterprise buyers.
What we did. We worked on the HumanMetrix product and ran the lead generation behind it, from the SaaS experience through to demand generation for enterprise buyers.
Every engagement is tailored to your goals and budget. These are starting points — the first consultation is always free.
per project
An honest read on where AI will pay off, with a prioritised roadmap.
That is exactly where we start — an honest assessment of where AI will and will not pay off for your business, before anyone writes a line of code.
Yes. We build around your current stack rather than forcing a rip-and-replace, so AI fits into how your team already works.
We design for it from the outset, with clear guardrails on data handling, access, and model use, so you stay in control and compliant.
5 min read
Not every AI problem deserves a custom build, and not every off-the-shelf tool will fit. Here is a clear way to decide which path is right.
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AI is not a strategy. Here is how to find the use cases that earn their keep — and avoid the expensive experiments that never ship.
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Plenty of companies run an AI pilot. Far fewer put one into production. The gap is rarely the technology — it is how the work was scoped from the start.
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