AI

AI that makes it into production.Most of it never does.

Most AI projects die between the demo and the deployment. Something impressive gets built, everyone agrees it's the future, and a year later nothing is running in the business. The technology was rarely the problem.

We build AI into the systems you already run, and stay accountable for it once it's live. Same answer as everything else we do: one team, owning it until it works.

Book a strategy call

Why pilots stall

A demo proves it can work. Production proves it does.

A pilot runs on clean data, a willing team and no deadline. Production has none of those. The model meets real documents, real edge cases, and real people who already have a job to do — and somewhere in there the project stops being anyone's responsibility.

That gap isn't a technology problem. It's an ownership problem.

What we build

Three things, all of them shipped before.

AI automation

The manual steps in a workflow: reading documents, extracting data, moving it between systems.

  • Document parsing and data extraction at volume
  • Call and meeting transcription into structured records
  • Report generation from unstructured inputs
  • Routing and triage inside existing workflows

AI transformation

Changing how a process works, not just making the current version faster.

  • Decision layers inside operational workflows
  • Copilots embedded where the work actually happens
  • Predictive analytics on operational data
  • Rebuilding a process around what AI makes possible

AI optimisation

Processes you already run, made measurably better.

  • Cost and latency tuning on existing AI systems
  • Accuracy measurement and evaluation harnesses
  • Replacing brittle rules with models where it pays
  • Taking a stalled pilot the rest of the way

Proof

Days to hours. And we still support it.

Insurance case processing ran on manual document handling and took days. We built a platform that parses claim PDFs, transcribes calls, extracts structured data and generates the reports. Processing dropped from days to hours.

See all six projects →

Scope

We'll tell you when AI isn't the answer.

Plenty of problems labelled "AI" turn out to be data problems, process problems or reporting problems, where a model would add cost and uncertainty and little else. If that's what we find, we'll say so — the same way we would about any product we didn't think was worth building.

Book a strategy call

hello@lucrumtech.com · Reply within 24 hours