We build machine learning models, natural language systems and computer vision tools that solve real problems. If your data sits unused in spreadsheets and databases, we turn it into decisions you can act on.
Every project starts with a question: what decision are you trying to improve? From there we pick the simplest technique that answers it. Sometimes that is a straightforward regression model. Other times it requires a custom transformer architecture. Here are the areas we work in most often.
We train models on your historical data to forecast demand, customer churn, equipment failure or financial risk. A typical churn model for a mid-size SaaS company takes us four to six weeks from raw data to a production API endpoint. You get probability scores per customer, updated daily, plus a dashboard your team can filter by segment.
From automated ticket classification to contract clause extraction, we build NLP pipelines that read text the way a human would, only faster. One logistics client reduced manual email sorting from 12 hours a week to under 30 minutes after we deployed a fine-tuned classification model on their support inbox.
Quality control on a production line, shelf-stock monitoring in retail, damage detection on infrastructure: our computer vision models handle image and video feeds in real time. We have deployed systems that inspect up to 200 items per minute with accuracy above 97 percent, running on edge hardware so nothing leaves your premises.
A model is useless if it cannot run reliably. We set up the pipelines, monitoring and retraining schedules that keep your AI systems accurate over time. Our standard MLOps stack uses containerised microservices, automated drift detection and version-controlled model registries so you know exactly which model is serving which predictions.
We have been building production AI systems since 2018. That means we have seen models fail in the real world, not just on Kaggle leaderboards. Most of our work is with mid-market companies (50 to 2,000 employees) in manufacturing, logistics, financial services and healthcare.
Our team of eleven includes six machine learning engineers, two data engineers, a UX designer who specialises in AI-facing interfaces and two project managers. Everyone writes code. Nobody only manages.
We charge on a fixed-price-per-milestone basis for most projects. You approve each deliverable before we invoice. If the model does not meet the accuracy threshold we agreed on, we keep iterating at no extra cost until it does, or we refund that milestone. That is written into every contract.
"They built a demand forecasting model that cut our overstock costs by 18 percent in the first quarter. The weekly retraining pipeline they set up means the model adapts to seasonal shifts without us lifting a finger."
Rachel Kemp, operations director at a UK food distributor
"We needed a document extraction tool that could read handwritten notes on inspection forms. Their computer vision pipeline handles about 4,000 forms a week now and flags the 2 percent that need human review. Genuinely changed how our compliance team works."
David Osborne, head of compliance at a construction firm
Send us a message and we will reply within one working day. If you already have a dataset or a brief, attach it to the email and we can give you a rough scope estimate in our first reply.
United Kingdom, Scotland, North Streich-Skilesworth, UZ39 3GD, 2 Baker Street
