Predictive analytics
We train regression and classification models on your historical data to forecast demand, churn or equipment failures. A recent project for a Midlands logistics firm cut late deliveries by 23% within three months of deployment.
Artificial Intelligence that works for your business
We build prediction models, computer vision pipelines and natural language tools that plug straight into your existing systems. Our team of seven engineers and data scientists has delivered over 40 production-grade AI projects since 2019, mostly for mid-sized companies in logistics, retail and healthcare.
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What we actually build
Each project starts with a two-week discovery sprint where we audit your data, define measurable outcomes and agree on a timeline. Here are the four areas we focus on.
Computer vision
From quality-control cameras on production lines to automated document scanning, we design and deploy image recognition systems. Our models run on-premise or in the cloud, depending on latency and data-privacy requirements.
Natural language processing
Chatbots that actually understand context, sentiment classifiers for customer reviews, and entity extraction from contracts. We fine-tune large language models on your domain-specific vocabulary so they give useful answers from day one.
Data engineering and pipelines
Good models need clean data. We build ETL pipelines, set up feature stores and connect disparate databases so your AI systems always train on fresh, validated information. Most pipeline builds take four to six weeks.
How a typical project unfolds
We keep things transparent. You will always know what stage we are at and what comes next.
Discovery sprint
Two weeks of data audits, stakeholder interviews and feasibility analysis. At the end you receive a written report with recommended approaches, estimated accuracy ranges and a fixed-price quote.
Model development
Our engineers build, test and iterate on models in two-week cycles. You get a demo at the end of each cycle and can steer priorities. This phase usually runs six to ten weeks.
Integration and deployment
We package the model as a REST API, a containerised microservice, or an embedded module, whichever fits your stack. Deployment includes monitoring dashboards and automated retraining triggers.
Ongoing support
Models drift. We offer 12-month support contracts that include monthly performance reviews, data-drift alerts and model updates. About 80% of our clients choose this option.
What our clients say
We asked a few long-term clients to share their experience.
"They reduced our invoice processing time from 14 minutes per document to under 90 seconds. The OCR model they built handles handwritten notes surprisingly well."
Operations director, Clearway Health Group
"Most vendors gave us vague timelines. Committed Ai View told us exactly which weeks they would deliver what, and they stuck to it. The demand forecasting model paid for itself in five months."
Supply chain manager, Fennell Logistics
"Our customer service chatbot now resolves about 60% of queries without a human agent. The team fine-tuned it on three years of our ticket history, so it actually knows our product range."
Head of digital, Braeburn Retail