AI Solutions
Practical AI integration built around your actual workflows. We focus on where AI creates reliable value and help you avoid the projects that sound good and deliver little.
Most AI projects fail at the integration layer, not the model layer. The models exist and they work. The hard part is connecting them to your data, your users, and your processes in a way that actually changes outcomes.
We approach AI practically. We start by understanding your workflows and identifying where intelligent automation would reduce friction or cost. Then we build the integration, test it against real data, and measure whether it delivers what we expected. If it does not, we adjust rather than double down.
What We Deliver
LLM Integration
We integrate large language models into existing products and workflows. Document processing, intelligent search, automated responses, and internal tooling built around the models that actually fit your use case.
Workflow Automation
Identifying and eliminating repetitive manual processes using AI-assisted automation. We focus on workflows where AI adds reliable value, not where it adds complexity for its own sake.
Data Pipeline Engineering
Structured pipelines that move, clean, and transform data into formats that AI models can actually work with. The quality of AI output is determined almost entirely by the quality of the input.
Custom Model Integration
Connecting pre-trained models to your systems via APIs, fine-tuning where it makes sense, and building evaluation frameworks so you know when the model is performing well and when it is not.
Intelligent Document Processing
Extraction, classification, and summarisation of documents at scale. Useful for industries like insurance, legal, and healthcare where document volume is high and manual review is expensive.
AI Strategy and Scoping
Before building anything, we help you identify where AI is likely to give you a return and where it is likely to be a distraction. Not every problem needs a model. Some need better data or a simpler process first.
Who This Is For
- Companies with high volumes of repetitive knowledge work that could be automated or augmented
- Businesses sitting on large amounts of unstructured data they are not currently using
- Teams that want to integrate AI into their product but need guidance on where to start
- Organisations that have tried AI tools and found them too generic for their specific use case
Our Approach to AI
We do not start with a model and look for a problem to apply it to. We start with a workflow that is expensive, error-prone, or slow, and assess whether AI can improve it reliably and cost-effectively.
Every AI integration we build includes evaluation criteria agreed upfront. You will know before we ship whether the model is performing at the standard we set out to achieve.