- Frontier model API integration
- RAG systems
- Intelligent automation
- AI-enhanced product features
- Guardrails & reliability
- Monitoring & iteration
- Frontier model API integration
We integrate large language models from providers like OpenAI and Anthropic into your applications – not as a chatbot slapped onto the corner of a screen, but as a core capability built into your product's workflows. Summarisation, classification, extraction, generation, analysis – the range of what these models can do is broad, but the value comes from applying them to the right problem in the right way.
We handle the technical complexity of working with these APIs: prompt engineering, token management, response parsing, error handling, rate limiting, and cost control.
- RAG systems
Retrieval-Augmented Generation lets AI work with your own data – documents, knowledge bases, internal records – rather than relying solely on what the model was trained on. This is what makes the difference between a generic AI response and one that's actually useful in a business context.
We build RAG systems that retrieve the right information, present it to the model with appropriate context, and produce responses that are accurate and grounded in your data. This involves careful work on chunking strategies, embedding models, vector storage, retrieval ranking, and prompt design. Get any of these wrong and the system either misses relevant information or surfaces the wrong thing.
- Intelligent automation
Some processes are too complex for simple rule-based automation but too repetitive for humans to do efficiently. AI fills that gap. We build automation that can handle variability – processing unstructured documents, categorising incoming requests, extracting data from inconsistent sources, routing work based on content rather than rigid rules.
The key is designing automation that knows its limits. We build systems that handle the confident cases automatically and flag the uncertain ones for human review, so you get the efficiency gains without the risk of silent failures.
- AI-enhanced product features
If you have an existing product, AI can add capabilities that would be impractical to build with traditional software. Intelligent search that understands intent rather than just matching keywords. Recommendations that improve with usage. Content generation tailored to specific contexts. Analysis that spots patterns across large datasets that humans would miss.
We work with you to identify which features would create genuine value for your users, design them to integrate naturally with the existing product, and build them to perform reliably at your scale.
- Guardrails & reliability
AI systems behave differently from traditional software. They can hallucinate, produce inconsistent outputs, and fail in ways that are hard to predict. If you're putting AI in front of your users or using it to make business decisions, these aren't acceptable risks to leave unmanaged.
We build guardrails into every AI feature: confidence thresholds that determine when to trust the output and when to escalate, validation layers that catch obvious errors, fallback behaviours for when the model isn't performing, and clear boundaries around what the AI is and isn't allowed to do. The goal is a system your team and your users can trust.
- Monitoring & iteration
An AI feature that works well at launch can degrade over time as data changes, usage patterns shift, or models get updated. We set up monitoring that tracks how your AI features are actually performing – accuracy, latency, cost, user behaviour – so problems are caught before users notice them.
AI features also improve with iteration. Real usage data reveals which prompts work, which edge cases need handling, and where the model's behaviour doesn't match user expectations. We build with this in mind, making it straightforward to refine and improve AI features as you learn more about how people use them.
