Add AI features to your apps — without rebuilding the stack.
Chat, summarisation, classification, search, content generation. We integrate LLMs into the apps you already have, with the engineering rigour production demands.
Integration is more than an API call.
Integrating LLMs into production is far more complex than calling an API. You need prompt management, response streaming, error handling, rate limiting, cost optimisation, model fallbacks, and user-experience design.
Most teams underestimate the engineering effort. What starts as a 'simple API call' quickly becomes a nightmare of edge cases, latency issues, and unpredictable model behaviour.
- LLM APIs have dozens of hidden edge cases.
- Prompt engineering requires constant iteration.
- Response latency and streaming need careful UX design.
- Cost optimisation is critical but hard to get right.
- Model selection and fallback strategies are complex.
How we integrate
We add AI capabilities to your existing applications — seamlessly and securely.
API integration
Clean, production-ready integration with OpenAI, Anthropic, Google, and other providers. Proper error handling, retries, and fallbacks built in.
Feature development
AI-powered features your users will love — intelligent search, content generation, summarisation, classification, and conversational interfaces.
Prompt engineering
Carefully engineered prompts that produce consistent, reliable outputs. Prompt management systems for easy iteration.
Security & compliance
PII filtering, data handling, content moderation, and audit logging — designed for enterprise compliance from day one.
Cost optimisation
Smart caching, token optimisation, and model routing that keep AI costs predictable. Use the cheapest model that gets the job done.
Multi-model support
Don't lock into one provider. We build abstractions that let you switch between GPT-4, Claude, Gemini, and open-source models easily.
Every engagement includes
- LLM API integration into your existing apps.
- Streaming response handling and UX.
- Prompt engineering and management systems.
- Multi-model support and fallback strategies.
- Cost optimisation and usage analytics.
- Security, compliance, and data handling.
- Performance monitoring and alerting.
- Ongoing support and model updates.
Ready to add AI to your apps?
Let's discuss how LLM integration can enhance your applications.