AI & ML Integration
Make your existing product 10x smarter — without rebuilding it
We embed LLMs, RAG pipelines, and AI features directly into your existing stack. Your product stays intact — it just gets dramatically more capable. We've shipped AI features across SaaS, fintech, healthcare, and e-commerce.
What's Included
- LLM integration — GPT-4o, Claude 4, Gemini, Llama 3, Mistral
- RAG pipelines that actually retrieve the right context
- Vector search with Pinecone, Weaviate, or pgvector
- AI-powered search, recommendations, and personalisation
- Streaming responses with real-time UX
- Prompt engineering, evals, and ongoing optimisation
Real AI, Not a Wrapper
Slapping a GPT API call on a form field is not an AI product. We build integrations with proper context management, retrieval, evaluation, and fallback logic — so the feature actually works in production.
What We've Built
Smart document search for legal teams, AI writing assistants inside SaaS dashboards, recommendation engines that drive revenue, automated content moderation, and AI-powered onboarding flows that reduce support tickets by 60%.
Model-Agnostic by Design
We don't lock you into one provider. Our integrations are built so you can swap GPT-4o for Claude or Gemini based on cost, performance, or compliance — without rewriting your product.
Frequently Asked Questions
Can you add AI features to my existing product without rebuilding it?
Yes — that is exactly what we specialise in. We embed LLMs, RAG pipelines, and AI features directly into your current stack so your product stays intact and simply becomes more capable. Most integrations require no rewrite of your existing code.
Which AI models do you work with?
We integrate all major models including OpenAI GPT-4o, Anthropic Claude, Google Gemini, Llama 3, and Mistral. We help you choose the right model for accuracy, latency, and cost, and we can mix models for different tasks in the same product.
What is a RAG pipeline and do I need one?
RAG (Retrieval-Augmented Generation) lets an AI answer using your own data — documents, database, or knowledge base — instead of only its training data. If you want accurate, grounded answers about your specific business, you need one, and we build them with vector search using Pinecone, Weaviate, or pgvector.
How do you make sure the AI is accurate and reliable?
We build evaluation suites, monitor real usage, and continuously tune prompts and retrieval. This lets us measure quality objectively and catch regressions before your users do.
Tech Stack
Ready to Build Something
Great Together?
Tell us about your project. We typically respond within 24 hours and can start within a week.