AI Agents & RAG Systems Development

From OpenAI, Claude, and Gemini integrations to full RAG pipelines, AI agents, and multi-agent systems — including self-hosted (Ollama) options for data-sensitive clients. We build AI products that solve real business problems, with evaluation, monitoring, and fallback handling built in.

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The problem we solve

Most AI chatbots hallucinate because they answer from memory instead of looking things up. A confident wrong answer about your refund policy or pricing is worse than no answer at all — and it erodes customer trust fast.

What we build

  • RAG-powered support chatbots grounded strictly in your documentation (with citations)
  • Document extraction and classification pipelines
  • AI-driven content generation with your brand voice as a guardrail
  • LLM-based workflow routing and decision logic
  • Intelligent data enrichment and lead scoring
  • Self-hosted models via Ollama for privacy-sensitive workloads

Common use cases

  • Support bot that resolves 70% of tickets from your docs
  • PDF → summary + flashcards + quiz generation
  • Inbound email triage and auto-classification
  • AI step inside an n8n automation pipeline

Tools & tech

OpenAI GPT-4oClaudeGeminiOllamaLangChainRAGpgvectorPinecone

Frequently asked questions

How do you stop the AI from making things up?
We use retrieval-augmented generation (RAG): the model answers only from your retrieved documents, with a strict instruction to say 'I don't know' rather than guess. We add an evaluation harness to measure accuracy before launch.
Can the AI run on our own servers for privacy?
Yes. For data-sensitive clients we deploy open models via Ollama so no data ever leaves your infrastructure. We'll advise on the accuracy/privacy trade-off.
Who pays for the OpenAI/API tokens?
You do, on your own account — we never mark up third-party API costs. We optimise prompts and caching to keep your token spend low.

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