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Production AI applications with LangChain, LlamaIndex, and custom RAG pipelines.
We build production AI applications using LangChain, LlamaIndex, and custom frameworks. Our engineers design RAG (Retrieval-Augmented Generation) pipelines, build AI agents with tool use, implement evaluation frameworks, and deploy LLM applications with proper guardrails, monitoring, and cost optimization. We work with OpenAI, Anthropic, and open-source models.
We built a legal document analysis system processing 10,000+ documents with 95% accuracy using RAG.
View Case StudiesLangChain is great for prototyping and standard patterns. For production systems with specific requirements, we often build custom pipelines that are more maintainable and performant. We help you choose the right approach.
pgvector if you already use PostgreSQL, Pinecone for managed simplicity, Weaviate for hybrid search. We choose based on your scale, latency requirements, and existing infrastructure.
Caching, prompt optimization, model selection (using smaller models where appropriate), and batch processing. We typically reduce LLM API costs by 40-60% compared to naive implementations.
Yes. We implement transparency requirements, human oversight mechanisms, bias testing, and documentation as required by the EU AI Act. See our EU AI Act compliance page for details.
Senior engineers, EU timezone, no lock-in. Tell us what you need and we will show you how we can help.