From RAG systems to complex reasoning chains—we build LangChain applications that actually work in production. Python or JavaScript, your choice.
The Challenge
Most teams underestimate the gap between a working demo and a production system. Here's what goes wrong.
Without proper RAG architecture, LLMs confidently make up facts. Users lose trust fast.
Naive implementations burn through API credits. Poor chunking and retrieval multiply costs unnecessarily.
Users expect instant answers. Unoptimized chains with multiple LLM calls create frustrating delays.
Wrong documents, missed context, irrelevant results. The AI can't answer what it can't find.
Our Services
End-to-end LangChain development from architecture to deployment.
Connect your LLM to your data. We build retrieval augmented generation systems with proper chunking, embedding strategies, and vector database integration.
Build intelligent systems that answer questions from your documents, contracts, knowledge bases, and internal wikis with accurate, sourced responses.
Multi-step reasoning, tool use, and complex workflows. We build LangChain Expression Language (LCEL) chains that handle real business logic.
Pinecone, Weaviate, ChromaDB, Qdrant—we set up and optimize your vector store for fast, accurate semantic search.
Technology
LangChain
Python & JS
OpenAI
GPT-4, Embeddings
Anthropic
Claude
Pinecone
Vector DB
Weaviate
Vector DB
ChromaDB
Vector DB
PostgreSQL
pgvector
FastAPI
API Layer
Process
From concept to production in four phases.
We understand your data, use case, and success criteria. What questions should the system answer?
Design the right retrieval strategy, chunking approach, and chain structure for your needs.
Build, test, and iterate. We optimize for accuracy, speed, and cost efficiency.
Production deployment with monitoring, error handling, and documentation.
Use Cases
AI that answers customer questions from your help docs, reducing ticket volume and response time.
Let employees find answers across Confluence, Notion, Google Drive, and internal wikis.
Automated research from multiple sources with summarization and citation tracking.
AI that understands your codebase and answers developer questions with relevant examples.
Pricing
Every LangChain project is different. We provide custom quotes based on your data volume, complexity, and requirements.
Tell us about your project. We'll review your requirements and get back to you with recommendations for your LangChain implementation.