Key Benefits

  • RAG pipelines built with LangChain.js and Qdrant — your documents and data become queryable by your team and systems
  • Multi-step agentic workflows with LangGraph.js — AI processes that handle complex, stateful logic without brittle scripting
  • Production-ready Node.js deployment on Azure — consistent with your existing JavaScript stack, no Python environment required
  • Internal AI assistants for legal, financial, and operational knowledge bases — staff get accurate answers from your own documents
  • Workflow automation — manual processes handed off to AI agents that trigger, route, and complete tasks reliably
  • Azure OpenAI integration with your own data — commercial-grade LLM access with enterprise security and compliance
Stack

Technologies Used

LangChain.js
LangGraph.js
Qdrant Vector Database
LangChain.js
LangGraph.js
Qdrant Vector Database
Azure OpenAI Service
Node.js / TypeScript
Azure OpenAI Service
Node.js / TypeScript

Considering an AI agent or RAG implementation? We start with a 2-week AI Discovery Workshop — we map your use case, assess your data, and deliver a fixed-fee build plan before any development begins.

FAQs

Frequently Asked Questions

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