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