Finance · Case study
Enterprise Agentic RAG Platform
LangGraph agentic RAG with citations, tool use, and human-in-the-loop review over approved policy and product knowledge.
Outcome: 55% less research time
The challenge
Analysts and support teams hunted across SharePoint, PDFs, and wikis for answers. Inconsistent guidance slowed cases and raised compliance risk when staff relied on memory.
Our solution
We built an agentic RAG platform on LangGraph and LangChain: hybrid retrieval over Qdrant, citation-backed answers, tool calling for internal APIs, guardrails for sensitive topics, and LangSmith tracing for evals. FastAPI services and a React console give reviewers a clear approve/escalate path.
Results
- About 55% less time spent searching for approved answers
- Answers grounded with source citations
- Human review retained for high-risk decisions
- Observable traces for quality and prompt iteration
Tech stack
Core technologies used on this engagement.
LangGraph
LangChain
LangSmith
OpenAI
Anthropic
Qdrant
Python
FastAPI
PostgreSQL
React
Docker
Kubernetes
Services involved
Capabilities that powered this delivery.
AI & Intelligent Solutions
Voice agents, agentic RAG, document intelligence, and automation built for real workflows.
Learn moreCustom Software Development
Tailored applications built around your workflows and business rules.
Learn moreCloud & Infrastructure
Secure, scalable cloud setups and reliable infrastructure foundations.
Learn moreWant results like these?
Share your challenge and we'll outline a realistic approach, timeline, and stack.