Why Definely chose LangGraph for building their multi-agent AI system

See how Definely used LangGraph to design a multi-agent system to help lawyers speed up their workflows. Related content Case Studies How Workday Built an Enterprise-Scale AI Agent Platform with LangGraph and LangSmith Sofia Sulikowski November 10, 2026 4 min Observability & Evals LangSmith What Is Eval-Driven Development?

Agent or tool: LangChain
Topic: Customer Support
Reported on: Blog (LangChain)
Added: 2026-11-11

Why it matters

Support is repetitive and time-sensitive. Agents can draft answers, look things up and handle simple requests, so people can focus on the tricky ones. It is one of 554 sightings filed under Customer Support on Agent Sightings (number 503 by interest), and one of 25 involving LangChain.

How you could try it

Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into LangChain or any similar agent and adjust the details to your situation.

I want an agent to handle routine customer questions end to end, and pass anything unclear to a person. The tool in the source case was LangChain.

Saved

Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.

Source

Read the original first-hand account on Blog (LangChain): https://langchain.com/blog/customers-definely. Our summary is a paraphrase; details are in the source.

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