AI BriefingHow LangChain Built Its GTM Agent
Key point
LangChain built a GTM agent based on Deep Agents to automate its sales process, increasing lead conversion rates by 250%.
Details
The existing outbound sales process required reps to manually conduct research by switching between multiple tabs such as Salesforce, Gong, and LinkedIn, which was cumbersome. To solve this, LangChain built a GTM (Go-To-Market) agent that performs an end-to-end process using Deep Agents.
This agent detects new leads in Salesforce, gathers context, checks meeting history, and then sends a draft to Slack for the sales rep to approve. In particular, it was designed with the human-in-the-loop principle applied, so that no email is sent without the rep's final review.
The key results are as follows:
- Lead-to-qualified-opportunity conversion rate: increased by 250% as of March 2026 compared to December 2025
- Sales productivity: saved an average of 40 hours per month per rep in research and drafting time
- Usage: recorded 50% daily active users (DAU) and 86% weekly active users (WAU) within the sales team
Additionally, this agent is expanding beyond simple draft writing to integrate web activity, product usage, and marketing touchpoint data, providing account intelligence such as deal risk factors and expansion opportunities.
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