LangChain Grabs $300M Series C At $3B Valuation

Illustration for LangChain Grabs $300M Series C At $3B Valuation

LangChain said it raised $300 million at a $3 billion valuation, a major funding round tied to its push to help companies run, improve, and govern AI agents.

Key Takeaways

  • LangChain said it raised $300 million in a Series C at a $3 billion valuation
  • The round was led by existing investor CapitalG
  • LangChain said more than 7,000 organizations already rely on LangSmith
  • Workday uses LangSmith to reduce new agent deployment time from five months to under a day

LangChain announced on Nov. 13 that its Series C was led by existing investor CapitalG, with significant participation from new investors GIC and DFJ Growth and existing investors IVP and Sapphire Ventures.

The company said the funding will advance its mission to enable every company to own its intelligence through LangSmith, which it describes as a framework-agnostic platform to run, improve, and govern agents.

Also Read: AWS Uses Okta Logins To Stop AI Agents Going Rogue At Work

What LangChain Said The Platform Does

LangChain said companies should be able to choose the best models for their needs, control their data and infrastructure, and continuously improve their agents while maintaining governance to operate securely at scale.

The company said LangSmith provides that foundation across three pillars: Agent Runtime, Agent Improvement, and Agent Governance.

Customers And Usage Examples

LangChain said more than 7,000 organizations already rely on LangSmith, including startups such as Harvey, Rippling, and Listen Labs and Fortune 500 companies such as NVIDIA, Toyota, and Salesforce.

According to LangChain, Clay uses LangSmith to monitor hundreds of millions of agent runs per month and improve its agents. The company also said Workday uses LangSmith to run and govern agents across the organization, reducing the time to deploy a new agent from five months to under a day.

Three Pillars Of LangSmith

HeadHead
Agent RuntimeArchitecture and infrastructure to run agents reliably, including Agent Server, Sandboxes, Managed Agents, and Fleet
Agent ImprovementTools to test, monitor, and improve performance, including Observability, Evaluation, Engine, and Fine-Tuning
Agent GovernanceCentralized control over how agents use models, tools, and data through LLM and Tool Gateways

LangChain said Deep Agents, LangGraph, and LangChain give developers flexibility across models and control over how context is managed. It also said its LLM and Tool Gateways help teams manage model budgets and fallbacks, protect sensitive data, and govern tool access and authentication across teams and agents.

The company said it will share several new LangSmith capabilities on Nov. 20 at a special release event.

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