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LangChain$500 in LangSmith credits for Startups

$500 in LangSmith credits

Framework for building LLM-powered applications — chains, agents, RAG, and tool use with any model provider.

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Deal Highlights

$500 in LangSmith credits
Deal Value
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AI Tools
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What Is LangChain?

LangChain is the framework for building applications powered by large language models — providing the abstractions, tooling, and infrastructure for chains (sequential LLM calls), agents (LLMs that use tools), RAG (retrieval-augmented generation), and memory (conversation context). LangSmith, the companion platform, provides tracing, evaluation, and monitoring for LLM applications in production.

For AI startups building complex LLM-powered features, LangChain provides the development framework and LangSmith provides the production observability — together covering the full lifecycle from prototype to production.

What''s Included

  • $500 in LangSmith credits — LLM application tracing, prompt evaluation, dataset management, production monitoring, and regression testing for AI applications.

Key Features

  • LangSmith tracing: See every LLM call, tool use, and retrieval step in your AI pipeline
  • Prompt evaluation: Test prompts against datasets and score outputs for quality
  • Dataset management: Build test datasets for evaluating LLM application quality
  • Production monitoring: Track latency, cost, and quality metrics for production AI features
  • Regression testing: Ensure prompt changes don''t degrade output quality

Who Is This Deal For?

Early-Stage Startups

Seed and pre-seed companies looking to move fast without overspending on tools.

Growing SaaS Teams

Series A+ companies scaling their stack and optimizing software costs.

Solo Founders

Indie hackers and bootstrapped founders who need enterprise tools at startup prices.

Get $500 in LangSmith credits off LangChain

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!Eligibility Requirements

AI startup building LLM applications

Frequently Asked Questions

Everything you need to know about this startup deal.

LangChain is an open-source framework for building LLM applications. It provides abstractions for chains (sequential calls), agents (tool-using LLMs), RAG (search + generation), and memory. Available for Python and JavaScript/TypeScript.