LangChain: Agent Frameworks

Founded 2022|San Francisco, CA|51-200 people|Open Source

What is LangChain?

LangChain is the most widely adopted framework for building LLM-powered applications and AI agents, founded in 2022 by Harrison Chase. The company provides an open-source Python and TypeScript framework with abstractions for chains, agents, tools, memory, and retrieval that make it easy to compose complex AI systems.

LangGraph, its agent orchestration layer, enables building stateful, multi-actor workflows with human-in-the-loop capabilities. LangSmith provides tracing, evaluation, and monitoring for LLM applications in production. The LangChain ecosystem is the largest in the AI application development space, with the company reaching $16M in revenue and 1,000 customers by 2025.

Backed by $260M in total funding at a $1.25B valuation, LangChain has grown to 199 employees and is headquartered in San Francisco. The company serves as the de facto orchestration layer for teams building production AI applications.

Key features

Core capabilities this platform advertises.

LangChain Expression Language (LCEL)
LangGraph for stateful multi-agent workflows
1000+ integrations
LangSmith observability companion
Python and JavaScript SDKs

Strengths and tradeoffs

What this tool does well, and the limitations to keep in mind.

Pros

Largest ecosystem and community in AI application development
Comprehensive abstractions for chains, agents, tools, and memory
LangSmith provides production-grade tracing and evaluation
LangGraph enables complex stateful multi-actor agent workflows
Extensive integrations with LLM providers, vector stores, and tools

Cons

Steep learning curve for advanced configurations and LangGraph
High total cost of ownership for complex deployments
Rapid API changes can break existing implementations
Trace pricing can escalate quickly at scale ($2.50-$5.00 per 1K traces)

Plans & pricing

What's included in each plan, and how the tiers compare.

Developer

Free

Monthly

5K traces/month
14-day retention
1 seat
1 workspace
1 agent with 50 runs

Plus

$39/seat

Monthly

10K base traces/month
Up to 10 seats
3 workspaces
1 free dev-sized deployment

Enterprise

Custom

Annual

HIPAA BAA
SOC 2 Type II
Self-hosting options
Custom trace limits
Dedicated support

View official pricing page

Common use cases

Developers building complex LLM applications who need a comprehensive orchestration framework

Building RAG applications
Multi-agent orchestration with LangGraph
Tool-using conversational agents
Document processing pipelines
Complex chain-of-thought workflows

Using LangChain with Respan

Respan integrates with LangChain to provide deep observability into LLM chains and agent workflows. By monitoring LangChain traces alongside Respan evaluation metrics, teams can identify performance bottlenecks, track prompt effectiveness, and optimize agent behavior across production deployments.

Monitor LangChain agent execution traces in real-time
Evaluate LLM output quality across chain steps
Track token usage and cost across LangChain workflows
Compare prompt variations within LangChain pipelines

Run LangChain in production with Respan

10KFree traces/mo

1,000+Models

5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Best LangChain alternatives & competitors

Top companies in Agent Frameworks you can use instead of LangChain.

OpenClaw

Connects to 50+ channels — WhatsApp, Telegram, Slack, Discord, Signal, iMessage, Teams