LangGraph
What is LangGraph?
LangGraph is LangChain's framework for developers and teams that need reliable AI agents with low-level control across complex workflows. It combines Observability, Evaluation, Deployment, Fleet, Sandboxes, Monitoring and alerting, and Online and offline evals, plus a REST API and one-click deployment. LangChain says it serves 6K+ active LangSmith customers and 5 of the Fortune 10, with named customers including Klarna, Monday.com, Podium, ServiceNow, C.H. Robinson, Fortune 500 Companies, Tech Startups, Open Source Community, and Max Agency. Plans run Free; Basic $29/month; Pro $99/month; Enterprise custom.
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At a glance
- LangGraph is best for AI engineers who need deterministic control over production agents.
- Free; Basic $29/month; Pro $99/month; Enterprise custom
- 30 days, no credit card
- Yes — REST API for external integrations and platforms; the vendor describes it as reliable.
What does LangGraph do?
LangGraph is LangChain's framework for building reliable AI agents with low-level control. It is aimed at developers and teams that need production-grade orchestration rather than a simple prompt wrapper, especially when agents must behave deterministically across complex workflows. The product sits alongside LangSmith and LangChain in the broader platform. LangGraph supports agent development with observability, evaluation, deployment, Fleet, and Sandboxes. The platform also includes monitoring and alerting, online and offline evals, and one-click deployment, while the enterprise offering adds hybrid and self-hosted hosting options so data stays in your VPC. LangChain says it serves 6K+ active LangSmith customers, 100M+ monthly open source downloads, and 5 of the Fortune 10; named customers include Klarna, Monday.com, Podium, ServiceNow, and C.H. Robinson.
Why use LangGraph?
- Low-level control makes it a fit for deterministic agent workflows that need more than a simple chain abstraction.
- Observability, evaluation, deployment, Fleet, and Sandboxes live in one platform instead of separate tools.
- Enterprise hosting options include hybrid and self-hosted setups, which helps with VPC and data-residency requirements.
- Monitoring and alerting are built into the agent lifecycle, so teams can catch regressions without stitching together extra tooling.
- LangChain's ecosystem is already widely used, with 100M+ monthly open source downloads and 6K+ active customers.
Who is LangGraph for?
- AI engineers who need deterministic orchestration for complex agent workflows.
- Platform teams who want observability and evaluation across agent lifecycles.
- Enterprise developers who need hybrid or self-hosted deployment options for data residency.
- Product teams who want to ship agents with monitoring, alerting, and feedback loops.
What are LangGraph's key features?
Observability
Inspect traces to see exactly what agents are doing, which helps teams debug execution paths and understand failures across runs.
Evaluation
Score agent behavior with online and offline evals so teams can compare outputs, catch regressions, and improve performance before release.
Deployment
Ship agents in production with one-click deployment and production-ready infrastructure, reducing the gap between testing and live traffic.
Fleet
Manage agents for the whole company, with support for multiple agents and workspace-level coordination across teams.
Sandboxes
Run agent-generated code safely in isolated environments, which helps teams test risky actions before they touch production systems.
Monitoring and alerting
Track agent health and receive alerts when behavior changes, so teams can respond before issues affect customers or workflows.
Online and offline evals
Compare live and offline agent performance using trace data, giving teams a way to validate changes against real execution patterns.
Up to 5k base traces / mo, then pay-as-you-go
Start with 5k base traces per month and expand as usage grows, which keeps trace ingestion aligned with actual agent activity.
What are LangGraph's use cases?
Production agent orchestration
AI engineers use LangGraph to build production agents with low-level control, then pair Observability and Evaluation to inspect traces, score behavior, and tighten reliability before release.
Enterprise deployment control
Enterprise developers use LangGraph to deploy agents with Deployment and Fleet, then rely on Sandboxes and monitoring to test changes safely and keep production behavior predictable.
Lifecycle monitoring for teams
Platform teams use LangGraph to watch agent runs in Observability, trigger Monitoring and alerting, and compare Online and offline evals so regressions surface before customers feel them.
How does LangGraph work?
- Build your agent in LangChain frameworks, then connect it to LangGraph for low-level control over execution paths and deterministic behavior.
- Open LangSmith Observability to inspect traces, review what each agent step is doing, and spot failures in real time.
- Run Evaluation with online and offline evals, then use feedback to improve prompts, routing, and agent decisions before wider rollout.
- Deploy through LangSmith Deployment or Fleet, using one-click deployment and monitoring and alerting to keep production agents stable.
- Use Sandboxes to test agent-generated code safely, then iterate on designs and ship updates with confidence.
How much does LangGraph cost?
Basic
$29/month- Core features
- Community support
Pro
$99/month- All basic features
- Integrations
- Priority support
Enterprise
Custom- All Pro features
- Customized solutions
- Dedicated support
Frequently asked questions
What is LangGraph used for?
LangGraph is used to build reliable AI agents with low-level control. LangChain positions it for production agents that need determinism, and it sits within the broader LangSmith/LangChain platform for development, deployment, and monitoring.
Does LangGraph have observability tools?
Yes. LangSmith Observability lets you inspect traces and see exactly what your agents are doing. That makes it easier to debug execution paths, understand failures, and review behavior across runs.
Can I evaluate agent performance?
Yes. LangSmith Evaluation supports both online and offline evals, so teams can score agent behavior, compare outputs, and improve performance before and after deployment.
Is there a free plan?
Yes. LangChain offers a Free plan, and the vendor also says there is a 30-day free trial. The free tier is aimed at getting started with basic agent development.
Does LangGraph offer an API?
Yes. LangSmith provides a REST API for integrating with external systems and platforms, and the vendor describes it as a reliable API for those integrations.
Can LangGraph be self-hosted?
Yes, on Enterprise. The pricing page says Enterprise includes alternative hosting options, including hybrid and self-hosted, so data doesn't leave your VPC.
What support do you get?
Support depends on plan. The vendor lists community support on lower tiers, priority support on Pro, and dedicated support plus a support SLA for Enterprise.
Which customers use LangChain?
LangChain cites customers such as Klarna, Monday.com, Podium, ServiceNow, and C.H. Robinson. The site also says it has 6K+ active LangSmith customers and 5 of the Fortune 10.
Editor's read
Check whether your workload needs the Enterprise hybrid or self-hosted hosting options for VPC data residency. If so, confirm that requirement before comparing only the Free, Basic $29/month, and Pro $99/month tiers.
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