Managing long-running, stateful AI agents has historically presented significant challenges. With the LangGraph Platform now widely available, teams can efficiently move agents from concept to production without wrestling with infrastructure complexity. After a successful beta involving nearly 400 companies, LangGraph is poised to transform how organizations deploy and operate sophisticated agentic applications.
Solving Unique Infrastructure Challenges
Unlike traditional software, agent-based systems introduce new complexities. Agents may run for days or weeks, require asynchronous collaboration with humans or other services, and face sudden traffic spikes. These realities demand infrastructure that is both resilient and adaptable.
- Long-running tasks: Agents triggered by events or schedules need infrastructure that ensures durability and reliability.
- Asynchronous collaboration: Handling unpredictable human or agent inputs requires robust state management capabilities.
- Bursty workloads: Seamless scaling is essential to handle fluctuating demand in real-world environments.
Key Features of LangGraph Platform
The LangGraph Platform addresses these pain points with a suite of powerful capabilities:
- 1-click deployment: Launch agents directly from your GitHub repository in minutes.
- 30 flexible API endpoints: Customize user interactions and agent behaviors with ease.
- Horizontal scaling: Effortlessly manage both steady and spiky workloads.
- Persistence layer: Preserve agent memory, track conversation history, and support complex, multi-agent workflows.
- LangGraph Studio (IDE): Visualize, debug, and refine agent workflows in real time, complete with memory inspection and checkpoint editing.
Accelerated Development with Visual Workflows
LangGraph Studio empowers developers to inspect each step of agent execution, test edge cases, and rapidly debug intricate logic. Built-in checkpointing makes it simple to rewind and rerun specific workflow steps, streamlining both development and production troubleshooting.
Centralized Management for Modern Teams
As organizations scale their use of AI agents, centralized management is crucial. LangGraph’s unified dashboard, agent registry, and versioning (“assistants”) make it easy for teams to monitor, update, and reuse agent architectures. Enterprise-grade support for RBAC and workspaces ensures secure, collaborative operations. Industry leaders like Qualtrics are already leveraging LangGraph to power advanced AI workflows.
Flexible Deployment to Meet Any Need
The platform offers a range of deployment models to suit various operational requirements:
- Cloud (SaaS): Fully managed and integrated with LangSmith for rapid deployment.
- Hybrid: Combine SaaS control with a self-hosted data plane for sensitive data scenarios.
- Fully Self-Hosted: Maximum control for those needing data sovereignty and custom compliance.
- Developer Tier: Free self-hosting for experimentation or hobby projects (up to 100k nodes/month).
Each model is tailored to address compliance, security, and scale, making it easy for any team to adopt agent-based automation.
Take the Leap into Agentic AI
LangGraph Platform removes barriers to production, letting you concentrate on building powerful agent architectures rather than managing infrastructure. Whether you’re developing standalone agentic apps or integrating with LangChain and LangSmith, LangGraph provides the tools you need for scalable, reliable AI development. Explore the platform, select your deployment model, and experience the next evolution in agent-driven automation.
Source: LangChain Blog
LangGraph Platform: Simplifying Agent Deployment and Management at Scale