Lyzr is an enterprise AI agent platform for building, governing and running agents in Lyzr's cloud, your own cloud or on-premises, sold as annual modules.
Lyzr gives large organisations one place to design AI agents, move them into production and keep them under common rules. The problem it targets is agent sprawl: agents built by different teams on different frameworks, running without shared controls. The platform belongs to Lyzr, Inc., an independent Delaware corporation based in Jersey City, New Jersey. Work starts in Agent Studio, the web app at studio.lyzr.ai. Agent Studio is the builder, where knowledge bases ground answers in uploaded files, web pages and live sources. Custom tools come from OpenAPI specs, and any MCP server can be connected. SuperFlow lays agents, model calls, code, conditionals and human approval nodes on a drag-and-drop canvas, and its runs resume where they paused. A Manager Agent routes tasks to specialised agents, while guardrail policies screen inputs and outputs for PII and brand risk. OpenTelemetry traces, version snapshots and Agent Eval test suites cover operation and release, and Opencontroller, Open Cowork and Openfinetuner extend the platform to governance, employee agents and model training. The fit is an enterprise where the CIO, the CISO, risk teams and operations all have a say in how agents reach production. Engineers who prefer code get the Python ADK, with Pydantic-validated outputs, beside the visual tools. Developers build and test on the Community plan without paying, because agents in development draw nothing. Paying customers buy modules on annual prepaid contracts, and production agents are metered in agent-months rather than seats, so user counts are unlimited. A common first project is an internal assistant that answers staff questions from company documents and intranet pages. Teams then chain agents into workflows that call outside systems over HTTP, wait for a manager's approval and pick up days later. Each agent exposes its own REST endpoint and can start from a webhook, so an outside system can hand it work directly. Companies already running agents on Microsoft Copilot, AWS Bedrock or LangGraph use Opencontroller to bring them under one set of policies. Where data cannot leave the building, the same agents run inside the customer's own VPC or on Lyzr Optimus hardware.
Pricing
View plans-
Build, test and experiment (Community)
Free
- Free forever
- Build and test agents in Agent Studio
- Agents in development never use agent-months
- An agent moved into production draws agent-months, which only a paid module supplies
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Control your agents
$250,000 per year
$250,000 per year, annual and prepaid, no monthly option
- Powered by Opencontroller
- Unlimited agents and users
- Covers agents built on Copilot, Bedrock, LangGraph and more
- Basecode for coding agents adds $250,000 a year
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Put agents to work
$250,000 per year
$250,000 per year for a block of 150 agent-months ($1,667 each), annual and prepaid
- Powered by Agent Studio, Architect and SuperFlow
- About 12 agents in production for a year per block
- 2 forward-deployed engineers in year one
- Any number of agent-months from 150; each extra agent-month costs $2,000
- 151 agent-months come to $252,000
- Agent-months drawn per agent depend on its tier and run volume; Heavy agents are customized for enterprises
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AI for every employee
$100,000 per year
$100,000 per year, annual and prepaid, no monthly option
- Powered by Open Cowork
- Unlimited users
- Personal agents are included at no charge
- Team agents shared in a workbench use agent-months
Features
- Included: Visual agent workflow canvas
- Included: Custom tool and function definitions
- Included: Model provider choice per agent
- Included: Retrieval-augmented knowledge bases
- Included: Multi-agent handoff and delegation
- Included: Conversation state and checkpointing
- Included: Structured output schema validation
- Included: Input and output guardrails
- Included: Human-in-the-loop approval steps
- Included: Built-in execution tracing
- Included: Prompt versioning in the builder
- Included: Agent evaluation and test suites
- Included: MCP server support
- Included: Webhook and event triggers
- Included: Code-first SDK
- Included: Deploy an agent as an API endpoint
- Not included: Embeddable agent chat widget
- Included: Self-hosted agent runtime
Additional Features
- Agent Studio no-code agent builder
- SuperFlow drag-and-drop automation canvas
- SuperFlow human approval nodes
- Durable SuperFlow runs that resume after a pause
- Manager Agent routing work to specialised agents
- Knowledge bases from files, text, URLs and live sources
- Custom tools from OpenAPI specs
- Connections to any MCP server
Best for
- Enterprises moving AI agents from pilots into production
- CIOs and CISOs governing agents built on several frameworks
- Risk and compliance teams that need guardrails and approval steps
- Engineering teams that want to define agents in Python code
- Organisations that must keep agent data inside their own VPC or data centre
- Developers prototyping agents before committing to a production contract
- Companies that want to fine-tune and own an open-weight model
- Organisations buying software on annual prepaid enterprise contracts
Use cases
- Building an internal assistant over company documents and web pages
- Chaining agents, tools and HTTP calls into one automation
- Pausing a workflow until a person approves the next step
- Governing agents built on Copilot, Bedrock or LangGraph from one control plane
- Running agents inside a private VPC or on-premises
- Starting an agent from an outside system's webhook
- Calling a finished agent from another application over REST
- Testing an agent against generated cases before release
- Rolling an agent back to an earlier saved configuration
- Giving every employee personal agents and shared team agents
- Fine-tuning an open-weight model the company keeps
Screenshots & Videos
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