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Introducing Lyzr

Lyzr is an agent framework with an agentic approach to building generative AI applications. Its highly configurable agents come with pre-built RAG pipelines, safe and responsible features, allowing you to build and launch enterprise ready agents in minutes. Agents can be built and tested on Lyzr’s Studio or can be directly used with the help of the REST APIs that are available. With Lyzr, you can build chatbots, knowledge search, data analysis, RAG-powered apps, and multi-agent workflow automation with minimal effort.

  • RAG pipelines
  • Safe and responsible features

All this allows you to build and launch enterprise-ready agents in minutes. Agents can be:

With Lyzr, you can create chatbots, knowledge-search tools, data-analysis assistants, RAG-powered apps, and multi-agent workflow automations with minimal effort.

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Lyzr’s Safe and Responsible AI Architecture

Lyzr’s framework incorporates our proprietary Safe and Responsible AI features directly into the agent inference flow. Every agent you build benefits from:

  • Input filtering and sanitization
  • Bias and toxicity checks
  • Privacy protections
  • Audit-ready logging

Ensuring high accuracy, compliance, and traceability for all results.

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Who Is Lyzr For?

  • Developers
    You’ll love the simplicity of the framework and rapid prototyping capabilities.

  • CTOs & CPOs
    Seamlessly integrate generative AI into your products with configurable agents—minimal learning curve for your in-house team.

  • CIOs
    Introduce GenAI enterprise-wide with our Safe and Responsible AI architecture, plus use the AI Management System (AIMS) to manage agents, monitor logs, and train your team via the in-built Lyzr Academy.

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Orchestration Modes

Lyzr provides two distinct orchestration paradigms:

  • Directed Acyclic Graph (DAG) Orchestration
    Ideal when your workflow has well-defined, dependent tasks.

    • Ensures all dependencies are resolved in order
    • Provides full traceability

  • Managerial Orchestration
    Suited for dynamic workflows where tasks evolve at runtime.

    • A “manager” agent decomposes goals into subtasks
    • Handles retries, branching, and fault recovery
    • Adapts to changing requirements on the fly