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Quick reference: match your use case to the right Lyzr product and capability.
Use CaseBest ProductKey Capability
Chat assistant with memoryAgent StudioCognis memory, multi-turn sessions
Document Q&AAgent StudioClassic KB, RAG, citation output
Database query via natural languageAgent StudioSemantic Model, Text-to-SQL
Complex relationship queriesAgent StudioKnowledge Graph (Neo4j)
Multi-step business workflowAgent StudioSuperFlow or Manager Agent
Voice bot / phone agentAgent StudioVoice Agents (Realtime/Pipeline)
Full-stack AI app from a promptArchitectText-to-App, agent orchestration
Programmatic agent creationADKPython/TypeScript SDK, full control
Add AI to an existing productAPIREST endpoints, any language or stack

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Chat agents

Conversational agents answer questions, handle requests, and maintain context across a conversation. What’s required: a role, a goal, and instructions; a supported LLM (GPT-4o, Claude, Gemini, and others). Optionally, enable Cognis for cross-session memory so the agent remembers past conversations with the same user. Example prompt: Role 
You are a senior support specialist for [Company].
Goal 
Resolve billing and account queries accurately.
Instructions 
Always ask for the account ID before pulling specific details. Be concise. Escalate to a human agent if the issue involves a refund over $500.

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Knowledge search and document Q&A

Knowledge agents answer questions grounded in your organization’s documents, PDFs, URLs, or databases. What’s required: a Classic Knowledge Base with uploaded documents, RAG retrieval enabled on the agent, and optionally citation output mode. Supported sources: PDF, DOCX, TXT, CSV, websites (live crawl or snapshot), SharePoint, S3, Google Drive, Notion, Confluence. Use a Knowledge Graph instead when your data has complex relationships (org charts, product dependencies, compliance rules) where entity connections matter as much as the text. Use a Semantic Model instead when your data lives in a relational database and users need to query it in plain English.

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Database query (Text-to-SQL)

The Semantic Model translates natural-language questions into SQL queries against your structured data. What’s required: a Semantic Model connected to a database (PostgreSQL, MySQL, BigQuery, Snowflake, and others), plus a schema definition covering tables, columns, and business glossary. By default, the Semantic Model generates SELECT queries only (read-only). Write access is configurable for internal tooling.

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Multi-step workflows

Workflows automate sequences of actions: fetch, analyze, decide, act. Lyzr provides two orchestration modes: Manager Agent is dynamic. The manager agent reads the task and routes it to sub-agents based on context. Use Manager Agent for conversational, branching logic where the execution path varies by input. SuperFlow is deterministic. You define a directed acyclic graph (DAG) of nodes (LLM calls, HTTP requests, code, conditionals, human approvals) and the workflow runs exactly the steps you defined. Use SuperFlow when execution order must be guaranteed, when you need exactly-once side effects, or when the workflow touches financial or compliance-sensitive systems.

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Voice agents

Voice agents handle phone calls, voice assistants, and real-time speech interfaces. Two engine modes:
  • Realtime: sub-500ms latency, streaming ASR + TTS + LLM. Best for live phone calls.
  • Pipeline: standard latency, higher accuracy. Best for asynchronous voice UX.
Telephony integrations: Twilio, Telnyx, Plivo (inbound and outbound calling). What’s required: Voice Agent configuration, telephony credentials, and optionally a Knowledge Base for call scripts.

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Full-stack AI apps (Architect)

Architect builds a complete, deployed web application from a plain-English description. What Architect generates: a frontend UI (React/Next.js), a multi-agent backend wired together, API endpoints, and auth and database layers if requested. Use Architect when you want a working product rather than just an API, for demos, customer-facing tools, or internal dashboards.

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Programmatic agents (ADK)

The Agent Development Kit (ADK) lets you build and manage agents from Python or TypeScript code. Use the ADK when you are integrating Lyzr into an existing service, building CI/CD pipelines that create or update agents programmatically, or need custom retry logic and runtime control.

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API integration

Call any Lyzr agent from any language or stack using the REST API. Use the REST API when your application is in Node, Go, Ruby, Java, PHP, or any language that speaks HTTP, or when you are integrating into an existing API gateway or service mesh without an SDK.