Lyzr
Low-code agent framework for building reliable, enterprise-grade AI agents with built-in guardrails.
Lyzr is an enterprise platform for building and running AI agents, aimed squarely at the problem that stalls most corporate AI projects: getting agents out of a sandbox and into governed, reliable production. Rather than a single chatbot, Lyzr frames its goal as an entire AI workforce, networks of specialized agents operating across a company's systems, and positions itself as the infrastructure and control plane that lets organizations deploy, monitor, and govern those agents at scale.
Teams build on Lyzr through a low-code Agent Studio and SDK, or through Architect, where you describe a workflow in plain English and the platform assembles the agent, its logic, its integrations, access controls, and a usable interface. A library of pre-built agent blueprints spans common enterprise functions, from sales and marketing to HR, finance, banking, insurance, and customer service, so teams can start from a proven template rather than from scratch. For more complex work, an orchestration layer lets multiple specialized agents collaborate on end-to-end, multi-step processes, sharing context and delegating tasks across departments.
What distinguishes Lyzr from a pure developer toolkit is its emphasis on the controls enterprises need to trust agents in production. A simulation engine lets teams test an agent before it ships, full observability traces every run in real time, and responsible-AI guardrails check outputs for hallucinations and personally identifiable information before they reach a user. Layered on top are access and governance controls over who can see and modify each agent, plus audit logging and compliance features that make every action and decision traceable, which matters most in regulated industries.
Lyzr is deliberately model-agnostic, so enterprises can run agents on models from different providers and swap them without rewriting, avoiding lock-in to a single vendor. It also supports deployment in a company's own private cloud or on-premises, with locally deployable SDKs and private APIs, addressing data-privacy, compliance, and latency requirements while letting the customer retain ownership of its data and the agents it builds. The result is a platform pitched less at experimentation and more at operationalizing AI across an organization.
Vendor details
Canonical URL
https://www.lyzr.ai
Category
Agent builder
Company status
independent
Use cases & customers
Target customers
Deployment options
In practice
Your AI agent works in a demo but stalls before production because of governance and compliance. Lyzr adds a simulation engine, observability, guardrails for hallucinations and PII, and audit logging so the agent can be trusted live.
You want to automate work across HR, finance, and support without building each agent from scratch. Lyzr's blueprint library gives you pre-built agents per function, and an orchestration layer lets them collaborate on multi-step processes.
Regulatory rules mean your data can't leave your environment. Lyzr deploys in your private cloud or on-premises with private APIs, runs on the model of your choice, and lets you keep ownership of your data and agents.
Capability coverage
10.5 / 14 capabilities · 75%
| Integrations & Tool CallingAgent Features research report + JSON Feature Rubric | Full |
|---|---|
| Workflow OrchestrationAgent Features research report + JSON Feature Rubric | Full |
| Knowledge Grounding & RAGAgent Features research report + JSON Feature Rubric | Full |
| Human Oversight & GuardrailsAgent Features research report + JSON Feature Rubric | Full |
| Security, Identity & GovernanceAgent Features research report + JSON Feature Rubric | Full |
| Observability & AuditabilityAgent Features research report + JSON Feature Rubric | Full |
| Memory & State PersistenceAgent Features research report + JSON Feature Rubric | Unable to verify |
| Deployment & Data ResidencyAgent Features research report + JSON Feature Rubric | Full |
| Prebuilt Agents, Templates & PacksAgent Features research report + JSON Feature Rubric | Partial |
| Triggers & Channel CoverageAgent Features research report + JSON Feature Rubric | Partial |
| Model Flexibility & RoutingAgent Features research report + JSON Feature Rubric | Full |
| APIs, SDKs & MCP ExtensibilityAgent Features research report + JSON Feature Rubric | Partial |
| Testing, Debugging & OptimizationAgent Features research report + JSON Feature Rubric | Full |
| Browser & Computer UseAgent Features research report + JSON Feature Rubric | Unable to verify |
Recent platform changes
Lyzr open-sourced SivaClaw, the AI agent it initially built to support its own Series B fundraising process. The agent runs on GitAgent using the OpenGAP protocol and handles automated workflows like investor communication, diligence material organization, and company briefings.
View sourceLyzr released the Agent Improvement Engine, which analyzes live production traces to detect quality issues in deployed agents. Its Agent Hardening layer spots failure patterns and auto-generates recommendations to revise an agent's instructions or goals.
View sourceLyzr published a finance-ops case study on payment-receipt verification automation, including portal, email, and WhatsApp intake, payment-method guardrails, API connectivity, and manual exception routing.
View sourcePricing
From $19/mo + per-run ($0.08 Cloud/$0.03 VPC) + LLM
hybrid
Included quota
Community (free): 500 credits, 1 builder license, base models, 100MB knowledge base, 7-day logs, unlimited agents + users. Starter ($19/mo): ~2,000 credits/mo, 1 license, 7-day logs, more KB. Pro ($99/mo, $79 annual): 10,000 credits/mo, 1 license, all standard/leading models, a few Super Agents, 1GB KB, 3-month logs. Enterprise Cloud (custom): unlimited credits, 50+ builder licenses, premium/custom models, 120GB KB, 1-year logs, 24/7 support, 10 Super Agents, 48-hr integration SLA, Agent Entitlement Policy, Org General Intelligence, Lyzr Build Services (5 agents). On-Premise (custom): unlimited credits, custom licenses, logs retained forever, 20 Super Agents. (Some listings also show mid Teams $999 / Organization $2,499 tiers.)
What is public
Lyzr (lyzr.ai - enterprise agentic-AI platform; Agent Studio no-code/low-code builder on its 'safe & responsible AI' Agent Framework) publishes transparent low-end tiers, notable in a quote-heavy category: Community free ($0, 500 credits, 1 license, 100MB KB, 7-day logs), Starter $19/mo (2,000 credits), Pro $99/mo ($79/mo annual; 10,000 credits/mo, super agents, 1GB KB, 3-month logs), and custom Enterprise/On-Prem (unlimited credits, 50+ licenses, 24/7 support, on-prem/VPC). CRITICALLY, production is billed SEPARATELY per agent run - $0.08/run on Lyzr Cloud, $0.03/run on VPC/on-prem - plus LLM token pass-through; the subscription is a small part of the real bill.
Billing mechanics
Three cost layers: (1) a flat SUBSCRIPTION tier with a bundled monthly CREDIT allowance (500 Community / 2,000 Starter / 10,000 Pro / unlimited Enterprise) - credits meter build-time + premium operations (knowledge-base ops, tool calls, specific features); (2) PER-AGENT-RUN production charges billed on top - $0.08/run on Lyzr Cloud, $0.03/run on Lyzr VPC/on-prem; (3) LLM TOKEN costs passed through at provider rates (OpenAI/Anthropic/Google/Bedrock), accruing directly to the model provider. Annual billing gives two months free (Pro $99 to $79/mo). Extra credits top up one-time at $0.01/credit ($10/1,000 up to $5,000/500,000).
Cost watchouts
The subscription is the SMALL part - production agent runs ($0.08/run Cloud) + LLM pass-through dominate at scale (1,000 runs/day on Cloud ~ $80/day ~ $2,400/mo, dwarfing the $99 Pro sub; a 20+-agent workflow ~ $1.02/successful run on-prem); LLM token costs 'frequently exceed the platform fee'; credits get burned by trial-and-error when docs are unclear (a common complaint); VPC/on-prem cuts the per-run rate to $0.03 but is Enterprise-gated; budget 5-10x the subscription
Variable cost rationale
High and multi-layered - flat subscription is minor; the real variable cost is per-agent-run production billing ($0.08 Cloud / $0.03 VPC-on-prem) scaling with invocation volume, PLUS LLM token pass-through (often the largest line), PLUS credit consumption for KB/tool/premium ops; deployment choice (Cloud vs VPC/on-prem) materially changes per-run economics
Additional watchouts
Runtime (per-agent-run) + LLM pass-through are the real bill - the cheap $19/$99 sub is a 'rounding error' at production scale (budget 5-10x); documentation gaps cause trial-and-error that wastes credits (top complaint); setup can feel heavy/complex for small teams; aggregator pricing is a mess (verify on official docs); thin public review/Reddit presence
Overage / add-ons
When monthly credits run dry, buy one-time top-ups at a flat $0.01/credit ($10 for 1,000, up to $5,000 for 500,000). Production agent runs are billed as you go ($0.08 Cloud / $0.03 VPC-on-prem per run) - there's no cap; LLM token usage bills directly from your model provider. Higher tiers raise credit bundles and lower effective run economics (VPC/on-prem at $0.03 vs Cloud $0.08).
Sales call required
Mixed (some tiers require a call)
Free / trial
Free
Lowest paid plan
$19/mo
Commercial notes
Positions Agent Studio as the first agent framework with safe/responsible AI natively in the core; strong in regulated verticals (BFSI, insurance, healthcare, IT services); pre-built agentic blueprints + multi-agent orchestration; 75% of customers run 2+ agents; NTT Data case study cites 70,000+ hours saved. NY-based; raised an $8M Series A (Rocketship.vc + Accenture Ventures, 2025) then a $14.5M round led by Accenture (March 2026) at a ~$250M valuation; 400+ enterprise customers (Accenture, AWS, Hitachi Energy, Publicis, AirAsia). Competes with Relevance AI, CrewAI, StackAI, Agentforce; builds agents - NOT a contact-data provider (pair with an enrichment layer for B2B data).
Key ambiguities
Subscription tiers are clear (Community/$19/$99/Enterprise) but aggregators show wildly conflicting numbers ($19 vs $99 vs $999 Teams vs Rs 143,928 vs $2,499 Organization) due to currency/outdated listings; Pro credit allowance is cited as 10,000/mo (= 120k/yr); some sources list intermediate Teams ($999) / Organization ($2,499) tiers between Pro and Enterprise; what exactly consumes 'credits' vs triggers a billable 'agent run' isn't fully itemized
Cancellation / refund
Community free (no card); Starter/Pro self-serve monthly or annual (annual = two months free, Pro $99 to $79/mo); one-time credit top-ups ($0.01/credit, no subscription); Enterprise/On-Prem custom-contracted (50+ licenses, build services); BYOM and on-prem keep data/IP in your environment
Support SLA / resale
Email/help-desk + chat + knowledge-base support (lower tiers); Enterprise adds 24/7 support, a 48-hr custom-integration SLA, dedicated build services, SSO, RBAC, audit logging, Human-in-the-Loop; SOC2/GDPR/ISO 27001 compliant; model-agnostic (OpenAI/Anthropic/Google/Bedrock + BYOM); deploy on Lyzr Cloud, VPC, or on-prem; native 'safe & responsible AI' (Hallucination Manager, PII redaction); integrates with Slack/Salesforce/Snowflake/Pinecone/Perplexity/etc.
Missing data
Aggregators show conflicting numbers (currency/outdated); intermediate Teams ($999)/Organization ($2,499) tiers appear in some listings; exact credit-vs-run consumption rules aren't fully itemized. Seed 'Community free (500 credits); Starter $19/mo (2k); Pro $99/mo (10k; $79/mo AE); Enterprise custom' is accurate for the subscription tiers - but the seed OMITS the key cost driver: production is billed per agent run ($0.08 Cloud / $0.03 VPC-on-prem) on top, plus LLM token pass-through, plus $0.01/credit top-ups.
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