For business teams without engineering resources, Lindy is a no-code platform for building custom AI agents that automate routine business tasks and workflows, replacing manual busywork with agents anyone can configure.
Presence & Market Position
#15 of 22
Orchestrators & Agentic Workflow
▼ 16 60-day move
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Lindy positions itself as a no-code way to build custom AI agents: an interface any business team can configure to replace manual busywork, spanning an AI executive-assistant experience for email, scheduling, and meeting notes to broader agent workflows for sales, support, and operations. In practitioner conversation, it holds a steady presence inside roundups of agentic-workflow and orchestration tools, named alongside category peers as a go-to option for teams assembling an agent stack. Coverage extends to reviews and pricing breakdowns for people evaluating the product, and its own disclosed operating decisions, such as a change in which underlying AI model it runs on, have been picked up as data points in wider debates about AI model economics.
Relevance AI
Dust
Vellum
Inngest
CrewAITruemed, Pragmatic, Ankor, Tiddle, Seven Zero Ventures, Interlaced
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Business Profile
Lindy was founded in 2023 by Flo Crivello, a former Uber product manager who had previously started the virtual-office company Teamflow. The company has raised $49.9M in venture funding and reported $5.1M in ARR in 2024, alongside a team that has grown to roughly 50 people. Lindy started by pitching itself broadly as an AI teammate for business operations and has since sharpened that pitch around a flagship AI executive-assistant product, handling email, scheduling, and meeting follow-up, while keeping the underlying no-code agent-builder available for teams that want to configure their own workflows. Customers cited alongside the platform include Truemed, Pragmatic, and Ankor.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Lindy publishes developer-facing docs covering HTTP request and webhook triggers, an OpenAPI spec, and code execution inside workflows, alongside offline evals for testing agent behavior before it ships. The company has used that evals process in public: switching its underlying model to cut inference cost after running the alternative through internal testing and retention tracking. Recent template additions, including a Slack-based agent and a personalized daily-briefing agent, show the library still expanding.
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