Move your team from Lindy to Make.

Both platforms support autonomous AI agents that go beyond fixed automation steps and can reason over goals, process data dynamically, and collaborate across tasks. Lindy's 'agent swarms' feature lets a single agent duplicate itself to run many tasks in parallel (e.g. sending hundreds of personalized emails simultaneously), while separate Lindy agents can hand work off to each other — one qualifies leads, another sends follow-ups, a third updates the CRM. Make's AI agents are built directly on the scenario canvas using the same module interface, and can adaptively choose execution paths, process files, query historical data, and integrate with 400+ AI models (OpenAI, Claude, Gemini, DeepSeek). To migrate multi-agent orchestration from Lindy to Make: map each Lindy agent's role and handoff conditions to a Make scenario with an AI agent module; use Make's routing and filtering to replicate handoff logic between scenarios. To migrate from Make to Lindy: convert AI agent scenarios into named Lindies with defined roles and goals, and set the trigger for each to match how the Make scenario was called.

Both platforms provide large libraries of pre-built app connectors that supply triggers and actions for automation workflows. Lindy advertises 'hundreds of popular tools' on its agent builder page, with coverage cited as 1,600–4,000+ apps including Gmail, Google Docs, Salesforce, HubSpot, Notion, GitHub, and Airtable; a generic Webhook connector extends coverage further. Make's library lists 3,520+ verified connectors spanning the same categories, plus an HTTP module for any REST API not in the catalog. When switching platforms, map each connected app on the source side to its counterpart on the destination side — most major apps (Gmail, Slack, HubSpot, Salesforce, Notion, Airtable) appear in both catalogs. Reconnect each integration by authorizing the app under a new connection in Make's connection manager, or under Lindy's integrations panel. Re-test triggers and actions after migration since field names and payload shapes can differ between the two implementations of the same connector.

Both platforms provide a mechanism for grounding AI agents in proprietary business data so that automated responses and decisions are based on real company content rather than generic LLM knowledge. Lindy's Knowledge Base lets agents query uploaded documents, connected sources (Google Docs, Notion, Intercom, websites), and individual files; every answer includes source annotations. Make's MCP Server exposes business systems and data sources to external AI models via the Model Context Protocol, while the MCP Client allows Make scenarios to pull context from external MCP-compatible services. To migrate a knowledge-grounding workflow from Lindy to Make: identify the data sources the Lindy Knowledge Base indexes (Google Drive, Notion pages, websites); in Make, connect those same sources via app modules (Google Drive 'Search Files', Notion 'Get Page') within the scenario, or expose them through the MCP Server so connected AI models can query them. To migrate from Make to Lindy: add the same data sources as Knowledge Base entries in Lindy's settings, enable 'Resync Knowledge Base Source' to refresh content, then instruct the Lindy agent to reference the Knowledge Base before answering.

Both platforms let non-technical users build multi-step automations visually without code. In Lindy, automations are AI agents ('Lindies') built by selecting a trigger event, giving natural-language instructions, and connecting apps via the agent builder. In Make, the equivalent is a 'scenario' — a canvas where you drag and drop app modules and connect them with wires to define data flow. To migrate from Lindy to Make: document each Lindy agent's trigger (e.g. 'new email received'), its action steps (e.g. 'draft reply', 'update CRM'), and any conditional logic; then recreate each step as a Make module on the canvas. To migrate from Make to Lindy: export or screenshot your scenario structure, recreate the trigger in Lindy's trigger picker, and replace each Make module with a Lindy action using natural-language instructions. Both products offer pre-built templates — check each marketplace before rebuilding from scratch.

Both platforms model automation as a trigger-then-action chain that can run on a schedule or in response to real-time events. Lindy calls its workflow builder 'Rails': a workflow starts from a trigger (e.g. 'email received', 'scheduled time') and then performs a sequence of actions across connected accounts, with support for conditional flows and multi-step processes. Make calls the equivalent a 'scenario': a scheduled or webhook-triggered chain of modules. To migrate from Lindy to Make: identify the trigger type (event-based or time-based), recreate it as a Make trigger module (Watch Email, Scheduled, or Webhook), then add an action module for each Lindy action step. To migrate from Make to Lindy: map each Make module to a Lindy action type in the Rails builder, set the matching trigger, and write natural-language instructions for any logic that was handled by Make's router or filter modules. Both platforms support branching (Lindy: conditional flows; Make: routers and filters).