What’s the difference between Lindy, Zapier AI and Make?

Lindy is an AI agent platform: you give an agent a goal, context and tools, and it reads the situation and decides what to do. Zapier (with AI Actions and Zapier Agents) and Make are deterministic automation platforms: you design the steps, and AI is one step inside an otherwise rule-based flow. The real question isn’t which tool has more features — it’s how much judgment you want to delegate.

This comparison is documentation-based — sourced from each vendor’s public pricing pages and product documentation — not first-party operator experience.

TL;DR

  • Lindy fits work you can’t write clean rules for: inbox triage, scheduling, lead qualification. The agent handles the gray area.
  • Zapier fits linear “when X happens, do Y” automations and has the broadest integration catalog. AI is an add-on step.
  • Make fits complex deterministic workflows — branches, loops, iterators — on a visual canvas, billed per credit.
  • Most solo builders end up with two layers: Lindy for judgment work, plus Zapier or Make for data movement.

How to think about the choice

  • Zapier’s and Make’s mental model: “When X happens, do Y.” You spell out every branch, filter and fallback. Runs are predictable. Anything fuzzy — “is this email from a real prospect or recruiter spam?” — has to become a rule, and rules miss cases.
  • Lindy’s mental model: “When X happens, here’s the goal — figure it out.” The agent reads the actual content, makes a call and acts. It’s flexible, but you can’t always predict edge-case behavior.

So the trade-off is predictability with brittleness (Zapier, Make) versus flexibility with unpredictability (Lindy). Judgment work favors the second; data movement favors the first.

Pricing structure

The live pricing cards on this page show current numbers from our daily tracker.

Lindy

Lindy starts with free trial credits, then sells per-seat plans (Plus, Pro, Max, plus Enterprise). Each seat adds a monthly credit allowance to a shared workspace pool, and bigger tasks use more credits. A high-volume agent — say, triaging hundreds of support emails a day — will push you up the tiers quickly. See the Lindy tracker for plan prices and history.

Zapier

Traditional Zaps are priced per task, and AI Actions count as additional usage. Zapier Agents, the newer agent product, has its own usage pricing on top. An AI-heavy Zap can burn through tasks faster than expected, because each action step that runs counts: a Zap with five action steps running 1,000 times a month is 5,000 tasks before any AI usage.

Make

Make bills per credit. Its free plan includes 1,000 credits a month, two active scenarios and a 15-minute minimum schedule interval; paid plans are Core, Pro and Teams. Most module actions use one credit, and some AI features use more. Iterators and aggregators are where costs surprise people: a scenario that processes 100 rows through 10 steps uses on the order of a thousand credits per run. Early filters and breakpoints keep this under control. See the Make tracker.

The work each tool is built for

Lindy: judgment work

  • Email triage: read incoming mail, classify intent, draft replies for low-stakes threads, escalate the rest
  • Calendar coordination: book meetings without a long back-and-forth
  • Lead qualification: read inbound forms, enrich from public data, decide whether to route to sales
  • Internal Q&A: answer team questions from internal docs

These tasks share one property: they don’t compress to rules cleanly. Forcing them through a rule engine means handling most cases and breaking on the ones that matter.

Zapier and Make: data movement with AI steps

  • Stripe payment lands → AI summary of the customer → CRM
  • New form submission → AI classifies intent → route to the right channel
  • Calendar event ends → AI writes a summary → Notion
  • Daily scrape → parse → store → notify

These are pipelines. AI produces text or a classification; it doesn’t decide what happens next. Zapier is the simpler pick when the pipeline is linear. Make is the better pick when it branches, loops over records or merges several sources.

Reliability and debugging

Zapier and Make: predictable

When a Zap or scenario fails, the run history shows the exact step and data that broke. You fix the rule and re-run. Make additionally lets you attach error handlers per module and re-run a single module with changed input.

Lindy: probabilistic

When an agent does something unexpected — replies to an email it should have escalated, books the wrong slot — you’re debugging judgment, not logic. You can read the agent’s reasoning, tighten its instructions and add guardrails, but “why did it decide that?” doesn’t always have a clean answer.

The practical rule: never give an agent authority over something you can’t unwind. Email replies and calendar bookings are recoverable; refunds and wire transfers are not. Start each agent in a low-stakes domain, watch it for a week, then expand its authority.

Integrations and escape hatches

  • Zapier has the largest integration catalog of the three, including a long tail of niche SaaS.
  • Make also covers a very large catalog and adds HTTP and webhook modules for any API, plus a Code app for custom logic (billed by execution time).
  • Lindy covers the common solo-founder stack — Gmail, Calendar, Slack, popular CRMs — but its catalog is smaller.

If your work depends on a niche industry tool, check Lindy’s integration list before committing. For the typical stack (Gmail, Calendar, Slack, Notion, Airtable, HubSpot, Stripe, Beehiiv), all three cover what you need.

When to pick which

Pick Lindy if:

  • Your bottleneck is repetitive judgment work (inbox, calendar, lead triage)
  • You want an agent that takes actions, not just suggests them
  • You can start with low-stakes agents and expand their authority over time

Pick Zapier if:

  • Your workflows are linear and AI is a single step inside them
  • You depend on niche SaaS integrations
  • You want the fastest path from idea to working automation

Pick Make if:

  • Your workflows branch, loop over records or combine several sources
  • You want a visual canvas with HTTP, webhook and code escape hatches
  • You’re comfortable building scenarios defensively to keep credit use predictable

The honest verdict

For solo founders running content, product and operations in parallel, Lindy is the better tool for the coordination layer — the hours that disappear into inbox triage, scheduling and follow-ups are exactly what an agent should take over. Zapier or Make is the better tool for the pipeline layer: Zapier for simple, linear automations; Make once the logic gets complex.

The layers don’t really compete. If you have to pick just one: choose Lindy if coordination work is what’s drowning you, and Zapier or Make if stitching tools together is.

You can check Lindy’s current pricing and Make’s current pricing on our tracker, including the history of past changes.