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Lindy vs Make
A plain-English comparison to help you choose between them.
Delegation against construction, again with a twist of scale: Lindy hands a described job to an agent, Make hands you a canvas to build the process yourself. Pick Lindy when the work is a recurring administrative loop with acceptable variation, inbox triage, scheduling, CRM upkeep, described in sentences and run on triggers. Pick Make when the automation has real logic and real volume, branching, iteration and error paths drawn across hundreds of apps, priced by credits so sophisticated flows stay affordable, with in-scenario agents where a step needs judgement.
Side by side
- Summary
Lindy is a platform for building AI agents that do real work across your existing tools.
- Best for
- Delegating whole jobs such as inbox triage or meeting scheduling to an agent
- Building agents in plain language without code or flowcharts
- Keeping CRM records current from email and meeting activity
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Hosted service
- Data
- Agents hold live access to email, calendar and connected tools; grant scopes per agent, per job.
- Summary
Make is visual automation with engineering sensibilities: scenarios built on a canvas where branching, loops, error handling and data transformation are first-class, connecting thousands of apps at credit-based pricing that undercuts the per-task platforms at volume.
- Best for
- Branching, loops and error handling built visually
- High-volume automation at credit-based pricing
- Reusable AI agents inside scenarios, reasoning visible
- Cost
- Freemium (Free tier + paid plans)
- Ease
- Openness
- Hosted service
- Data
- Per Make's Help Center, "effective august 27th, 2025, we're replacing operations with credits as our billing unit," with existing operations converting 1:1. Standard modules stay at 1 credit, but native AI modules consume credits variably: per one 2026 review, "A workflow with AI Agents can consume 43-50 credits per execution (Small model), versus the few credits of a classic workflow." Extra credits cost 25% more than in-plan (Help Center, updated 6 Nov 2025), for both manual and auto-purchase. The sticker price is not the bill; consider calling AI APIs directly via HTTP for cost control.
Common questions
Which failure tolerance fits which tool?
Lindy's judgement is a feature where variation is acceptable and a liability where it is not, its own framing, so pipelines that must behave identically on every run belong on the workflow platforms, Make included. Make's determinism cuts the other way: error handling exists but needs actually configuring, and a scenario nobody documented is production infrastructure with a bus factor of one.
Who does the building on each?
Lindy asks for a manager: describe the job, connect the tools, set the rules, start from a template, then review while trust builds, since agents act on live email and customer records. Make asks for a builder, someone who enjoys constructing the machine and thinks in flows, with the visual form surviving handover better than a script but still deserving documentation.
How do their meters differ?
Both scale with activity, on different axes. Lindy's costs track how much the agents actually do, so always-on delegation deserves a look at plan allowances before running unattended. Make's credits track volume through scenarios, cheaper than task-priced rivals at scale yet compounding at the extreme. Neither punishes trying; both punish scaling without arithmetic.
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Tool facts last checked July 2026