Who looks for a Make.com alternative
Make is a good product. Its visual canvas is one of the clearest ways to see how data moves between apps, it connects to thousands of services, and its entry plans are cheap. Agencies and operations people build serious businesses on it. So the people searching for an alternative are rarely unhappy with Make as a whole. They are unhappy with one kind of job running on it.
That job usually looks like this. Every Monday a scenario pulls data from a CRM or a list of web pages, sends it through an OpenAI or Claude module, formats the answer and posts it to Slack. It worked when it was built. Six months later it has three routers, an iterator, an aggregator, a text parser that breaks when the model changes its wording, and a filter nobody remembers adding. The person who built it is the only one who can touch it.
Signs Make is more machinery than the job needs
- Most of your scenarios start with a schedule and end with a message, an email or a row in a sheet.
- The AI step is the heart of the scenario, and everything around it is glue to clean its output.
- You keep a separate data store only so the scenario can remember what it saw last week.
- Credit usage jumps when a list gets longer, because every item multiplies the operations.
- A failed run shows up as an incomplete execution that someone finds days later.
Crons vs Make side by side
| Area | Crons | Make |
|---|---|---|
| How you build | One sentence in plain English, then edit the proposed steps | Drag modules onto a scenario canvas and map fields between them, with routers, iterators and filters |
| Schedules | Plain English with timezone, every hour on Starter, 15 minutes on Pro, 5 minutes on Teams | Scenario schedule with intervals down to 1 minute on paid plans and 15 minutes on Free |
| AI agents | Every cron is an AI agent with web, browser, reasoning, memory and delivery steps | AI modules and Make AI Agents that you add to scenarios; model costs may be billed by the model provider |
| Memory between runs | Built in steps to compare with the last run and skip duplicates | Possible with data stores and lookups you design |
| Human approval | Approval gate step on every plan, with Slack or email notice | Possible with webhooks, forms or third party tools you wire in |
| Failure handling | 3 retries with backoff and an alert by email or Slack with the failing step | Error handler routes and incomplete executions you set up per scenario |
| Integrations | Slack, Gmail, HubSpot, Google Sheets, Notion, webhooks, HTTP requests, browser actions | Thousands of app modules, the widest catalog in this comparison |
| Pricing model | Flat plans at $99, $299 or $999 per month, or $49, $149 or $499 billed yearly, AI calls included | Credits: most actions use 1 credit, some AI features use more; paid plans start at about $9 per month billed yearly for 10,000 credits |
| Best for | Business teams running recurring research, reporting and monitoring agents | Builders who connect many apps with precise data mapping |
Make details come from Make's pricing page and help center, which describe credits as the billing unit, note that most actions use 1 credit while some AI features use more, and list Core, Pro, Teams and Enterprise plans. Make changes prices and limits from time to time, so check the current page before you decide.
The honest summary: Make wins on price per simple operation and on the size of its app catalog. If your scenarios move data between many apps with exact field mapping, Make is hard to beat and you should stay. Crons wins when the work is a smaller set of scheduled AI jobs that a business team has to build, trust and audit without a scenario specialist.
What Make really costs for AI jobs
The sticker price of Make is low, which is why it shows up on every shortlist. The real bill for an AI job is made of three parts. First the credits: a scenario that reads 40 competitor pages, sends each one to a model and writes the result uses at least one credit per module per item, so a weekly run over 40 items with five modules is around 200 credits a run before any retries. Second the AI itself: if you connect your own OpenAI or Anthropic key, the model usage is billed by that provider on top of Make. Third the time: someone has to maintain the parsers, data stores and error routes.
None of that is a reason to leave Make for integrations. It is a reason to look at the jobs where the AI step does most of the work. In Crons a cron run is counted once no matter how many steps it has, the AI calls are included in the plan, and memory, retries and alerts are part of the product rather than modules you add.
| Cost item | Crons Starter | Make paid plan |
|---|---|---|
| Runs per month | 4 runs, out of 300 included | 4 scenario runs |
| Usage counted | 4 runs | Roughly 800 credits at about 200 per run, more with retries or AI features that use extra credits |
| AI model usage | Included in the plan | Billed by Make or by your model provider, depending on the module |
| Memory of last week | Built in step | Data store you create and maintain |
The credit figure is an estimate for a typical five module scenario, not a Make quote. Run the scenario once and read the credit count in its history to get your own number.
Moving a Make scenario to Crons
You do not import a blueprint. Read the scenario from the trigger to the last module, and write what it achieves as one sentence. For example: "Every Monday at 8 AM New York time, read the pricing pages of our 12 competitors, compare with last week, and post only real changes to #product in Slack."
- 1Paste the sentence into the demo on the homepage. Crons turns the timing into a cron expression and shows the next three run times.
- 2Review the proposed steps: web fetch or browser actions, an AI step that reads the pages, a memory check against last week, and a Slack post. There are no routers or iterators to configure.
- 3Connect the apps the cron uses from the integrations list.
- 4Run it once as a dry run and read the full log without posting anything.
- 5Add an approval gate in front of any step that emails customers or writes to your CRM, then switch the cron on and turn the Make scenario off.
Most reporting and research scenarios move over in under an hour, including testing. Scenarios that are really data plumbing, such as copying every new order into an ERP with exact field mapping, are better left in Make or triggered from it.
Jobs that fit Crons better than Make
- Competitor monitoring. Pricing pages, changelogs and job boards checked on a schedule, with only real changes reported. The competitor monitor template is ready to use.
- Weekly team reports. Pipeline, ticket or campaign data summarized every Monday and posted to Slack. See the AI agent Slack bot guide.
- Lead research. New funding announcements or hiring signals matched to your ideal customer profile every weekday and written to HubSpot without duplicates.
- Client reporting for agencies. One cron per client with its own schedule, sources and Slack channel, instead of one scenario cloned twenty times.
- Month end checks. Invoices from Gmail matched against a ledger sheet, with mismatches held for approval before anyone is emailed.
The common thread is a clock, a judgment call by AI and a result a person acts on. That is why each job in Crons is a single AI cron job rather than a scenario of modules.
When Make is the better choice
Pick Make if you need an app Crons does not connect to, if you run thousands of small operations a day where a cent per action matters, if your work is mostly event driven data sync, or if you have a builder on the team who likes the canvas. Make is also the right call for complex transformations of structured data where exact field mapping beats an AI summary.
Crons has no free plan. Starter is $99 per month, or $49 per month billed yearly, for 10 active crons and 300 runs a month. Pro is $299, or $149 billed yearly, for 50 crons, 1,500 runs, 5 seats, inbound webhooks, the REST API, an MCP server and sandboxed code steps. Teams adds unlimited crons, SSO, an audit log and a 99.9 percent uptime SLA. Full limits are on the pricing page.
Using Make and Crons together
Many teams keep both. Make handles real time plumbing between apps, and Crons runs the scheduled AI agents. On Pro and Teams, a Make HTTP module can start a cron through an inbound webhook or the REST API, and a cron can call a Make custom webhook at the end of its run to hand results to an existing scenario. Teams weighing other builders can read our n8n alternative comparison and Zapier AI Agents comparison.
Frequently asked questions
What is the best Make.com alternative for AI agents?
For scheduled AI work, the easiest alternative is a tool that builds the job from a plain sentence. Crons turns "every Monday, check these pages and post changes to Slack" into a schedule with steps, memory and approvals. For broad app to app automation, Zapier and n8n are the usual picks.
Is Make cheaper than Zapier?
For simple automations, usually yes. Make charges credits, where most actions use 1 credit, and its paid plans start at about $9 per month billed yearly for 10,000 credits. Costs rise with long lists and AI features that use more credits, so measure a real run before comparing.
How much does Make.com cost per month?
Make has a Free plan with 1,000 credits a month and paid Core, Pro and Teams plans priced by credit volume, starting at about $9 per month billed yearly for 10,000 credits, with Enterprise on request. Check Make's pricing page for current numbers.
Can I move my Make scenarios to Crons?
You rebuild them rather than import a blueprint. Describe what the scenario achieves in one sentence, review the proposed steps and do a dry run. Scheduled reporting, research and monitoring scenarios usually take minutes to rebuild.
Does Crons charge per operation like Make?
No. Crons counts runs, not steps, and includes the AI calls in the plan. Starter covers 10 active crons and 300 runs a month, Pro 50 crons and 1,500 runs, and Teams is unlimited.
Can Crons and Make work together?
Yes. On Pro and Teams, Make can start a cron through an inbound webhook or the REST API, and a cron can send its results to a Make custom webhook. Many teams keep integrations in Make and move scheduled AI jobs to Crons.