Deelo vs. Make (Integromat): Visual Automation Without the Per-Task Bill

Make, formerly Integromat, is one of the most genuinely powerful automation tools on the market. Its visual scenario builder lets you construct multi-step, branching, data-transforming workflows that would make a lot of 'no-code' tools choke. If you have a complicated chain of logic to run across many third-party apps, Make can almost certainly model it, and model it elegantly. This is not a hit piece — Make earns its reputation.

But Make and Deelo solve the automation problem from opposite ends, and the comparison only makes sense once you see that. Make is a standalone connector: it sits outside your apps and shuttles data between them, billed by the operation. Deelo is an all-in-one platform where the automation runs inside the system your data already lives in, so there is nothing to connect and no per-task meter for moving your own data between your own apps.

This post is an honest head-to-head: where Make is the better tool, where Deelo is, and how the per-operation pricing model changes the math as you scale. Pricing here is dated and hedged on purpose — check current figures before deciding.

Make connects apps you bought separately; Deelo automates apps that already share a platform. Everything else flows from that.

With Make, your CRM, your invoicing tool, your project app, and your email platform are four separate vendors. Make's job is to be the wiring between them — watch for an event in one, transform the data, push it into another. That wiring is the product, and it is metered: every step a scenario runs consumes an operation, and operations are what you pay for. The more your automations do, and the more often they run, the more operations you burn.

With Deelo, those same functions — CRM, invoicing, projects, helpdesk, and 50+ apps — live on one platform under one login, sharing a data layer. The automation engine does not connect them because there is no gap to bridge. A won deal can create an invoice and start a project as one native workflow, and you are not charged per step to move data between your own apps, because nothing is leaving the platform. This is the entire reason the per-task bill is the headline of this comparison: it is the cost Make's architecture necessarily incurs and Deelo's architecture necessarily avoids. Whether that matters to you depends on how consolidated your stack is.

Make's pricing is metered by operations — roughly, each step a scenario executes counts as one operation, and your plan includes a monthly quota. This model is fair and transparent: you pay for what you use. It is also the thing that surprises people as they scale, so it deserves a clear-eyed look rather than a cheap shot.

The dynamic is straightforward. A simple two-step scenario that runs occasionally costs almost nothing. But automation done well tends to grow — more scenarios, more steps per scenario, higher trigger frequency. A multi-step workflow that fires hundreds of times a month is hundreds times its step count in operations, and successful automation is precisely the kind that runs a lot. So the per-operation model has a quiet property: the better your automation works, the more it costs. That is not a flaw — it is honest usage-based pricing — but it is the opposite of how a flat platform subscription behaves, where running a native workflow ten thousand times costs the same as running it ten times.

The fair framing: if your automations are few and infrequent, Make's metering is cheap and the power is a bonus. If you are building a lot of high-frequency cross-app automation, model the operation count honestly before you commit, because it scales with success. And if most of that cross-app work is between apps that could live on one platform, the metered model is paying to move your own data — which is exactly the cost Deelo's architecture removes. Always check Make's current pricing and quotas; tiers and operation allowances change.

Make's power has a price beyond operations: it asks more of the person building. Iterators, aggregators, data stores, and complex routing are genuinely capable, but they assume a builder comfortable thinking about data structures, mapping, and flow control. For a technical operator that is a feature — the ceiling is high. For a non-technical small-business owner who just wants 'won deal makes an invoice,' it can be more machine than the job needs.

There is also a maintenance question that standalone connectors cannot escape. Every scenario depends on connections to third-party apps, and those apps change — APIs get versioned, auth tokens expire, fields get renamed. Someone has to own keeping the wiring alive, and on a small team that someone is usually the busiest person. A scenario that worked perfectly in January can quietly break in March because a connected app changed something upstream, and you find out when the automation stops doing its job.

Deelo's native model sidesteps both issues for on-platform work. The builder is a visual graph with conditions, delays, loops, and AI nodes — capable, but aimed at the common small-business case rather than arbitrary data engineering. And because cross-app actions stay inside the platform, there is no third-party connection to maintain for them. The honest caveat: Deelo is not trying to match Make's depth for transforming data across hundreds of external services. For that specific job, Make is the better tool, and you should use it.

This does not have to be a divorce. A sensible setup for many small businesses is native automation inside Deelo for everything on-platform — the CRM-to-invoice, project-to-invoice, ticket-to-CRM flows that make up the bulk of daily operations — and a connector like Make reserved for the genuine outliers, the handful of third-party tools you will never bring on-platform.

That way you get the best of both architectures. The high-frequency, cross-app, data-already-here automations run native and unmetered, so the cost that grows with success simply does not apply to them. The occasional 'push this Deelo event into a specialized external system' runs through Make, where the per-operation cost is small precisely because it is occasional. You stop paying a metered bill to shuttle your own data between your own apps, and you keep Make for what it is genuinely best at — connecting the things that live outside.

The decision is not 'Deelo or Make.' It is 'how much of my stack is already consolidated, and how much is genuinely external.' The more consolidated you are, the more your automation should be native and the smaller Make's role becomes. The more fragmented you are and intend to stay, the more Make earns its keep. Be honest about which describes you today, and revisit it as you consolidate.

Make is an excellent, powerful, visual automation tool for connecting a fragmented stack, and technical operators who use its depth get a lot for the operations they spend. If your business runs a dozen specialized tools you have no plan to consolidate, Make is a strong choice and you should evaluate it on its merits.

Deelo is not a better connector than Make — it is a different proposition. It removes the need to connect in the first place for everything on the platform, which means no per-task bill to move your own data and nothing to maintain. That is most valuable when your apps already share a home. If you are consolidating onto one platform, native automation turns a recurring, scaling cost into something included in your subscription. If you are committed to a sprawling external stack, a connector is the right tool and Make is one of the best.

Choose based on architecture, not features. Where does your data live, and how much of your automation simply moves it between apps you could have run in one place? Answer that honestly and the right tool — or the right combination — becomes obvious.