Scenarios you wire on a canvas, or automation that reads your messages.
Make (formerly Integromat) is one of the most capable visual automation platforms there is: a canvas where you connect triggers and modules, a huge catalog of app integrations, and fine-grained control over complex multi-step scenarios. You build the scenario, and it runs the way you drew it. this+that takes a different shape. It reads the messages your team receives, decides what needs to happen, and runs the work, described in plain language rather than wired on a canvas.
Two different shapes of automation
Make is explicit and visual. You drop modules onto a canvas, wire the triggers to the actions, map the data between them, and the scenario runs the path you drew. For complex, deterministic pipelines across a large catalog of apps, few tools give a power user more control. this+that works the other way around. It reads your inbox and chat channels, works out what each message needs, and runs the workflow, with the steps described in plain language and grounded in your brain. One is built for the ops engineer who already knows the pipeline she wants. The other is built for the person buried in messages who needs an agent to read them, decide, and act. Plenty of teams will end up using both.
Feature by feature
How the two products compare across the things that matter most.
| Topic | Make | this+that |
|---|---|---|
| Core philosophy | Build it yourself on a canvas. You place modules, wire triggers to actions, and map the data, and the scenario runs the path you drew. | Read messages, decide what they need, and run the work that follows. The logic is described in plain language, not wired step by step. |
| Where work starts | With a trigger you configured in a scenario. Make is event-reactive once you build and wire the trigger module. | With the messages already arriving in your channels. Nothing to assemble before each one runs. |
| How automations are built | Visual scenario editor. Drag modules onto a canvas, connect them, and map fields between steps. Powerful and precise, with a real learning curve. | Plain-language workflows. 32 action types across email, the DoBox, calendar, and per-channel sends, with conditional logic, loops, and autonomous sub-agents. |
| AI decision-making | AI is available as modules you add to a scenario. The scenario itself runs the path you wired; it does not decide what to do with an incoming message on its own. | AI decision-making is built into the workflow. Steps can branch on what a message says, what it is asking for, and how urgent it is. |
| Inbox awareness | Not built in. A scenario can be triggered by a new email module, but Make does not read and triage your inbox proactively. | Core capability. this+that reads every message across email, Slack, Teams, and Google Chat and surfaces what matters. |
| Task layer | No persistent task layer. A scenario can write a row or a card wherever you wire it, but tracking lives in whatever tool you connect. | DoBox. Tasks are auto-created from messages across multiple lists, with assignees, priorities, due dates, comments, attachments, and recurring tasks. |
| Knowledge / grounding | Data stores and variables hold values inside a scenario. No team knowledge layer that grounds the automation in what your team knows. | The brain: a team knowledge layer with version history that grounds workflow steps and the AI. It does not yet auto-update from your messages; that is coming. |
| Integration breadth | Very large catalog of app integrations, plus HTTP and webhook modules for anything with an API. This is a real strength. | Deep, native handling of your messaging channels, plus the open MCP standard for tools like GitHub, Notion, HubSpot, Asana, ClickUp, and more. |
| Channels | Trigger on an email or chat event you wire up, but not a unified inbox. No proactive cross-channel reading. | Gmail, Outlook, Slack (personal and team bot), Google Chat, and Telegram read as one stream. Teams ingested. WhatsApp, Instagram, and Messenger coming soon. |
| Team features | Team and organization plans for shared scenarios, roles, and folders. No shared task assignment. | Shared task view, tasks assignable to teammates, and workflow delegation across the team. |
| Who it is for | The ops engineer or power user building precise, complex pipelines across many apps. | The person buried in messages who needs an agent to read them, decide, and act. |
| Maturity | A mature, widely used platform with years of production use and deep power-user features. | Newer product, actively developed. Core automation, inbox, and task features are available now. |
- Raw control over complex scenarios. The visual canvas lets a power user build precise, multi-branch pipelines with exact data mapping between steps.
- An enormous catalog of app integrations, plus HTTP and webhook modules that reach anything with an API.
- Fine-grained handling of data: iterators, aggregators, routers, filters, and data stores give deep control over how records move and transform.
- Predictable runs. A scenario behaves the same way every time, which is what you want for structured, high-volume pipelines where every record should take the same path.
- A mature platform with years of production use, error handling, scheduling, and detailed run logs.
- For the ops engineer who knows precisely what to automate and wants to build it, Make is a strong pick.
- It reads your team's messages and acts on them, rather than waiting for triggers you wire up per scenario.
- Workflow steps can branch on what a message says and what it asks for, not just on fixed conditions you mapped in advance.
- You describe a workflow in plain language, with conditional logic, loops, and autonomous sub-agents, instead of assembling it module by module.
- Task extraction comes built in: every conversation is scanned for requests, commitments, and deadlines, surfaced in DoBox automatically.
- A universal inbox, tasks, and a knowledge layer come bundled, rather than being something you wire a scenario to populate.
- Workflow steps draw on a team knowledge layer, so the automation reflects what your team already knows.
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