Make at a glance
Rather than acting as a generic AI layer, Make is positioned around a visual workflow automation platform for connecting applications, logic, data, and ai services, with operations teams, technical marketers, automation specialists, agencies, and businesses that want visual control over complex workflows as the clearest audience. Its visual graph makes complex automation logic easier to inspect than a strictly linear recipe, which appeals to users who want more control without writing a complete integration service. The product matters because users increasingly expect AI to participate directly in the workflow rather than simply produce isolated text or media. Its value depends on how well it turns a request into something usable and easy to refine. Make is particularly strong when a workflow needs branching, data manipulation, or several connected services rather than one simple trigger and action.
Make is best understood as a freemium visual automation platform for orchestrating apps, data, business logic, and ai-powered steps. It addresses the gap between a user having an objective and having a finished or actionable output. Instead of requiring the user to build every step from scratch, the product provides an interface, workflow, or set of AI capabilities tailored to automation tasks. That makes it useful when speed and iteration matter, while still leaving room for human review and domain judgment.
Make in depth
How it works
From the user side, the workflow begins with an instruction, source material, project context, or other input supported by the product. Users assemble scenarios on a canvas by connecting application modules and routing data between them. Filters, routers, transformations, iterators, and AI services can be combined to create branching workflows that run on schedules or events. The result can then be reviewed, regenerated, edited, or passed into the next stage. In practice, iteration with clearer context and constraints matters more than expecting a perfect first output.
Getting started
A sensible first session with Make is deliberately small. Start with a two-step scenario using apps you already know. Run it manually with sample data and inspect every bundle before adding routers, loops, or AI modules, because debugging gets harder as the visual graph grows. Start with one representative task rather than a mission-critical workflow, then compare the result with what you would normally produce manually. Check where human correction is still required, then save a successful prompt, template, or project as a repeatable baseline.
About Celonis
Make is published by **Celonis**. Celonis owns Make, a visual automation platform used to connect cloud applications and orchestrate data-driven workflows. For procurement or long-term adoption, use the official site and documentation as the source of record for current product and policy details.
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Features
Workflows are represented as connected modules on a canvas, making branching and multi-step logic easier to understand and troubleshoot.
Built-in mapping, filtering, iteration, and routing help users reshape information as it moves between applications.
Prebuilt integrations reduce the need to hand-code common connections across marketing, sales, operations, and productivity software.
AI models and services can be inserted into scenarios for tasks such as classification, generation, extraction, and decision support.
Technical teams can use APIs and webhooks when they need to connect custom systems or extend beyond standard modules.
Use cases
A team can collect leads, normalize form data, route contacts by campaign, create CRM records, and trigger follow-up without manual spreadsheet work.
An operations workflow can receive files, extract or classify information with AI, rename and store the document, then notify the responsible team.
A store can react to orders, sync inventory or customer data, and branch workflows based on product, location, or order value.
A creator can combine databases, prompts, AI generation, approval steps, and publishing systems in one visible scenario.
Advantages & Limitations
✓ Advantages
- Advantages
The main advantage of Make is its expressive visual builder and strong control over branching, transformations, and data flow. That can make it meaningfully faster to reach a first usable result and easier to repeat a workflow across projects or team members.
− Limitations
- Limitations
Its limitations are equally important: the interface can become dense for very large scenarios, operation-based pricing matters at scale, and poorly designed automations can be hard for another team member to maintain. Generated output can also be uneven or wrong in edge cases, so consequential work still needs human review.
Frequently asked questions
How does Make differ visually from other automation tools?+
Make features an interactive drag-and-drop visual canvas where users construct branching workflows. Users can visually map data variables, configure conditional routing routers, inspect error-handling paths, and observe live execution flows in real time.
Can Make process complex data transformations and AI operations?+
Yes, Make includes built-in functions for JSON parsing, array aggregation, regex extraction, and mathematical calculations. It connects seamlessly with AI model endpoints to categorize data, summarize content, and structure incoming webhooks.
Is Make suitable for high-volume enterprise data pipelines?+
Make offers robust scheduling, detailed execution logs, webhook rate-limiting, and error-handling modules that retry failed transactions, making it reliable for enterprise data synchronization, ecommerce order routing, and complex marketing automation pipelines.