“Automate your work.”
Make is a visual no-code/low-code automation platform for integrations, workflows, and increasingly also agentic AI processes.
Companies can use it to connect data and actions across 3,000+ apps, automate API-based processes, and incorporate AI features such as AI Agents, AI Toolkit, AI Content Extractor, AI Web Search, and MCP servers into scenarios. The product addresses both simple app automations and more complex enterprise workflows with team, governance, and hybrid connectivity.
Make
Automate your work
Origin: USA ⓘ Celonis, Inc., One World Trade Center, 87th Floor, New York, NY 10007, USA.
Pro Everything in Core plus Priority Scenario Execution, Custom Variables, and Full-Text Execution Log Search.
Teams Everything in Pro plus Teams, team roles, and sharing of scenario templates. Other Enterprise Custom Functions Support, Enterprise App Integrations, 24/7 Enterprise Support, Value Engineering, Overage Protection, and Advanced Security.
Credits / AI Agents Credit-based usage for scenarios and AI automation; scope of features varies by plan.
Target audience
Make is aimed at a broad spectrum: from individual users who want to build simple app automations via drag-and-drop to teams and large enterprises building cross-functional integration and AI landscapes. Officially, Make addresses areas including marketing, sales, operations, customer experience, finance, IT, HR, and workplace productivity. For enterprise users, Make additionally positions itself as a platform for scalable, secure, and governance-ready automation.
Outstanding features
Particularly noteworthy are the visual scenario modeling, the large app library, and the more recent integration of AI with traditional automation. Under “Make + AI,” Make lists several building blocks: AI Applications, MCP Server, AI Content Extractor, AI Web Search (beta), AI Agents, and AI Toolkit. The new AI Agents are created directly in the builder and, according to Make, offer traceable execution via a Reasoning Panel, which improves debugging and transparency compared to typical black-box agents.
Key application areas
The most important areas include app integrations, data and process synchronization, lead and CRM automation, email and marketing workflows, support triage, reporting, document extraction, and AI-supported decision logic. Make also cites specific agent examples such as support ticket triage, sales outreach, content marketing, market research, and candidate screening. This means the tool covers both classic BPA scenarios and newer agentic use cases.
Usage & notes
Operation is primarily handled via the visual Scenario Builder. For AI functions, one important point is that AI Agents are officially in Open Beta, and pricing may change. The billing model is based on credits; with AI functions, complexity increases because, in addition to operations, tokens, file sizes, pages, or runtimes may also be factored in. From a data protection perspective, particular attention should be paid to the selected hosting region, the enabled AI services, and the privacy policies of the connected third-party providers.
| Target audience | Assessment |
|---|---|
| Self-employed / Freelancers | Highly suitable – for recurring workflows, marketing, CRM, data synchronization, and AI automation. |
| SMEs | Highly suitable – visual automation across many apps, APIs, and data sources. |
| Agencies / Automation experts | Highly suitable – more complex scenarios, routers, filters, API workflows, and templates. |
| Enterprise teams | Suitable – Enterprise offers more security, support, integrations, and governance. |
| Non-technical beginners | Conditionally suitable – easier than code, but more complex than very simple Zapier workflows. |
Hosting & Data
1) On-prem / local hosting
Meaning: The company operates the solution on its own hardware or within its own infrastructure. In the strictest sense, not only the application runs locally, but ideally the model as well.
2) Private cloud / data center
Meaning: The solution runs in a dedicated or more clearly separated cloud environment, often with a hosting provider or hyperscaler, but in a German data center or in a particularly controlled environment.
3) EU SaaS / managed
Meaning: The provider operates the solution itself as a service. The company uses the tool as a ready-made cloud service, ideally with EU data residency.
4) Hybrid
Meaning: One part of the processing remains internal / local / in a private cloud, while another part runs in an external cloud or EU SaaS.
5) AVV / DPA
Meaning: This is the data processing agreement or Data Processing Addendum. It governs that the provider processes personal data on behalf of the customer and is bound by the customer's instructions.
6) No training
Meaning: The provider does not use your prompts, uploads, attachments, chat histories, or outputs for training or improving the general model — ideally excluded by contract.
7) Open-source / transparency path
Meaning: There is a path toward greater technical transparency and sovereignty, for example through:
- open models
- documented components
- self-hostable parts
- traceable architecture
- export / switching options
| On-prem / local hosting | ⚠️ |
| Private cloud / data center | ⚠️ |
| EU SaaS / Managed | ✅ |
| Hybrid | ✅ |
| DPA / AVV | ✅ |
| No training on customer data | ❓ |
| Open source / transparency path | ⚠️ |
Overall assessment of hosting & data:
Make is a managed SaaS platform for visual automation and AI agents. On-premises hosting is not publicly documented as a standard option. Positive aspects include 3,000+ apps, a visual workflow builder, API access, routers/filters, team roles, scenario templates, enterprise support, and AI Agents. Critical concerns remain third-party connections, logs, data transfer between apps, API credentials, and AI providers in scenarios.
Conclusion:
Make is strong for flexible, visual business automation; for GDPR-compliant use, a DPA, data minimization, EU/region verification, credential security, and review of all connected apps are essential.
| On-prem / local hosting | ⚠️ |
| Private cloud / data center | ⚠️ |
| EU SaaS / Managed | ✅ |
| Hybrid | ✅ |
| DPA / AVV | ✅ |
| No training on customer data | ❓ |
| Open source / transparency path | ⚠️ |
Overall assessment of hosting & data:
Make is a managed SaaS platform for visual automation and AI agents. On-premises hosting is not publicly documented as a standard option. Positive aspects include 3,000+ apps, a visual workflow builder, API access, routers/filters, team roles, scenario templates, enterprise support, and AI Agents. Critical concerns remain third-party connections, logs, data transfer between apps, API credentials, and AI providers in scenarios.
Conclusion:
Make is strong for flexible, visual business automation; for GDPR-compliant use, a DPA, data minimization, EU/region verification, credential security, and review of all connected apps are essential.
Strengths & Weaknesses at a Glance
| Strengths | Weaknesses |
|---|---|
| – Very strong visual workflow modeling without the requirement for in-house backend development. | – The pricing model is credit-based; for AI and advanced features, consumption can fluctuate dynamically based on operations, tokens, pages, file size, or runtime, which makes cost estimation more difficult. |
| – 3,000+ standard apps and API access for broad integration coverage. | – The free tier is significantly limited for production use, including 1,000 credits/month, 2 active scenarios, and a 15-minute interval. |
| – AI features are not just add-ons, but can be integrated directly into scenarios. | – According to the Help Center, the On-Prem Agent is an Enterprise feature and currently supports only the HTTP Agent approach, i.e. not full self-hosting of the entire platform. |
| – Enterprise expansion with team roles, templates, enterprise apps, on-prem agent, and advanced security features. | – The new AI Agents are officially in Open Beta; functionality and pricing may change. |
| – Official privacy/compliance documentation is published comparatively extensively. | – According to the MSA, the customer remains responsible for third-party services and their data protection/terms of use. |
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GDPR-compliant use possible?
GDPR assessment: From a GDPR perspective, Make is conditionally to well suited, especially for European companies, if a DPA and an appropriate data region are used.
Positive is that Make provides a Privacy & GDPR page, a Data Processing Agreement, subprocessors/SCC documents, as well as SOC 2 Type II and SOC 3. Also positive is the European provider/Celonis connection and the ability to control automations very closely.
Negative is that, depending on the connected apps, modules, AI providers, and third parties, data may be transferred to additional systems; for AI functions, the respective model providers must also be reviewed separately.
Server location: Make does not publicly state in all sources a clear blanket server location for all accounts; Enterprise/regions/subprocessors should be checked specifically. Further link: Make Privacy & GDPR, Security, DPA.