Power Automate AI excels in seamless integrations with Microsoft 365 services, providing comprehensive automation for enterprise companies. Make AI, on the other hand, is well-regarded for its advanced app creation capabilities and is suited for more creative technical tasks, despite its higher cost and occasional glitches.
Best for
Power Automate AI is the better choice when integration with Microsoft products and automating workflow processes across a wide range of tools is crucial, especially for teams well-versed in Microsoft ecosystems.
Best for
Make AI is the better choice when developing complex applications, like iOS apps, without extensive technical expertise is a priority, particularly for teams focused on creative technical outputs.
Key Differences
Verdict
Choose Power Automate AI if your organization heavily relies on the Microsoft ecosystem and needs comprehensive workflow automation. Opt for Make AI if you require the ability to create complex applications with less technical skill but can accommodate higher costs and occasional unpredictability. Both tools are strong contenders in their respective niches, so the decision should align with your company’s primary needs and integration requirements.
Power Automate AI
Power Automate AI is praised for its integration capabilities and the ability to streamline workflows efficiently through automation. However, users have noted concerns regarding complex setup processes and occasional reliability issues. On the pricing front, users often express that while the tool offers robust features, it can be perceived as expensive for smaller businesses. Overall, its reputation is positive among developers and businesses valuing automation, but it may require technical expertise to maximize its potential.
Make AI
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Users of "Make AI" appreciate its capabilities in automating coding tasks and creating applications, highlighting the tool's ability to generate complex outputs like iOS applications without requiring extensive technical expertise. However, some users express concerns regarding unpredictable behavior, such as the insertion of unexpected prompts, and note the high cost of subscription relative to local currency conversion rates. Pricing is seen as a barrier for some, though its advanced features justify the expense for many who can afford it. Overall, "Make AI" has a strong reputation among those leveraging it for creative and technical applications, though it may intimidate non-developers due to perceived complexity and occasional glitches.
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Pricing found: $100,000
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DeepSeek just popped the American AI bubble.
DeepSeek just popped the American AI bubble. Not by killing AI. By killing the fantasy of unlimited AI pricing power. DeepSeek V4 Pro: Input: $0.435 per 1M tokens Output: $0.87 per 1M tokens OpenAI GPT-5.5: Input: $5.00 Output: $30.00 Claude Opus 4.7: Input: $5.00 Output: $25.00 Cl
Make AI
arXiv implements 1-year ban for papers containing incontrovertible evidence of unchecked LLM-generated errors, such as hallucinated references or results. [N]
From Thomas G. Dietterich (arXiv moderator for cs.LG) on 𝕏 (thread): [https://x.com/tdietterich/status/2055000956144935055](https://x.com/tdietterich/status/2055000956144935055) [https://xcancel.com/tdietterich/status/2055000956144935055](https://xcancel.com/tdietterich/status/20550009561449350
For automating Microsoft-based workflows, Power Automate AI is superior, while Make AI excels at building complex applications without extensive coding.
Power Automate AI is considered expensive for smaller businesses, while Make AI offers a tiered pricing model with options up to $100,000, including a freemium tier.
Power Automate AI has strong support within the Microsoft community, whereas Make AI benefits from a broader user base involved in creative and technical applications.
Yes, they can be used together, with Power Automate AI handling workflow automation and Make AI focusing on advanced app development tasks.
Power Automate AI might require more technical expertise initially, whereas Make AI is easier for rapid application development but may pose challenges for non-developers due to complexity.