Make (Integromat) vs Perplexity AI: Complete Comparison (2026)

Updated: March 12, 20268 min read

Make (Integromat) stands out as a robust visual automation platform that excels in connecting various apps and AI services to handle intricate workflows, such as multi-step data processing and integrations, making it ideal for power users who need flexibility beyond simple triggers. In contrast, Perplexity AI serves as an advanced AI search engine that provides real-time, cited answers to complex queries, leveraging up-to-date web sources for accurate research assistance, which is particularly useful for professionals requiring verified information without manual digging. While both tools boast high ratings of 4.7/5, Make's strength lies in its operations-based pricing and deep automation capabilities, whereas Perplexity shines in delivering source-cited responses but falls short in areas like precise coding support. This comparison highlights how Make is geared toward workflow efficiency and Perplexity toward informed decision-making through AI-driven research.

⚙️
Make (Integromat)
AI & Machine Learning
94
hiltonsoftware.co Score
VS
🔍
Perplexity AI
AI & Machine Learning
94
hiltonsoftware.co Score

Quick Comparison

Make (Integromat)
Perplexity AI
Starting Price
$9/mo
$20/mo
Free Plan
Yes
Yes
Users
800K+
15M+
Founded
2012
2022
Rating
4.7/5
4.7/5
Best For
Power users building complex, multi-step automatio...
Researchers and professionals wanting AI-powered, ...

Feature-by-Feature Comparison

Make (Integromat)Perplexity AI
97Ease of Use96
96Features96
99Value for Money96
93Customer Support90
90Integrations96
91Scalability94
92Learning Curve97

Pros & Cons at a Glance

Make (Integromat)
+Very powerful and flexible automation
+Better than Zapier for complex flows
-Steeper learning curve than Zapier
-Operations-based pricing confuses users
Perplexity AI
+Up-to-date answers with sources
+Excellent research assistant
-Sources sometimes misquoted
-Less powerful for coding than ChatGPT
AI Verdict

Based on the provided data, I recommend Make (Integromat) for users focused on building complex, multi-step automations between apps, as its powerful flexibility and 800K+ user base make it superior for scenarios requiring intricate integrations, despite its steeper learning curve. On the other hand, Perplexity AI is the better choice for researchers and professionals needing real-time, cited answers to web queries, given its 15M+ users and strength in up-to-date information, though it has issues with source accuracy. Ultimately, if your priority is workflow automation over research, Make's $9/month pricing and features edge out Perplexity's $20/month plan, but for AI-powered search, Perplexity takes the lead due to its specialized capabilities.

CHOOSE MAKE (INTEGROMAT) IF:

Power users building complex, multi-step automations between apps.

CHOOSE PERPLEXITY AI IF:

Researchers and professionals wanting AI-powered, cited web research.

Frequently Asked Questions

What are the primary differences in functionality between Make (Integromat) and Perplexity AI?
Make (Integromat) focuses on visual automation for connecting apps and AI to create complex workflows, such as multi-step processes that handle data across platforms, making it more powerful for integration-heavy tasks compared to simpler tools like Zapier. Perplexity AI, however, is designed as an AI search engine that delivers real-time, cited answers to questions, emphasizing research accuracy with source links, but it lacks the depth in automation that Make offers. This means Make is better for operational efficiency in business processes, while Perplexity excels in providing quick, verified insights for knowledge-based work.
How do the pricing structures and key features of Make compare to those of Perplexity AI?
Make (Integromat) starts at $9 per month with a free plan, offering features like flexible automation for complex workflows and app integrations, though its operations-based pricing can confuse users due to variable costs based on usage. Perplexity AI, priced at $20 per month with a free plan, provides AI-powered search with real-time, cited answers and source verification, but it doesn't match Make's depth in building multi-step automations. Overall, Make is more cost-effective for automation needs, while Perplexity's higher price reflects its specialized research capabilities, making the choice depend on whether you prioritize workflow tools or advanced search.
Which tool is better for automating research workflows involving AI?
For automating research workflows, Perplexity AI is generally better due to its ability to deliver real-time, cited answers from web sources, making it an excellent assistant for professionals who need quick, verified insights without manual effort. However, if the workflow involves integrating AI with other apps for more complex automation, Make (Integromat) would be the superior choice because of its powerful multi-step capabilities and flexibility. Based on user ratings and features, I'd recommend Perplexity for straightforward AI research and Make for broader automation integration.
How easy is it to switch from Make to Perplexity AI or vice versa?
Switching from Make to Perplexity AI might be straightforward if you're moving from automation to pure research, as Perplexity's user-friendly interface allows quick adoption for query-based tasks, but you'll lose Make's workflow capabilities, potentially requiring a learning curve for new users. Conversely, migrating from Perplexity to Make could be more challenging due to Make's steeper learning curve for building complex automations, though its visual platform helps in transferring research insights into actionable workflows. In either case, backing up your data and understanding each tool's strengths is essential to minimize disruption during the switch.

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