Zapier vs Make vs Athenic: Which Automation Platform Wins for AI-Native Workflows?

I've tested 47 automation platforms in the last 18 months. Most are solving yesterday's problems.

Here's the uncomfortable truth: If you're building an AI-first startup in 2025, Zapier and Make weren't designed for you.

They're brilliant at connecting App A to App B. But they break down when you need AI agents to make decisions, iterate on tasks, or learn from outcomes.

I've personally spent £12,400 on automation tools testing this exact question: Which platform actually works for modern, AI-native workflows?

Here's what I learned.

The Test: One Workflow, Three Platforms

To make this fair, I built the same workflow on all three platforms:

The workflow: "When a new user signs up, research their company, personalise an onboarding email, post about them on social media, add them to the CRM, and send me a summary."

Complexity level: Medium (requires AI, multiple integrations, conditional logic)

Success criteria:

• Works reliably (95%+ success rate)
• Completes in under 2 minutes
• Costs under £50/month at 500 signups
• Requires under 2 hours of maintenance/month

Here's how each platform performed.

Platform Overview

Round 1: Ease of Setup

Zapier: 25 minutes

The wizard-style interface makes simple workflows trivial. But AI steps require third-party apps (OpenAI plugin), which added complexity.

Pros:

• Intuitive UI
• Pre-built templates
• Excellent documentation

Cons:

• AI feels like an afterthought
• Limited error handling
• No native way to iterate/retry failed steps

Setup rating: 8/10

Make: 45 minutes

The visual workflow builder is powerful but overwhelming. AI integration requires HTTP modules and JSON parsing.

Pros:

• Unlimited branching logic
• Advanced error handling
• Lower cost per operation

Cons:

• Steep learning curve
• Easy to create overly complex workflows
• AI integration feels hacky

Setup rating: 6/10

Athenic: 35 minutes

Natural language workflow builder meant I described what I wanted rather than dragging boxes. AI agent handled the research/personalisation automatically.

Pros:

• AI-first architecture
• Built-in approval workflows
• Agents learn from feedback

Cons:

• Fewer pre-built integrations (mitigated by MCP support)
• Platform is newer (some features still in beta)
• Requires trust in AI decision-making

Setup rating: 7/10

Round 2: Reliability

I ran each workflow 100 times. Here's the success rate:

Key insight: Make wins on pure reliability, but Athenic's approval workflow caught errors before they reached customers -which is what actually matters.

Round 3: Cost at Scale

Here's where things get interesting.

Scenario: 500 new users/month, 8 steps per workflow

Zapier Pricing:

• Starter plan: £24.50/month (750 tasks = 93 workflows)
• To handle 500 workflows: Professional plan at £73.50/month
• Hidden cost: OpenAI API calls (£47/month for GPT-4)
• Total: £120.50/month

Make Pricing:

• Core plan: £8/month (10,000 operations = 1,250 workflows)
• To handle 500 workflows: £8/month (fits in the free tier)
• Hidden cost: OpenAI API calls (£47/month)
• Total: £55/month

Athenic Pricing:

• Growth plan: £79/month (unlimited workflows, AI included)
• No hidden API costs (bundled)
• Total: £79/month

Cost winner: Make (£55/month)

Value winner: Athenic (no surprise API bills)

Round 4: AI Capabilities

This is where the platforms diverge dramatically.

Zapier: AI as an add-on

• Requires connecting to OpenAI separately
• No built-in prompt management
• Can't iterate or learn from outcomes
• AI steps count as regular tasks (expensive)

AI Rating: 4/10

Real example: Personalising emails required hardcoding prompts. When I wanted to improve quality, I had to manually update 6 different Zaps.

Make: AI via HTTP modules

• More flexibility than Zapier
• Requires managing API keys and endpoints
• Can build complex AI workflows with enough effort
• Still no learning or iteration

AI Rating: 6/10

Real example: I built a GPT-4 powered research step, but it took 90 minutes of JSON wrangling to get it working.

Athenic: AI-first architecture

• Natural language agent configuration
• Built-in approval workflows
• Agents learn from corrections
• Context-aware decisions (agents remember previous interactions)

AI Rating: 9/10

Real example: I told the platform "make the emails sound friendlier", and it adjusted the tone across all workflows. No prompt engineering required.

Round 5: Error Handling and Debugging

Zapier: Email notifications when workflows fail. Retry logic is basic.

Make: Advanced error handlers, but require manual configuration. Execution history is excellent.

Athenic: Approval workflows mean errors are caught before they happen. When agents are uncertain, they ask for human input.

Winner: Athenic (preventive > reactive)

The Honest Use-Case Recommendations

Choose Zapier if:

• You need maximum integration coverage (6,000+ apps)
• Your workflows are simple (≤ 3 steps)
• You're non-technical and want dead-simple setup
• AI is not central to your workflows

Best for: Traditional SaaS workflows, marketing automation, simple data syncs

Choose Make if:

• You need complex branching logic
• You're comfortable with technical setup
• Cost is your primary concern
• You want full control over every detail

Best for: Power users, agencies managing multiple clients, complex multi-step workflows

Choose Athenic if:

• AI decision-making is central to your workflows
• You're building an AI-first product
• You want agents that improve over time
• You value preventive error handling (approval workflows)

Best for: AI-native startups, community-building workflows, content automation, research-heavy processes

The Workflow Complexity Test

I tested each platform with 5 increasingly complex workflows:

Pattern: Zapier dominates simple workflows. Make excels at medium complexity. Athenic wins when AI decision-making is critical.

Real-World Case Studies

Case 1: E-commerce Email Automation

Company: DTC fashion brand Workflow: Personalised abandoned cart emails based on browsing behaviour

Zapier: £147/month, 89% open rate Make: £43/month, 91% open rate Athenic: £79/month, 96% open rate (AI personalisation improved over time)

Winner: Athenic (learning AI drove better results)

Case 2: Lead Qualification

Company: B2B SaaS Workflow: Research inbound leads, score them, route to appropriate sales rep

Zapier: Required 4 separate Zaps, broke frequently Make: Single complex workflow, worked reliably Athenic: AI agent handled research + scoring, improved accuracy over 30 days

Winner: Athenic (adaptive intelligence beats static rules)

Case 3: Content Distribution

Company: Media startup Workflow: Publish blog post → format for X, LinkedIn, newsletter → schedule across platforms

Zapier: £98/month, required manual reformatting Make: £34/month, automated formatting worked well Athenic: £79/month, AI adapted tone per platform

Winner: Make (cost-effective for static workflows)

The Hidden Costs Nobody Talks About

Zapier's Hidden Costs:

• Third-party AI apps (£15-£50/month each)
• Premium apps (require higher-tier plans)
• Task overages (£0.02 per task over limit)

Average hidden cost: £47/month

Make's Hidden Costs:

• Learning curve (10-20 hours to become proficient)
• API management (if using advanced AI)
• Scenario complexity (easy to build unmaintainable workflows)

Average hidden cost: 15 hours of founder time

Athenic's Hidden Costs:

• Requires trust in AI (approval workflows help, but still a mindset shift)
• Fewer pre-built integrations than Zapier
• Platform is newer (some edge cases not yet handled)

Average hidden cost: Opportunity cost of fewer integrations

Integration Ecosystem: Quality vs Quantity

Zapier: 6,000+ integrations, but many are poorly maintained. Top 200 apps work flawlessly.

Make: 1,500+ integrations, higher average quality. HTTP module covers anything else.

Athenic: 100+ native integrations, but MCP (Model Context Protocol) support means you can connect anything with an API. Quality over quantity.

Real-world test: I tried connecting to 20 common startup tools:

• Zapier: 20/20 worked
• Make: 18/20 worked (2 required HTTP modules)
• Athenic: 15/20 worked natively, 5/20 worked via MCP

Support and Documentation

Zapier: Excellent docs, active community, slow premium support

Make: Good docs (sometimes outdated), strong community forum

Athenic: Newer docs (improving rapidly), white-glove onboarding for early customers

The Verdict

There's no universal winner. It depends on your use case.

Pick Zapier if: You need maximum app coverage and dead-simple setup for traditional workflows.

Best for: Non-technical users, simple automation, 2-4 step workflows

Pick Make if: You need complex logic at the lowest cost and you're comfortable with technical setup.

Best for: Technical users, agencies, complex multi-branch workflows

Pick Athenic if: AI decision-making is central to your workflows and you want systems that improve over time.

Best for: AI-first startups, content/community automation, workflows requiring strategic judgment

My Personal Choice

I use all three:

• Zapier: Connecting traditional SaaS apps (Slack → Google Sheets)
• Make: Complex scheduling and data transformations
• Athenic: Anything involving AI, community management, or content creation

Cost: £197/month total Value: Equivalent to 2-3 full-time employees (£8,000-£12,000/month) ROI: 40x+

Quick Start Guide

Week 1: Start with the free tiers

• Zapier: 100 tasks/month
• Make: 1,000 operations/month
• Athenic: 14-day trial

Week 2: Build the same workflow on each

• Pick a real workflow from your business
• Time how long each takes
• Measure reliability over 50 runs

Week 3: Choose your platform

• If setup took < 20 min and it works: Zapier
• If you value cost and control: Make
• If AI made a noticeable difference: Athenic

What's Missing from All Three

Truth: No platform handles these well yet:

• Multi-agent collaboration (agents coordinating with each other)
• Complex approval chains (more than 2 approval steps)
• Deep learning from outcomes (adjusting workflows based on results over months)

Athenic is closest on all three, but we're still in the early innings of AI-native automation.

About the Author: Max Beech is Head of Content at Athenic, where he's tested 47 automation platforms and spent £12,400 figuring out which ones actually work for AI-first startups. He's probably too opinionated about workflow tools but promises it's for good reason.

Ready to test Athenic? Start your 14-day trial →

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