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Published 6 March 2026 · Updated 20 March 2026
Make vs Pinksheep: which is right for your team?
Quick answer
Make (formerly Integromat) is a visual automation platform that connects apps through drag-and-drop scenarios. Pinksheep is a conversational AI agent builder built for business teams. Make excels at complex multi-step automations with visual debugging. Pinksheep excels at AI-powered workflows where you want full visibility, approval-first actions, and plain-English agent building.
Make (formerly Integromat) is a visual automation platform that connects apps through drag-and-drop scenarios. Pinksheep is a conversational AI agent builder built for business teams. Make excels at complex multi-step automations with visual debugging. Pinksheep excels at AI-powered workflows where you want full visibility, approval-first actions, and plain-English agent building.
Feature comparison
| Feature | Make | Pinksheep |
|---|---|---|
| Builder type | Visual drag-and-drop scenarios | Conversational (plain English) |
| Approval workflows | None native | Native, optional per action |
| Audit trail | Execution history with visual debugging | Full decision + approval trail |
| No-code | Yes | Yes |
| Spend controls | No | Yes (per-agent caps) |
| Integrations | 1,000+ | 500+ |
| MCP export | No | Yes |
| AI reasoning | Limited (trigger-action model) | Core (agents reason about tasks) |
| Pricing | From $9/mo (operations-based) | Free tier, then credit-based plans from $29/mo |
| Best for | Complex visual automations with branching logic | AI-driven workflows with optional approval controls and full audit logging |
When Make is the better choice
- You need complex branching logic, error handling, and conditional routing in a visual interface.
- You want to debug automation runs visually, seeing exactly which step failed and why.
- Your workflows are operations-heavy and trigger-action based, not AI-reasoning based.
- You need access to Make's 1,000+ integration library.
When Pinksheep is the better choice
- You're deploying AI agents that reason about tasks, not static trigger-action chains.
- You need approval gates before any AI-driven write reaches your CRM or data systems.
- You need a full audit trail with actor attribution for compliance or review.
- Your team describes workflows in plain English, not by connecting nodes.
The key difference: control
Make is a deterministic automation engine. You define the scenario, it runs it. This works well for static, predictable workflows where you've already validated every step.
Pinksheep is built for AI agents that reason about what to do next. Because the agent is making decisions, you get a full audit trail of what it did and why. Pinksheep shows you the plan before important actions run, so you stay in control.
If you're automating with AI, visibility and control are part of the product. Pinksheep builds both in from day one.
Common questions
What does Make do well that Pinksheep doesn't try to replace?
Make excels at high-volume, high-frequency data movement between apps: syncing records in real time, transforming data structures, and running thousands of operations per month at low cost. If your core need is moving data between tools in a predictable, repeatable way without AI reasoning, Make's visual scenario builder and operations-based pricing is hard to beat.
What does Pinksheep do that Make can't?
Pinksheep adds AI reasoning to the workflow execution layer. An agent can read a Zendesk ticket's content and classify it, draft a personalised email based on deal context, or flag a CRM record anomaly based on pattern recognition. All with a full audit trail and approval-first actions on important writes. Make can call AI APIs via HTTP modules, but the reasoning, approval workflow, and audit trail aren't built in.
Our team built complex Make scenarios with hundreds of modules. Is migrating realistic?
For complex, stable Make scenarios that are working well, migration isn't necessary or recommended. Pinksheep is better suited for new workflows where the AI reasoning and approval control add clear value, or for Make scenarios that frequently break due to edge cases that fixed module logic can't handle. Most teams run both simultaneously rather than doing a wholesale migration.
How does Pinksheep's pricing compare to Make for a team running a moderate number of workflows?
Make charges per operation (each module execution counts as an operation), which means high-frequency workflows with many steps can get expensive quickly. Pinksheep charges per agent run (an entire workflow counts as one run), which is more predictable for complex multi-step workflows. For simple high-frequency trigger-action flows, Make's operation pricing is typically cheaper. For complex AI-driven workflows with multiple steps per run, Pinksheep's per-run pricing is often more economical.
Does Pinksheep have an equivalent to Make's data store for persisting information between workflow runs?
Pinksheep doesn't have a built-in data store. For persisting state between runs, you connect to an external store: Google Sheets, Airtable, Notion, or a database. The agent reads and writes to your chosen storage tool as part of the workflow, rather than Pinksheep maintaining its own data layer. This keeps your data in tools you own and control.
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