Viktor vs Make.com (2026)

Viktor

by Zeta Labs

Make.com

by Celonis (Make)

Pros

• ✓Executes tasks end-to-end in a persistent cloud computer: Viktor queries Salesforce, Stripe, Google Ads, and GitHub in one run and delivers a finished PDF or dashboard, not text to copy-paste into another tool.
• ✓Lives natively in Slack and Microsoft Teams: teams interact with Viktor like any colleague via @mention, with no separate interface or workflow to adopt, now one-click installable from the official Slack App Directory after full Slack approval.
• ✓Backed by the Slack co-founders and $75M in funding as of May 2026: Stewart Butterfield and Cal Henderson wrote personal checks into an AI coworker that runs inside the product they built, alongside Accel's Series A lead.

Limitations

• ⚠Security certifications are less mature than the marketing implies. Viktor holds SOC 2 Type 1, with Type II in progress and the report only available under NDA. ISO 27001 is in progress, not certified. Buyers whose procurement requires a completed Type II or ISO 27001 should treat both as pending.
• ⚠Credit-based pricing creates spend uncertainty for heavy users. Teams running many scheduled tasks or complex multi-tool queries monitor credit consumption carefully, with real-world spend ranging from $150 to $400 per month above the $50 headline Team plan rate.
• ⚠No standalone web interface. Viktor requires either Slack or Microsoft Teams as the interaction layer, so teams on Google Chat, Discord, or other platforms cannot adopt it without switching.

Pros

• ✓Visual scenario builder handles complex branching, iteration, parallel execution, and data transformation that Zapier's linear editor cannot match. Scenario Inputs and Outputs enable structured data passing between chained workflows.
• ✓Credit-based pricing is significantly more cost-effective than Zapier at high volume. Annual credits pool across 12 months rather than expiring monthly, and file size limits scale from 5 MB (Free) to 1 GB (Enterprise).
• ✓Connects 3,000+ apps with detailed control over data mapping and error handling at each step. Native MCP server and client app, Make AI Agents, Library of Agents, AI Content Extractor, and AI Web Search embed intelligence at any automation step.

Limitations

• ⚠Steeper learning curve than Zapier: building first scenarios takes meaningful time investment for non-technical users unfamiliar with visual workflow logic, scenario inputs and outputs, and branching paths.
• ⚠Smaller app library than Zapier at 3,000+ vs 8,000+: some niche tools lack native Make connectors and require custom HTTP module workarounds or the Custom Apps builder.
• ⚠No self-hosting option: data passes through Make's AWS infrastructure in EU or North America, limiting use for strict compliance environments that require on-premise data processing outside the Enterprise on-prem agent.