→How to Migrate from Make (Integromat) to Obviously AI (Step-by-Step)
Last updated: April 2026
Migrating from Make (Integromat) to Obviously AI makes sense when your focus shifts from workflow automation to predictive analytics. While Make excels at connecting apps and automating processes, Obviously AI specializes in turning historical data into actionable predictions without coding. This guide covers exporting your data from Make, preparing it for machine learning, mapping key features, and deploying predictive models. You'll learn how to transition from automation-focused workflows to AI-driven decision-making tools, including timeline estimates and common pitfalls to avoid during migration.
Estimated Timeline
solo user
2-4 hours for data export and model building
small team
2-3 days including testing and documentation
enterprise
2-3 weeks for full integration and validation
Migration Steps
Audit Your Make Scenarios
mediumExport Historical Data from Make
easyPrepare Data for Machine Learning
mediumUpload Data to Obviously AI
easyBuild and Train Predictive Models
easyDeploy and Integrate Predictions
mediumPhase Out Make Scenarios Gradually
hardFeature Mapping
| Make (Integromat) | Obviously AI Equivalent | Notes |
|---|---|---|
| Visual workflow builder | No-code model builder | Make focuses on process automation; Obviously AI focuses on predictive model creation |
| Data transformation modules | Automatic feature engineering | Make requires manual setup; Obviously AI automatically optimizes features for prediction |
| Conditional routing | Prediction thresholds | Make uses if/then rules; Obviously AI uses probability scores for decision boundaries |
| Webhooks and API calls | Prediction API endpoints | Make connects to various APIs; Obviously AI provides dedicated prediction APIs |
| Error handling routes | Model accuracy monitoring | Make handles process errors; Obviously AI monitors prediction performance drift |
| Data aggregation modules | Historical pattern recognition | Make summarizes data manually; Obviously AI identifies predictive patterns automatically |
| Schedule-based triggers | Batch prediction scheduling | Make triggers workflows; Obviously AI schedules regular prediction updates |
Data Transfer Guide
Export data from Make by using HTTP modules to download CSV files from connected apps or accessing Make's data stores. For database connections, use Make's SQL modules to export query results. Clean data in spreadsheet software before import, ensuring proper formatting and removing automation-specific fields. Import into Obviously AI via direct CSV upload or cloud storage connections (Google Drive, Dropbox). The platform automatically detects data types and suggests prediction tasks. For ongoing data transfer, set up automated exports from source systems directly to Obviously AI's storage, bypassing Make entirely.