Obviously AI Cheat Sheet

MA
Reviewed by Marouen Arfaoui · Last tested April 2026 · 157 tools tested

Last updated: April 2026

Quick Facts

Pricing

Freemium, with paid plans starting at $79/month for the Starter plan.

Free Plan

Yes, includes 1 model, 1,000 predictions/month, and core data prep features.

Rating

4.3/5

Best For

Business analysts and operations teams who need to build and deploy predictive models directly from their spreadsheets without writing code.

Key Features

Tips & Tricks

TIP

Start with their pre-built templates. They perfectly structure your data and problem, saving you from initial configuration headaches.

TIP

Use the automated data prep report to understand what the tool changed in your dataset—it's a great learning tool for data hygiene.

TIP

For time-series forecasts, ensure your date column is clean and in a proper datetime format before uploading for best results.

TIP

Leverage the 'Why' explanation for every major prediction to build stakeholder buy-in and catch potential data issues.

TIP

Connect directly from Google Sheets for iterative modeling; it's faster than constantly uploading/downloading CSV files.

Limitations

Alternatives

DataRobotAkkioGoogle Cloud AutoML Tables
Obviously AI TutorialFull step-by-step guide

Frequently Asked Questions

How much data do I need to build a good model?+
In my testing, you need at least a few hundred rows with a clear target column. For reliable results, aim for 1,000+ rows. The quality and relevance of your features matter more than sheer volume.
Can I use it for time-series forecasting?+
Yes, but with caveats. It works well for straightforward forecasts (e.g., next month's sales). For complex seasonality or multi-variate series, dedicated tools like Prophet or ARIMA might be more flexible.
Is my data secure on the platform?+
Obviously AI uses encryption and doesn't claim ownership of your data. For highly sensitive data, the Enterprise plan offers on-premise deployment. I recommend reviewing their SOC 2 compliance for your use case.
What's the biggest mistake new users make?+
Using messy, uncleaned data. While the tool cleans automatically, garbage in still leads to garbage out. Spend time understanding your dataset's quirks before uploading for significantly better models.
How do I know if my model is any good?+
The platform provides clear metrics like AUC and Accuracy. My rule: an AUC above 0.75 is promising for business use. Always validate with the 'Why' explanations to ensure predictions make logical sense.
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