Obviously AI

Obviously AI

Paid

No-code predictive analytics tool that lets business analysts build machine learning models and generate forecasts in minutes from spreadsheet data.

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What is Obviously AI?

Obviously AI is a no-code AutoML platform aimed at business analysts and small teams with no data science function. You upload historical data as a CSV or connect a source, state the question in business terms, such as which customers will churn or how much a region will sell next quarter, and it selects an algorithm, trains a model and returns predictions with explanations of which variables drove them. Results can be shared, used for what-if simulation and pushed through an API. Two evaluation points. It integrates with common sources including Salesforce, HubSpot, Redshift, Postgres and Google Drive, which matters because the friction in no-code ML is usually data plumbing rather than modelling. And pricing is not published, with plans quoted per organisation, so budget through a sales conversation. As with any AutoML tool, prediction quality depends far more on the history you feed it than on the platform.

Key Features

No-Code AutoMLPredictive Model BuilderFeature Importance RankingConfidence Score OutputWhat-If Scenario SimulationCSV and Excel UploadAPI IntegrationDownloadable PredictionsChurn PredictionSales ForecastingConversion Propensity ScoringModel SharingReal-Time PredictionsEdge-Sharp AutoML TechnologyAutomated Model Evaluation

How to Use Obviously AI

1Upload your historical dataset as a CSV or Excel file
2Select the column you want to predict (e.g., churn, revenue, conversion)
3Obviously AI automatically builds and evaluates multiple ML models
4Review feature importance, confidence scores, and model accuracy
5Download predictions, share with your team, or integrate via API

✅ Best For

  • Business analysts and product managers at mid-market companies who need accurate predictions from their historical data but do not have a data science team or the budget to hire one.
  • E-commerce operators, SaaS founders, and marketing teams who want to forecast churn, identify high-value leads, or predict campaign outcomes using their own CRM or transactional data.

❌ Not For

  • Data scientists and ML engineers who need full control over model architecture, hyperparameter tuning, custom training pipelines, and code-level access to the underlying algorithms.
  • Enterprises with highly sensitive data that cannot be uploaded to a cloud-based platform, or organizations requiring on-premise machine learning infrastructure and air-gapped environments.

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Pricing

Starter$99/mo
  • ✓Core AutoML
  • ✓CSV upload
  • ✓basic predictions
ProfessionalCustom
  • ✓API access
  • ✓scenario simulation
  • ✓team sharing
EnterpriseCustom
  • ✓Dedicated support
  • ✓custom integrations
  • ✓advanced security

Prompts to Try

Predict which customers are most likely to churn next month

Forecast Q4 sales revenue based on last 3 years of data

Which leads in my CRM have the highest probability of converting?

Simulate what happens to churn rate if we reduce pricing by 20%

Identify which product features drive the highest customer retention

Use Cases

A SaaS growth manager uploads 18 months of user activity data to Obviously AI and asks it to predict which trial users will convert to paid, enabling the sales team to prioritize outreach to the top 200 highest-scoring leads.
An e-commerce founder uses Obviously AI's churn prediction model to identify 500 customers likely to lapse within 30 days and triggers a personalized discount email via their ESP, recovering $40,000 in potential lost revenue.
A marketing manager at an insurance company uploads historical campaign response data and builds a propensity model in 20 minutes, improving their direct mail targeting response rate from 2.4% to 6.1%.
A retail operations lead uses the what-if scenario simulator to predict how a 15% price increase on a top SKU would affect demand, getting a confidence-interval forecast in seconds rather than commissioning an analyst study.
A product manager at a fintech startup uses Obviously AI's feature importance output to discover that transaction frequency is the single strongest predictor of premium upgrade, reshaping the product's onboarding flow.

Frequently Asked Questions