Obviously AI is a no-code AI Data Processing and predictive analytics platform for business teams, founded in San Francisco in 2019 by Harshit Bhavsar and Tapan Pandita. Users only need to upload CSV files to automatically train machine learning models to predict customer churn, sales, credit risk and other business results without writing code, starting from $75/month.

Obviously AI — No-code predictive analytics, AI data tools for business people

Core parameters and statistics

Parameters	Details
Founded	2019
Founders	Harshit Bhavsar, Tapan Pandita
Headquarters	San Francisco, USA
Core positioning	Code-free AutoML, for non-technical business teams
Supported task types	Classification prediction (churn/conversion), regression prediction (sales/price)
Data input method	CSV file upload to Google Sheets Connect to Salesforce integration
Model interpretability	SHAP value visualization, feature importance ranking
Free trial	Yes
Paid to start	Starter $75/month; Pro $999/month
Support Platform	Web Interface REST API

Obviously AI's core value proposition is very clear: allowing business analysts, market operations, and sales managers who do not understand programming and machine learning to directly use AI predictive models to make data-driven business decisions without waiting for scheduling by the data science team.

User and market recognition

Obviously AI has high ratings on platforms like Product Hunt and is rated as one of the most user-friendly AutoML tools for non-technical users. Founder Harshit Bhavsar’s multiple blog posts on no-code AI were widely circulated in the data analytics community, building organic brand awareness of the product.

Typical user stories of the product include: the e-commerce team used Obviously AI to build a customer churn prediction model without a data scientist, increasing customer retention rate by 20%; the SaaS company sales team used it to predict which leads are most likely to convert into paying customers, focusing sales resources on high-probability conversion objects. The automatic feature engineering function of AutoML v2 further lowers the barrier to use, allowing even users with no data cleaning experience to obtain higher-quality prediction models.

Cost advantage

Plan	Price	Key Benefits
Free trial	$0	Limited data set trial, core function experience
Starter	$75/month	Unlimited CSV uploads, basic AutoML, predictive downloads
Pro	$999/month	Full functionality, API access, real-time forecasting, Salesforce/Sheets connection, team collaboration
Enterprise Edition	Customized Quotation	Private deployment, dedicated support, custom integration, high-concurrency API

Compared to hiring a data scientist ($100,000-$200,000 per year) or outsourcing a data analysis project (tens of thousands of dollars per project), Obviously AI's $75-999/month subscription is extremely cost-effective to achieve equivalent predictive capabilities. For SMBs and teams without data science staff, Obviously AI is the most cost-effective entry point into predictive analytics.

Main functions

• Codeless AutoML Workflow: Core function, complete AI model training in three steps: Upload CSV file → Select the target column to be predicted → Click Run, the system automatically completes data cleaning, feature engineering, model selection and training optimization.
• Automatic Feature Engineering (AutoML v2): Automatically extract, transform and combine features with high predictive value from raw data, eliminating the need for users to manually construct features, significantly improving model accuracy, and is especially suitable for scenarios where the quality of the original data is not high.
• Model Interpretability (SHAP Visualization): Provides visualization of SHAP (Shapley Additive Explanations) values, allowing business users to understand which features have the greatest impact on prediction results (for example: "Customer age and last purchase date have the greatest impact on churn rate"), making AI prediction results credible and actionable.
• Real-time Prediction API: Deploy the trained model as a REST API endpoint with one click, support real-time prediction requests for a single record, and can be embedded in CRM, marketing automation or custom business systems.
• Batch prediction download: Upload new data files, the model automatically generates prediction probabilities for each record, and the results are downloaded in CSV format, which is suitable for scenarios where predictions are updated in batches on a regular basis.
• Salesforce Integration: Directly connect to Salesforce CRM data to predict the conversion probability of sales leads or score customers at churn risk, without the need for data export and import.
• Google Sheets connection: Supports reading data directly from Google Sheets for training and prediction, integrating into the data workflow most commonly used by non-technical teams.
• Multi-type prediction support: Supports major machine learning task types such as binary classification (Will it be lost? Will it be converted?), multi-classification and regression (What is the sales volume? What should the product price be?).

Model and version evolution

Milestone	Time	Description
Company Founding	2019	Harshit Bhavsar + Tapan Pandita Founded in San Francisco
Platform online	~2020-06	Code-free AutoML product release, CSV upload core workflow
Seed Financing + API	~2021-06	Seed round financing, REST API open, Sheets/Salesforce integration
AutoML v2	~2024-06	Automatic feature engineering, SHAP interpretability, API performance optimization

Technical advantages

Minimalist end-to-end AutoML wrapper: Obviously AI condenses the work that typically takes data scientists days or even weeks to complete (data cleaning, feature engineering, model selection, hyperparameter tuning, model evaluation) into a single-page form operation. This extreme ease of use is achieved not by reducing model quality, but by automating the AutoML process behind the scenes to execute industry best practices.

Business Oriented Interpretability Design: Most AutoML tools are geared towards technical users and provide technical metrics (AUC, F1 Score, etc.). Obviously AI's SHAP visualization is deliberately designed as business language ("The most important predictor is...") to help business decision-makers without a statistical background understand and trust AI prediction results. This is the key to whether no-code AI tools can truly be adopted by non-technical users.

Low threshold for real-time API deployment: The function of generating API endpoints with one click after training is completed enables non-technical teams to embed AI prediction capabilities into actual business processes without the need for developers to participate in deployment, greatly shortening the time from "training models" to "using predictions".

How to use

Entrance	Description
Web platform	Visit https://www.obviously.ai, register and upload CSV directly to start training
Google Sheets connection	Connect Google Sheets in the platform to read data directly from spreadsheets
Salesforce Integration	Connect to Salesforce via OAuth authorization and select CRM data objects for prediction
REST API	After obtaining the API Key, call the prediction endpoint to integrate the model into your own system

Typical usage steps (e-commerce customer churn prediction):

1. Visit https://www.obviously.ai, register an account and select the Starter plan.
2. Export customer data CSV from the database (including fields such as purchase frequency, latest purchase date, customer unit price, customer age, etc.).
3. Upload the CSV to Obviously AI and select the "churn" column as the prediction target.
4. Click "Train" and the system automatically completes all AutoML steps in the background (usually 2-10 minutes).
5. Review the model accuracy report and SHAP feature importance analysis to understand which factors affect churn the most.
6. Upload the customer data for the next month, download the churn probability prediction of each customer in batches, and guide the customer success team to prioritize high-risk customers.

Product Pricing

Obviously AI offers three tiers of pricing, ranging from personal trials to enterprise-level deployments:

• Free Trial: After registration, you can experience the core functions. The amount of data and number of predictions are limited, which is suitable for evaluating whether the product meets your needs.
• Starter ($75/month): For individual analysts and small teams, supports unlimited CSV upload and model training, can export batch prediction results, and is suitable for periodic prediction scenarios that do not require APIs.
• Pro ($999/mo): For teams who need real-time predictions and deep integration, includes REST API, Salesforce and Google Sheets connections, team collaboration capabilities, and is suitable for mid-sized enterprises looking to embed AI predictions into business systems.
• Enterprise (custom offer): Private deployment options, dedicated SLA, custom data connectors and high-concurrency API quotas, for large enterprises and organizations with strict data security requirements.

Application scenarios

1. E-commerce customer churn prediction and retention intervention E-commerce platforms or DTC brands use Obviously AI to train customer churn prediction models and generate churn risk scores for all active customers every week. The customer success team prioritizes follow-up with high-risk customers based on the scores and reduces the churn rate through personalized offers or proactive communication.

2. B2B sales lead conversion rate prediction The SaaS company's sales team uploads historical lead data (industry, company size, website visit behavior, etc.), trains a conversion probability prediction model, automatically scores new leads, and helps sales representatives focus their limited time on the highest-value potential customers.

3. Credit risk assessment automation Financial institutions or P2P lending platforms upload historical loan data (applicant information, repayment records, default situations) to train default prediction models, automatically score new applications, assist credit approval decisions, and reduce the subjectivity and workload of manual review.

4. Inventory demand forecast optimization Retailers or manufacturers use Obviously AI to perform regression predictions on historical sales data, predict the sales volume of each SKU in the next cycle, optimize stocking decisions, and reduce the risk of inventory overstock and out-of-stock.

5. Marketing activity effect prediction Before the event goes online, the marketing team uses historical marketing data to train a conversion rate prediction model to predict the response probability of the target audience to achieve precise audience reach and improve marketing ROI.

Applicable people

• Business Analysts and Operations (no coding background): Obviously AI’s core users are able to independently complete predictive analytics projects without the involvement of data scientists, significantly expanding the organizational accessibility of AI technology.
• Small business owners and department heads: Don’t have the budget to hire data scientists but need data-driven decision support, the starting price of $75/month provides cost-effective AI analysis capabilities.
• CRM and Sales Ops: Salesforce integration enables sales teams to increase sales productivity using AI lead scoring without leaving the CRM workflow.
• Startup companies and small digital teams: In the early stages, data-driven hypotheses need to be quickly verified, and Obviously AI’s rapid iteration capabilities (the complete process of uploading → training → prediction can be completed within one hour) is suitable for the pace of entrepreneurial teams.
• Unsuitable Scenarios: AI applications that need to process unstructured data (images, text, videos) (Obviously AI focuses on structured tabular data); high-level data science teams that require deeply customized model architecture and hyperparameter control (DataRobot or directly using the Python machine learning library is more suitable); enterprise-level scenarios that require real-time big data stream processing (millisecond-level high concurrency) (need to evaluate the processing capacity upper limit of the Pro/Enterprise plan).

Summary and Outlook

Obviously AI has effectively lowered the threshold for using AI predictive analysis from "data scientists are required" to "anyone who can use Excel can operate it" through a minimalist no-code AutoML workflow, establishing a clear positioning in the no-code AI tool track. For small and medium-sized enterprises and business teams that do not have data science staff but have real predictive analysis needs, Obviously AI provides a very low-entry and cost-controllable AI analysis starting tool.

Current limitations: Focusing on structured tabular data means that it cannot handle increasingly important unstructured data (text sentiment, image recognition); the price jump between Pro version $999/month and Starter $75/month is large, and the middle range is missing; model training is not as customizable as professional AutoML tools (such as DataRobot); AutoML's model performance may be unstable for data sets with poor data quality or extremely small sample sizes.

Follow-up focus: the introduction of natural language query data analysis capabilities ("Ask in Chinese, AI automatic analysis"); the expansion of native integration with more business systems (HubSpot, Shopify, Zendesk, etc.); the improvement of model monitoring and retraining (model drift detection) functions to help users maintain the prediction accuracy of long-term deployment models; and the strengthening of differentiated positioning in the context of intensified overall competition in the AutoML track.

Version Info

• AutoML v2 (automatic feature engineering version) ：Launched AutoML v2, introducing automatic feature engineering capabilities, the system can automatically extract and combine high predictive value features from raw data, significantly improving model accuracy; a new model interpretability panel (SHAP value visualization) is added to help business users understand which factors have the greatest impact on prediction results; API response speed is optimized to support real-time prediction requests. （~2024-06）
• Seed financing version (API open) ：Completed the seed round of financing and officially opened the REST API for developers and enterprise system integration; added a real-time prediction API (deploying the trained model as an API endpoint to support real-time prediction of a single record); launched a data connector to support direct connection to data sources such as Google Sheets and Salesforce. （~2021-06）
• The platform is officially launched ：Obviously the AI ​​platform is officially open to the public, launching the core code-free AutoML workflow: Upload CSV → Select target column → Automatically train classification and regression models → Download prediction results; it focuses on supporting two major business scenarios: customer churn prediction and sales prediction, for non-technical business analysts. （~2020-06）