Akkio vs Rows

Akkio is aimed at business users who want predictive analytics — forecasting future sales, predicting customer churn, scoring leads by likelihood to convert — without hiring a data science team or writing machine learning code. You connect a spreadsheet or common data source, pick a target outcome (e.g., "will this customer churn?"), and Akkio trains a predictive model automatically, which you can then apply to new data or connect to other tools via its API. A chat interface also allows plain-language questions about your connected data for quicker exploration alongside the predictive modeling. There's no free tier; plans start around $49/mo and scale with data volume and the number of models/users. Compared to chat-first analysis tools like Julius AI, Akkio is more purpose-built for repeatable predictive use cases than ad-hoc exploration, and like any predictive modeling tool, the quality of predictions depends heavily on having clean, sufficient historical data to train on.

Rows keeps the familiar spreadsheet grid but adds native connections to APIs, marketing platforms, and databases, plus an AI layer that can write formulas or summarize data from a plain-language request. It is aimed at teams who live in spreadsheets but are tired of manual data pulls and CSV exports.

• + Build predictive ML models from spreadsheets without coding
• + Plain-language chat interface for data Q&A
• + Pre-built use cases for common business problems
• + Integrates with common data sources and CRMs

• – No free tier
• – Less suited to ad-hoc exploration than chat-first tools
• – Prediction quality depends on input data quality

• + Natural language formulas
• + Live data connections
• + Familiar spreadsheet interface

• – Fewer advanced functions than Excel
• – Smaller integration library