Rows

About

Rows is what Google Sheets would be if it were built in 2026 with AI as a first-class feature. The free tier includes 5 AI tasks per month, manual data imports, 10 integration accounts, and up to 3 guests. Plus ($6/user/month annual, $8 monthly) unlocks 200 AI tasks per month, daily automated data imports, and 10 guests. Pro ($59/month + $6/user annual) jumps to 1,000 AI tasks, minute-level automation, 100 integrations, 200 guests, and video support. Enterprise gets unlimited everything with a dedicated customer success manager and custom API endpoints. The AI features set Rows apart from every other spreadsheet: ask questions about your data in plain English and get instant charts, summaries, and insights. Build AI-powered automations that pull live data from 50+ sources — Google Analytics, Stripe, HubSpot, Salesforce, social media APIs — directly into cells that auto-refresh on schedule. The AI analyst can classify text, extract entities, generate formulas, and even write SQL queries against your data. The interface is clean and familiar to anyone who's used a spreadsheet, which eliminates the learning curve that kills adoption of most data tools. Where Rows stumbles: 5 AI tasks on free is barely enough to demo the product. The Pro tier's base fee ($59/month before per-user costs) prices out solo founders. Performance degrades on spreadsheets with 50K+ rows. And while the AI handles common analysis well, it struggles with complex multi-step statistical operations that Excel power users expect. For teams that need a spreadsheet connected to their entire data stack with AI analysis built in, Rows fills a gap that Google Sheets and Excel can't touch.

Key Features

• AI data analyst that answers questions about your spreadsheet in plain English
• 50+ native data source integrations (Google Analytics, Stripe, HubSpot, APIs)
• Automated data imports on daily or minute-level schedules
• AI-powered text classification, entity extraction, and formula generation
• Live data cells that auto-refresh from connected sources
• Chart and visualization generation from natural language queries
• Shareable dashboards with guest access and embedded views

Use Cases

• 1Marketing teams pulling live Google Analytics and social media data into one dashboard
• 2Founders building real-time revenue dashboards connected to Stripe and HubSpot
• 3Sales teams analyzing CRM pipeline data with AI-generated insights
• 4Developers creating automated reporting workflows with API integrations
• 5Finance teams consolidating data from multiple tools without manual exports