Rows?

KINDAYou can build the valuable core, but the established product has meaningful operational complexity. Pick one narrow promise for v1.

BUILD FIRST

One specific customer type and one primary use case
A vertical slice that completes the main job without manual workarounds
Visible limits, review steps, and a fallback when an external dependency fails

LEAVE FOR LATER

Broad third-party integrations
High-scale collaboration, syncing, and permissions
Automation that can cause harm without human review

RESEARCH NOTES

What this tool actually does.

Checked 2026-09-06

Rows (rows.com) is a browser-based spreadsheet marketed as 'your new AI Data Analyst.' It pairs a spreadsheet grid with live data from 50+ sources (Stripe, Salesforce, Google Analytics) and public datasets (LinkedIn, Google Maps, Hunter), refreshed on a schedule. Differentiators: typing '=' in a cell lets users describe intent in natural language to fix formulas, generate charts, extract insights, add AI formula columns, join tables, tag/classify text, and run sentiment analysis; a built-in Python engine supports cohorts, forecasts, and advanced stats without leaving the grid. Workflow features: guided function builder, GET/POST/PUT API functions, a Rows REST API, CSV/XLSX import/export, sort/filter, conditional formatting, CMD/CTRL+K command palette, flexible layout/elastic grid, real-time collaboration with workspaces/folders/permissions, interactive cells (buttons, checkboxes, inputs)

SOURCES

RESEARCHED BUILD PROMPT

Give this to your coding agent.

Build a web app inspired by the Rows (rows.com) workflow: a spreadsheet where users connect data and get AI analysis triggered from inside a cell. Core flow: the user lands on a grid, loads or pastes tabular data (CSV/XLSX upload or a mocked 'imported data' button), types '=' in a cell and describes an intent in natural language (e.g., 'top 5 rows by revenue', 'add a column tagging sentiment'), and an AI agent resolves that into a formula, transformation, or direct answer shown inline in the cell. User-facing requirements: formula bar plus grid editing, sort/filter, conditional formatting, AI-generated formula columns, an AI-driven chart panel, CSV export, and a read-only publish/share view. Technical requirements: React with a grid library (AG Grid or Handsontable); a Node/Express or Python/FastAPI backend that owns sheet state and proxies an OpenAI-compatible LLM endpoint, sending the table schema plus a few sample cell values and receiving valid spreadsheet formulas or transformation steps; use a deterministic engine (HyperFormula) to execute computed cells so the AI only proposes formulas the engine then runs; include an evaluation harness with fixed sample datasets (sales, feedback, events) to sanity-check AI outputs. Deliberately out of scope: real third-party connectors, multi-user real-time collaboration, a production-grade formula parser/autocomplete, and any pixel-matching of Rows' visual identity. Do not copy Rows' brand, logo, marketing copy, proprietary assets, or UI layout. Deliver a README covering setup (env vars incl. LLM API key), how the '=' AI cell workflow works, and important limitations (AI output can be wrong, unsupported formulas, no auth, no persistence).

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