SheetsGPT has been unveiled by Russian developers as a neural network designed to simplify how people work with spreadsheets. The tool targets professionals who routinely handle tabular data, including accountants, market researchers, and data specialists. The project emphasizes institutional support from the press service of the NTI Platform, underscoring its backing and potential to streamline data workflows in Russia and beyond.
According to project lead Anton Averyanov, SheetsGPT functions as a web service where users upload their tables. The interface also accepts text-based queries, letting users search for specific data points or run calculations without digging through cells and formulas. The aim is to deliver results in roughly 15 seconds, helping professionals move quickly from data to insight.
“This represents a fundamentally different way to work with information”, Averyanov explains. “There’s no need to recall formulas or write macros. Users simply describe what they want to obtain in plain text.”
As development continues, the team plans to enable editing and modification of tables through natural language prompts. That capability would let users adjust values, reorganize data, or recompute calculations by typing commands, without manual edits in a spreadsheet program. The roadmap also contemplates enhanced collaboration features, allowing teams to share queries, track changes, and audit the steps that produced a given result.
Currently in the prototype stage, the project is set to undergo broader testing and explore commercial availability for individuals and organizations alike. The overarching objective is to provide a scalable, accessible tool that speeds up data tasks while reducing the learning curve associated with advanced spreadsheet techniques for users in North America and other markets.
Earlier reports from tech policymakers noted expectations that software would be tuned to run efficiently on domestic processors. This outlook has shaped the project’s development priorities and roadmap, influencing how SheetsGPT integrates with local hardware ecosystems and privacy controls while aiming to deliver robust performance across diverse use cases in North American contexts.