Tomat - 2026 Pricing, Features, Reviews & Alternatives

Tomat is a downloadable desktop application for Windows and macOS that enables data analysts, researchers, and business teams to clean, transform, merge, and enrich Excel and CSV datasets without writing code or formulas. Workflows are built using a visual drag-and-drop editor (Flows) with 20+ transforms and 150+ functions, covering filtering, sorting, grouping, pivoting, merging, and branching. All data processing runs locally on the user's machine, keeping datasets private and under full user control. Cloud execution is supported when connected to Snowflake or PostgreSQL. Connectors for CSV, Excel, PostgreSQL, and Snowflake are included, with access to 450+ additional data sources.

The platform handles datasets of any size, including large files that exceed Excel's row limits, and supports workflow scheduling and a data catalog for reuse across projects. AI capabilities are integrated directly into workflows: the AI Column node applies natural language prompts row by row for enrichment, extraction, cleaning, translation, categorization, and sentiment analysis, while the AI Table node handles complex dataset-level transformations described in plain language. A web search option within the AI node supports real-time data research. Model selection is available for AI tasks, and predictive suggestions assist with column type detection and transformation choices. Charts and PDF reports can be generated within workflows, eliminating the need for separate reporting tools.

Tomat targets individuals, small teams, and enterprise organizations that work regularly with structured data and need to automate repetitive data preparation tasks. Reusable pipelines reduce manual effort across recurring workflows, and the no-code interface lowers the barrier to entry for users with basic spreadsheet familiarity. An enterprise plan is available for larger organizations requiring shared connectors, file sharing among team users, and custom functions.