Local data loading
Load CSV, Excel, and supported database sources into a desktop workflow before applying analysis steps.
Tomat AI is a desktop data analysis tool for cleaning, transforming, and analyzing CSV, Excel, and supported database data with visual workflows and AI steps. It runs on Windows and macOS and keeps files on the local machine by default.
Tomat AI is a desktop data analysis tool that combines visual workflow building with AI-assisted data preparation. It is designed for people who work with CSV and Excel files, and it also supports PostgreSQL and Snowflake connectors, with access to additional data sources available on request.
The product’s main job is to help users clean, transform, enrich, summarize, and analyze data in a step-by-step interface. The site emphasizes local processing on Windows and macOS, reusable workflows, and AI steps that can handle tasks such as extraction, translation, sentiment analysis, and web research.
Load CSV, Excel, and supported database sources into a desktop workflow before applying analysis steps.
Build reusable pipelines with visual nodes and drag-and-drop steps instead of formulas or code.
Apply AI to one row at a time with prompts for enrichment, extraction, cleanup, translation, summarization, and sentiment analysis.
Use web search inside the AI node when a workflow needs external research, with token usage tied to the selected model and search depth.
Inspect data quality, unique values, distributions, and key statistics while building the workflow.
Add charts, create reports, and export results as PDF from the workflow.
Clean large CSV or Excel files in a repeatable workflow instead of manually editing the same dataset in spreadsheets.
Apply an AI prompt to every row to extract fields, translate text, or generate summaries from tabular data.
Use web search in the AI node to research entities across many rows, then write the results back into the table.
Review data quality, unique values, distributions, and other summary statistics before deciding on the next workflow step.
Build reports with charts and export them as PDF when the workflow needs a shareable output.
Tomat AI works by downloading the desktop app, creating a workflow, and adding a Source node to load a CSV or Excel file. You can then add a Use AI or AI Column step and describe the enrichment, extraction, cleanup, or analysis you want.
The source says Tomat AI is compatible with Windows and macOS.
Yes. Tomat AI supports PostgreSQL and Snowflake connectors, and the site says you can contact the team for access to 450+ additional data sources.
Tomat AI starts with 30,000 trial credits. The pricing page says you can buy additional AI credits on the Solo plan, and the site notes that 1 credit equals 1 token.
The site says Tomat AI keeps data on the local machine, so files never leave your laptop unless you choose to send data to the AI for the task you asked it to do.