SuperAPI AI Directory

Tomat

A No-Code Tool for Data Querying and Analytics Unlock the power of your unstructured data with our innovative no-code tool designed for data querying and analytics. By leveraging generative AI, you can effortlessly analyze and extract valuable insights from your data without the need for complex cod

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About this tool

Tomat is a no-code data query and analysis tool designed to let users analyze unstructured data and extract valuable information without writing code through generative AI.

Main Capabilities

  • Visual step-by-step interface: Users can load CSV files through a click-based UI and perform analysis step by step. It supports data cleaning, extraction, summarization, and sentiment analysis, assisted by a personal AI agent.
  • AI automation: It can automatically process Excel and CSV files to enable large-scale AI runs. It supports batch web research, data enrichment, and cleaning.
  • Prompt optimization and chaining: Users can test prompts on a small number of rows and then apply them to all data. It supports building prompt chains to complete complex multi-step tasks.
  • Process datasets of any size: It supports running AI operations on datasets ranging from 1 row to 1 million rows.
  • Visual workflows: Filter, sort, or group by dragging and dropping steps, and preview results instantly. No need to write formulas.
  • Building complex logic: It supports merging or stacking tables, creating pivot tables, or branching workflows to create segments. No technical skills required.
  • Fast insights: Instantly obtain data quality, unique values, distributions, and key statistics.
  • Instant reports: Add charts directly in the workflow, or build reports and export them as PDF.

How to Use

After downloading the Tomat app, users load CSV files through a click-based UI. There is no need to upload large files to the cloud, avoiding ZIP compression and lengthy loading processes. Then they build visual workflows by dragging and dropping steps, using AI agents for data cleaning, extraction, summarization, or sentiment analysis. Users can test prompts on a small amount of data, then apply them to all data, and build prompt chains to handle multi-step tasks.

Use Cases

  • Data query and analysis: quickly extract insights from CSV and Excel data.
  • Batch web research: automate the collection and organization of web information.
  • Data cleaning and enrichment: use AI to clean and enrich datasets.
  • Report generation: create reports with charts and export them as PDF.

Limitations

According to the available information, details such as Tomat's specific pricing, platform compatibility (such as operating system requirements), and whether an online version is offered are not currently provided.