As of May 2026, there are 25 SaaS companies in Data Extraction Software. They have combined revenues of $474.6M and employ 3.1K people. They have raised $1.1B and serve 6.8K customers combined.
Data Extraction Software is designed to enable the automated extraction of structured and unstructured data from various sources, such as documents, websites, and databases. These tools are essential for businesses seeking to convert raw data into usable formats, facilitating better decision-making and operational efficiency. Common use cases include gathering insights from customer feedback, enabling competitive intelligence, and ensuring compliance with regulatory requirements. Typically, data extraction software includes features such as data parsing, data cleansing, and integration with other analytics tools. It automates tedious data entry tasks, reducing the potential for human error and significantly increasing the speed of data processing. The primary users of this software often include data analysts, business intelligence teams, finance professionals, and IT departments tasked with data management.
Sorting: Highest -> Lowest
Showing 10 of 7 companies ranked by annual revenue.
Beijing, China
Developer of a big data platform designed to provide data analysis services. The company uses big data technology to provide enterprises with data analysis service and big data solutions including data computing, data processing and data application, enabling clients to improve data management efficiency and make accurate decisions.
Pittsburgh, Pennsylvania, United States
Etlworks is a cloud-native, easy-to-use cloud data integration service that can work with business applications, databases, structured, semi-structured and unstructured data of any type, shape, and size.
Silicon Slopes, UT, United States
Carve is a data engineering ops tool built for Snowflake that helps you manage and orchestrate the data lifecycle within Snowflake. Within Carve you can build and schedule data pipelines using SQL, Python, or DBT, fully catalog your Snowflake data assets including lineage, usage, and security, and optimize Snowflake warehouse usage and performance.
Waterloo, Ontario, Canada
Developer of an intelligent database management platform designed to increase project success and reduce risk. The company's intelligent database management platform develops a search engine that helps indexing of data, fast data discovery and cleansing, enabling businesses to get a faster, better and significantly lower costs data management software.
United States
We are a ISV for real time data connecting from any plateforme to any plateforme.
Chicago, Illinois, United States
StarfishETL is a full-featured, ever-evolving solution for connecting data in a way that’s scalable, timeless, and completely versatile. The StarfishETL vision is to empower businesses by integrating systems, cleaning and filtering data, migrating databases, and making sense of millions of data points to foster educated business decisions and optimal customer experiences. With over 350 connectors, its framework supports projects — no matter the size or complexity — with its Cloud, on-premises, and hybrid capabilities. StarfishETL’s migration functions are robust, allowing users to transfer enterprise-level loads of data or restrict the migration to smaller data sets at their discretion. We continue to release new functionality and connectors to simplify and speed up integration and migration projects.
Spokane, Washington, United States
Provider of next generation patent tools intended to offer patent data and analytic algorithms through API integration. The company's platform provides access to a world-class semantic search engine without needing to worry about infrastructure management and complicated optimizations, enabling companies to claim text analytics, automated due diligence and clean patent data all available at an API endpoint.
- Must automate the extraction of data from multiple sources including documents and websites - Should provide tools for data cleansing and formatting to ensure usability - Must enable integration with other software tools for analytics and reporting - Should allow for varying levels of data structuring depending on user needs - Must support compliance and regulatory data requirements in relevant industries - Not just for basic data collection; must also provide means for data analysis or reporting
Each Tuesday, we reverse-engineer a real SaaS company's revenue, profit, CAC, funnels, and its top growth tactic.
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