
Unstructured
Helping developers quickly engineer their data so it’s ready for data science.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor | €0.0 | round |
investor | €0.0 | round | |
investor investor investor investor investor investor investor investor investor | €0.0 | round | |
* | $40.0m | Series B | |
Total Funding | 000k |
USD | 2023 |
---|---|
Revenues | 0000 |
EBITDA | 0000 |
Profit | 0000 |
EV | 0000 |
EV / revenue | 00.0x |
EV / EBITDA | 00.0x |
R&D budget | 0000 |
Source: Dealroom estimates
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Unstructured.io operates in the data preprocessing and machine learning sector, focusing on transforming raw natural language data into formats ready for machine learning applications. The company serves developers and data scientists who need to process various types of unstructured data, such as HTML, PDFs, CRM data, XML, PPTX, and DOCX files.
The market it operates in is the data engineering and machine learning industry, which is rapidly growing due to the increasing need for data-driven decision-making. Unstructured.io's business model revolves around providing open-source libraries and APIs that enable users to build custom preprocessing pipelines. These pipelines can be used for labeling, training, or production machine learning workflows.
Revenue is generated through a combination of subscription fees for premium features, enterprise solutions, and possibly consulting services to help organizations implement and optimize their data preprocessing workflows.
The platform's key features include rapid orchestration of preprocessing pipelines using machine learning models, cleaning scripts, and regular expressions. It also offers seamless integration with downstream services, ensuring that data remains secure throughout the process.
By enabling users to publish their own APIs and format data for ingestion with various machine learning services, Unstructured.io aims to make it easier for organizations to leverage unstructured data at scale.
Keywords: data preprocessing, machine learning, natural language processing, unstructured data, APIs, open-source, data engineering, customizable pipelines, data security, developer tools.