The startup develops artificial intelligence and machine learning technology for automating data location and extraction processes. By providing services such as data extraction, records management, and automated quality control, the company enables clients to efficiently digitize and manage their data, significantly reducing time and costs associated with manual data handling.
Funding
$430K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations across industries struggle with the time-consuming and error-prone process of manually extracting data from physical documents and scanned images. This challenge leads to inefficiencies, increased operational costs, and delays in accessing critical information for decision-making.
Solution
NthDS offers an AI-powered suite of products designed to automate data discovery, digitization, and delivery, enabling organizations to unlock insights buried within unstructured data. The platform uses machine learning and robotic process automation (RPA) to crawl scanned documents, identify document types, extract metadata, and standardize files. NthDS's solutions facilitate efficient data management, improve data accuracy, and reduce the need for manual data entry, ultimately accelerating data-driven decision-making. The digitized data is delivered on-demand through a searchable online marketplace.
Target Audience
The primary target audience includes data managers and geologists in the oil and gas industry, as well as organizations in the logistics sector dealing with large volumes of documents.
Features
- **Ndex:** An online marketplace for digitized subsurface data, featuring a virtual AI assistant for data interaction.
- **Nspect:** AI-powered document digitization that converts scanned documents into searchable digital data.
- **Crawler:** A document crawler that uses machine learning to recognize document types, extract metadata, and standardize files.
- Automated data extraction from well logs, core data, and tabular data.
- AI-driven quality control to minimize errors and ensure data reliability.
- Web-based interface for easy searching, sorting, and downloading of digitized data.