From unstructured data
to actionable intelligence
Extract information from documents, images, emails, social media feed, and many more sources.
Reduce your OPEX by 70% and time-to-market by 5X while improving information capture accuracy by 30%.
Trusted by Fortune 500 Clients.
How does it work?
Use Foreseer connectors for google drive, box, web scrapers, feeds, email listeners, twitter feeds, and many more data sources.
Configure document sourcing rules
Document Sourcing Module
AWS S3 Buckets
Combine state of the Art Deep Learning and NLP based models to extract data from tables, footnotes, running text, graphics, and snippets.
Foreseer's Data Extraction Models
Graphics and Snippets Extraction
Or, build and use your own models
Data Extraction Module
Transform, Aggregate, Link, Summarize, Analyze extracted data using Python or any tooling of your choice.
Create and maintain data processing rules
Data Customization Module
Create and maintain data quality checks
Validate using our intuitive user interface or using Python scripts.
Data Quality Module
Distribute data in a variety of formats or store the data directly in your internal datastore.
OWNERSHIP DATA EXTRACTION
Extract ownership data from PDFs, Html, Document Scans from filing of public companies from around the world.
Effectively created a pipeline based system for processing documents in near real time from around the world.
Built machine learning models for effective table extraction, dates detection, named entity analysis.
Built deep learning model for data extraction from long text statements.
Built rich and powerful UI for data validation and correction and operational reports.
Across three Fortune 500 enterprises and multiple smaller companies, Foreseer processes over twenty million PDF and HTML pages every month with content sourced from 35 countries in 12 different languages.
Major Oil Drilling Corporation
Information extraction system for our semi structured reports was exemplary and easy to use.
Major Global Financial Institution
Our Process automation for handling hundreds of thousands of PDF, HTML, Scans in near real time was tremendous efficiency gains for us
Long Short Equity Fund, NYC
Handling of Tweeter feed data for sentiment analysis -- from labeling services to model build in a month was beyond our expectations.