Used for our own language models, RavenPack Annotations
are specifically designed to address the challenges of working
with unstructured textual content in the business, finance, social,
and legal sectors — from historical archives to real-time feeds.
Pre-annotated by hundreds of thousands of rules, they give you the highest-quality training data.
We spent over a decade crafting the best-in-class text analytics to build NLP models, so you don't have to.
Streamline your machine learning workflows for shorter time to market with the only text annotation infrastructure that delivers:
Preannotated using hundreds of thousands of enterprise-grade, domain-focused, supervised rules
The world's largest Point-In-Time,
annotated archive captured in real time at a millisecond resolution
Comprehensive knowledge graph covering 7 million companies, people, places, and more
RavenPack Annotations are produced by our proven natural language processing infrastructure that has processed terabytes of unstructured data over 15 years.
Explore the significance of training data and its pivotal role in advancing Large Language Models with these articles by RavenPack.
Please use your business email. If you don't have one, please email us at email@example.com.
Your request has been recorded and a team member will be in touch soon.
By providing your personal information and submitting your details, you acknowledge that you have read, understood, and agreed to our Privacy Statement and you accept our Terms and Conditions. We value your privacy and assure you that we will handle your personal information with the utmost care and in compliance with our Privacy Statement. You can exercise your rights of access, rectification, erasure, restriction of processing, data portability, and objection by emailing us at firstname.lastname@example.org in accordance with the General Data Protection Rules (GDPR). You also are agreeing to receive occasional updates and communications from RavenPack about resources, events, products, or services that may be of interest to you.