At NLPCORE we have focused on two fundamental problems in Life Sciences.
- Lack of precise search tools for Scientists and Researchers to help them identify candidate subject materials for their experiments, and
- Lack of usage information of biomaterials and reagents for their suppliers and manufacturers to help them plan their inventory and make sales recommendations.
Our solution – A Machine Learning / AI technology based search and annotations services platform that
- provides candidate proteins, genes, cell lines, reagents or collaborators for scientists and researchers at low to no cost to them and leverages their expert feedback (built right-in) to continually retrain its core algorithms; and that
- also provides a rich product (biomaterials and reagents) usage information (what products, when, where, how and together with what other products, they were used) extracted from published research (updated monthly, and curated with experts feedback) to their suppliers at a premium – our primary source of planned subscription revenues.
Strategically, our platform is built as a domain agnostic discrete web components (read our blogs at this site) that we are feverishly working on – polishing up their APIs, samples and documentation to publish on this very site. It will allow us to invite a broad base of development community to build their own innovative data analytics components at the bottom, alongside or visualization solutions on the top of our stack, across many industry verticals.
While we are still busy putting final touches to our planned features and publishing our web services, we invite you to take our early release for a spin here at http://beta.nlpcore.com and give us your feedback at firstname.lastname@example.org. Thanks!