Our popular showcase is back for it’s second year and bigger than ever!
The AI Product Showcase brings together companies and attendees on the first night of the conference to enjoy music, food, drinks, and technology. Featured showcase companies will have the opportunity to live demo their product with our audience, receive valuable feedback, find potential product contributors and talent, and connect with data scientists and companies looking for solutions. Companies must apply and be accepted to exhibit.
A high attendee-to-exhibitor ratio allows for ample opportunities to connect one-on-one and showcase the uniqueness of your product.
Syntasa enables you to bring all of your marketing cloud data into your big data environment, consolidate that data, produce a unified identity graph, and apply AI models to transform it all into intelligent experiences.
Conscia creates a 360 view of content and digital information from siloed backend systems such as PIM, DAM, CMS, ERP, etc and allows domain experts such as content and product managers to enrich this unified content for optimal search, analytics and personalization. Conscia offers AI-powered content enrichment features such as
Natural Language processing to extract insights from unstructured data and machine learning to classify the content into domain specific taxonomies and categories. These functions are traditionally understood, developed
and used by data scientists, however Conscia aims to disrupt this space by democratizing this capability to business and non-technical users.
recoMD is a real-time, decision-support tool for radiologists, built to fit into radiologists’ workflow. recoMD was developed by radiologists and the RP data science team for radiologists, with the primary goals of: (i) Increasing standardization of patient care, and (ii) Increasing efficiency and automation of common reporting functions so that radiologists can save time on the overhead of report creation, thus allowing more time for quality interpretation.
Icarus is an interactive data completion system that eases human effort in filling in missing values in large datasets. It shows high impact, relevant subsets of the dataset so that the user can make edits without having to navigate a large dataset. It leverages the database structure to generalize the user’s single edit to multiple cells through suggested semantic if-then rules, thereby reducing user effort and time. It is currently being used to complete multiple microbiology datasets at Ohio State’s Biomedical department.