Companies have powerful datasets, but little architecture for harvesting insights

For biotech and healthcare organizations, the hurdles to overcome data connectivity and interoperability challenges are immense. Vyasa Analytics, a 2020 Gartner Cool Vendor for A.I. Core Technologies, has developed a range of software solutions and API services to enable these organizations to make the leap into the application of deep learning A.I. analytics at scale on their data.

The mechanisms to gather and manage data for innovative R&D have evolved rapidly, making it difficult for data intensive environments, such as biotech and healthcare, to keep up. With the exponential volume of data being collected and stored, life science companies continue to curate powerful datasets, but have little architecture to efficiently process and harvest this data for innovative insights. As a result, the landscape of life science data storage has transformed into a messy collection of silos that are difficult to integrate cohesively without breaking down security and systems infrastructure.

These silos of data within an organization have made novel deep learning A.I. approaches, such as bidirectional encoder representations from transformers (BERT), valuable novel approaches for insights and value extraction. In order to enable AI-driven analytics, these organizations need a flexible and bridged solution that manages data with seamless connectivity to their data storage platforms while also providing API integrations for downstream analytics. That’s where Vyasa comes in!

Layar performs sophisticated analytics on data silos without altering existing storage architecture

Layar, Vyasa’s innovative deep learning data fabric engine, can connect to a diverse set of data connectors and third-party applications to provide a flexible data layer on top of data silos and perform sophisticated text and image analytics on the converged dataset without the need for re-architecting an organization’s pre-existing storage solution. The Layar data fabric taps into these silos and performs information retrieval via cutting edge deep learning BERT modeling approaches, which have been fine-tuned by our team of expert data scientists for life science corpora.

Users can run fabric-wide searches on public and private content, perform knowledge graph visualizations via Axon, or interact with the Layar data fabric programmatically via our suite of RESTful APIs.
Vyasa & NVIDIA partnership allows users to run their own models

As an NVIDIA Inception partner, Vyasa offers Layar users an opportunity to run NVIDIA’s novel BioMegatron model in the Layar data fabric. Additionally, our integration with NVIDIA products like NeMo, combined with the compute processing power of NVIDIA DGX hardware, has given our users access to a huge variety of pretrained models to facilitate efficient and transparent fine-tuning of their own domain-specific models as they perform text analytics on the data they’ve connected in Layar

With Vyasa’s cutting edge technologies, life science professionals can preserve the integrity of each independent data repository and empower their data analysts, physicians and R&D scientists with the data they need for their pursuit of biotech and healthcare innovation.

This blog was written in anticipation of the upcoming NVIDIA HLTH Conference. Read more about Vyasa and the other exciting businesses on NVIDIA’s post, “NVIDIA Inception Startups Advancing HLTH with AI”.