LAYAR

Deep Learning Artificial Intelligence Data Fabric Architecture

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Next-Generation Data Fabric Architecture

With the ever increasing velocity and diversity of data, organizations need to catalog, manage and apply advanced analytics across diverse, distributed sources in order to gain critical insights and enable high-value business decisions.

Introducing Vyasa Layar, a next-generation data fabric architecture that can be deployed across cloud and on-prem environments to enable secure, highly-scalable data management, cataloging, metadata tagging, analytics and content indexing across the full landscape of an organization’s most critical asset, its data.

Seeing, managing and utilizing the full tapestry of data within an organization is challenging. Vyasa Layar brings together cutting edge A.I. analytics with powerful cloud-native data management and cataloging to give organizations a bird’s eye view of their critical data assets, where they reside, their metadata properties and their A.I. derived content patterns, thereby providing valuable insights for critical business use cases and management functions.

Deep Learning A.I. Powered Data Fabric

Layar utilizes a library of deep learning A.I. agents applied to the text, image, tabular, quantitative and other types of content that the data fabric connects to in order to derive insights and mine relationships directly from data where it resides.

Extensive REST-ful API

Layar’s extensive API set enables a wide range of programmatic use cases, integration with third-party analysis / visualization tools as well as development of custom applications for focused use cases in areas such as life science, healthcare, legal, competitive intelligence and pharmacovigilance. Vyasa has developed two applications that work against the Layar API, Synapse and Cortex.

Flexible Deployment Options

Layar can be deployed as a fully containerized Helm/Kubernetes stack on cloud environments including Google Cloud, AWS and Azure or on-premise.

API / Microservices Architecture

Layar provides an extensive set of API calls and microservices to enable flexible deployment and custom or third-party application integration.

AWSGoogle Cloud PlatformMicrosoft Azure
On-prem StackLayar API

Breast Cancer Detection

Detection of breast cancer on screening mammography is challenging as an image classification task because cancerous tissue only represents a small portion of the tissue in the image. Cortex rises to the challenge with localized tiling to deliver state of the art results.

Crystal Morphology Classification

Microscopic images of drug crystals are generally evaluated and classified by subject matter experts, a bottleneck in the process that Cortex can help solve.

Identifying Emergent Companies and Patents

Automated identification of emergent technologies, patents, and companies from unstructured text can be challenging. Synapse can uncover even the most obscured similarities between technologies hidden deep in documents, making discovery efficient and effective.

Google Big QueryFHIRAmazon S3

Dynamic Data Connector Framework

The flexible and extensible nature of Layar’s data fabric architecture allows for the creation of secure connections from Layar to a wide range of sources including Google BigQuery, FHIR healthcare data repositories, AWS S3 buckets, internal document repositories and data streams, thereby enabling dynamic continuous availability and visibility of the aggregated Layar data fabric.

Pre-Built Master Layar Data Fabric Sources

Vyasa offers access to a set of pre-built master Layar data fabric sources that can be easily added to unique client data fabric systems. Each master Layar source is continuously fine-tuned against the data modeled from that source. We are constantly adding novel sources to this library of deep learning BERT-modeled sources.

Learn more about Layar Master Data Sources

The National Institute for Health and Care Excellence (NICE)PubMed AbstractsPubMed Central (PMC) Open AccessClinicalTrialsUS Patent Office (USPTO)PubChem

Dynamic Compute Technology

Deep learning models typically require substantial computing power for pre-training and ingestion of novel texts, which can be expensive if a company attempts to build and train algorithms from scratch. Layar avoids this with its hybrid GPU/CPU architecture and GPU Smart Switching capabilities, which allow deep learning training and model utilization to run seamlessly and efficiently.

Support

Vyasa Analytics has over a decade of data analytics expertise available to design and deploy deep learning software. We offer support from our experienced engineers and solution architects, who can advise you on strategy, implementation, and development of our software to optimize its functionality for your use cases.

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