Interconnect disparate data without sacrificing security or infrastructure


Secure, Scalable Solution

Layar is a secure and scalable solution that offers a full suite of reusable data services, pipelines, and APIs designed to provide your company with an elegant and sophisticated software to glean insights from your data.

Layar’s innovative deep learning Data Fabric technology enables companies to streamline the complexities of leveraging disparate data types without having to move, reformat, or modify files. Your data stays in its original location, but the Layar deep learning Data Fabric can access the information within your files to create emergent, powerful, and pervasive business insights.

Tailored Data Fabrics

Manage and connect data across diverse environments by weaving it together into a client-specific data fabric that can tap into a mosaic of private and public pools of data without a dependency on standardized controls or preprocessing.


Hone in to specific sections of unstructured and structured content (such as the executive summary of a PDF, or the metadata for a JPG) to drill down on dataset parameters and model refinement.

AWSGoogle Cloud PlatformMicrosoft Azure
On-prem StackLayar API

Flexible Deployment Options

Utilize your underlying infrastructure — whether it’s on-premises, multi-cloud, hybrid, or a containerized environment. Layar is equipped with several connectors to facilitate ease of integration into your stack.

APIs Available for App Customization

Layar capabilities are also available as API endpoints for programmatic interaction with end-user applications. The API Suite provides access to Vyasa’s most popular DL-assisted capabilities.

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.

Data Ingest for Public & Private Datasets

Layar leverages containerization and clustering technology to ensure seamless and efficient scaling and integration of an unlimited number of data repositories. Layar’s data fabric can process a variety of disparate data types, including but not limited to: XML, PDF, Sharepoint, Twitter, RSS, XLS, TXT, CSV, TSV, DOC, DOCX, and so many more.

We also offer access to the Layar Data Catalog, our off-the-shelf collection of Layar data sources that we use to continuously fine-tune our deep learning models.

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

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.


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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