Turn your Data into Discoveries, with nSights

Leverage the virtuous confluence of data, tools and expertise on nSights for your next breakthrough

Build Predictive ML Models Train Your AI Models Overcome Clinical Data Silos

Workbench for Feature Engineering and Building Predictive Models

Easily leverage virtual machines designed to support a variety of research goals

Query and analyze data directly in popular coding languages and tools
Run tailored analyses using nSights library of SDK templates
Train models using multimodal patient record-level data for pivotal insights

Suite of SDKs and sample notebooks

Query multimodal data, effortlessly discover variables at scale, and perform specialized tasks using the programming platform.

Flexibility to Operate and Scalability to Compute

• Common Data Science Tools and Custom packages with popular libraries & tools.
• Wide range of computing options from cost-effective minimal resource setups to large, robust, GPU-powered engines.

Project Collaboration Framework

Coordinate team projects with access to shared storage, costing dashboard, role hierarchies, and requests for exporting results.

Suite of SDKs and sample notebooks

Flexibility to Operate and Scalability to Compute

Project Collaboration Framework

Suite of SDKs and sample notebooks

Query multimodal data, effortlessly discover variables at scale, and perform specialized tasks using the programming platform.

Multi-modal Data Labeling Expertise to Build High Quality Datasets for AI Model Training

Streamline your clinical data annotation and AI model development with nSights AI Studio. This multi-modal data labeling platform supports diverse data types, provides robust annotation tools, efficient project management workflows, quality assurance support, and a user-friendly interface for rapidly scaling up the annotation projects.

AI-powered workflows are developed incorporating Segment-Anything Models, custom LLMs, and a variety of other pre-trained models. These semi-automated workflows improve annotation speed and efficiency.
Large-scale text annotation and image labeling projects are handled efficiently with the built-in project-management features. From organizing datasets to assigning tasks and tracking progress, the platform offers intuitive tools to facilitate collaboration and ensure project efficiency.
Resolve discrepancies in annotations with systematic quality validation framework. The adjudication workflow ensures the reliability and accuracy of labeled data by addressing inconsistencies between multiple annotators.

Breaking the Healthcare Data Silos through nSights Federated Network

Finally, a privacy-friendly way to harness multimodal, deeplinked data from leading Academic Medical Centers employing FAIR principles. Edge computing and Common Data Model enables secure sharing of metadata, results and models across the cloud with a network of data partners.

Collaborative Data Science

Federated learning

ML flow framework

Collaborative Data Science

nSights federated analytics is collaborative data science without centralized data collection. In essence, the platform enables the data scientists to answer 1 question across n Data Sources by writing only 1 query.

nSights Data Science Platform turning data into discoveries

Creating a virtuous confluence of data, tools and expertise

Experience in handling complex multi-modal data landscape

Overcome clinical data silos with state-of-art federated techniques