Build, train, manage AI models and accelerate impact of AI across your workflows
KenSci’s AI platform for digital health is at the core of a healthcare organization’s journey from BI to AI to ROI. KenSci brings a rich set of AI development features that allow for experimental model development as well as testing and production management of in-house developed models. Healthcare organizations can adopt AI within their workflows at their own pace aligned to ROI opportunities.
KenSci’s AI Platform has a rich, clinically validated feature library with 100s of healthcare attributes. Auto-generated by the underlying data pipeline, these features are ready for AI and ML model usage, and provide a quick and easy way to develop AI-based use-cases.
AI platform allows for training datasets that reference the ingested data pipeline as well as public data sets. Training data sets are available in your AI model development workspace and allows sharing, monitoring and tracking during model development and testing.
Clinically and research validated Phenotypes that enable segmentation of underlying data into common use-case applications. Accelerates variation analysis and enables agile experimentation & usage in model development and testing.
KenSci’s AI model engine allows stateless model scoring. This enables hosting of models developed and trained on other data sets to be scored on KenSci managed data pipeline. This helps in bringing in-house projects and experiments to production fostering innovation.
With capability to support real-time data feeds like HL7 and IOMT data, KenSci’s data pipeline aggregates streaming and batch data into a ML pipeline for model development, testing and deployment. This enables a wide variety of real-time data use-cases.
Get started with out-of-the-box pre-built models that come pre-trained and ready for use.Capturing the most common predictive use-cases, these pre-built models help generate AI based insights for use in key workflows immediately.
AI model management platform that allows for model development, testing, deployment, monitoring and maintenance across the lifecycle of a model. This enables data science teams to rapidly bring AI based insights into production workflows seamlessly.
Our experts can guide you through every leg of the AI journey, and help deliver tangible ROI. Talk to us today
Research and other whitepapers on AI Led healthcare transformation
SLUHN is fighting COVID-19 by staying ahead with a real-time command center
September 4, 2020
