Built for the healthcare data scientist.

ClosedLoop makes it easier for data scientists to build, train, deploy, and monitor more models in faster cycles than any other AI/ML solution available for healthcare.

Why task expert data scientists with reinventing the wheel?

Whether empowering clinician decision-making, risk stratifying for interventions, or optimizing care operations, the insights data science can provide are needed now, not later. So why waste months and years building fundamental healthcare data science tools when ClosedLoop has already built them for you?

Ingest & Normalize

Train and deploy more models by streamlining all of the processes needed to ingest and normalize nearly all healthcare data types.

Enrich & Transform

Utilize tools and critical enhancements to make raw data more clinically and operationally useful in healthcare settings.

Train & Validate (AutoML)

Focus data science efforts on building, iterating, and validating models faster.

Deploy & Monitor (ML Ops)

Automate monitoring and retraining of models to ensure accuracy and minimize disruptions to production.

Ingest and Normalize

If your team is spending precious time ingesting and cleaning raw healthcare data, they can’t focus on training, validating, and deploying predictive models to end-users. Accelerate delivery of real-world clinical impact with ClosedLoop’s rapid ingestion of raw healthcare data, automatic data cleanup processes, and HIPAA-compliant data storage and management.

  • Fast, secure integration and aggregation of data sources
  • Resilient ETL processing for both training and production
  • Error-free integration of data from new sources and organizations

Enrich & Transform

Turning healthcare data into usable ML features is time-consuming, often requires reengineering of data pipelines, and can result in inconsistent feature definitions across models. Leveraging ClosedLoop’s Healthcare Content Library, which includes more than 4,000 feature templates, eliminates any reengineering demands and standardizes data transformation.

  • Prebuilt healthcare features eliminate costly data prep
  • Improved accuracy without lengthy feature development
  • Standardized ML features with free clinical content updates

Train & Validate (Auto ML)

Rapid iteration is the heart of successful ML approaches. Success isn’t a function of overall time spent – it’s about how many attempts you make and how much you can learn from each. ClosedLoop enables you to build, iterate, and validate models as quickly as possible.

  • Prebuilt healthcare features eliminate costly data prep
  • Improved accuracy without lengthy feature development
  • Standardized ML features with free clinical content updates

Deploy & Monitor (MLOps)

Even the finest engines ever built need regular maintenance, and building a model isn’t nearly as difficult as keeping it running. ClosedLoop’s ML Ops tools standardize configuration and integration of model deployments, while automating monitoring and retraining to maintain accuracy.

  • Push-button deployment of model and end-to-end ETL process
  • Proactive mitigation of drops in model accuracy
  • Zero-downtime deployment, accuracy and bias monitoring


How and Why You Should Assess Bias & Fairness in Healthcare AI Before Deploying to Clinical Workflows

Watch the on-demand session to learn why it's important to evaluate algorithms for bias before deployment and what …

Where Most Healthcare AI/ML Deployments Go Wrong

Read the white paper to explore three of the most common ways healthcare AI/ML models go wrong, and how you can ensure …

Case Study — Healthfirst Achieves Agile AI/ML in Healthcare

Learn how Healthfirst’s analytics team has dramatically enhanced its ability to train, test, and deploy AI-based …

Make AI/ML a core element of your care strategy.

Get in touch today to see the ClosedLoop platform in action.