Based on our experience across multiple clients and EMRs, we have been able to deploy our products and demonstrate impact inside of 10 days.

We use both statistical measures common in machine learning and physician sampling.

97% is the current accuracy using human validation methods to confirm outcome was appropriate or not.

Our solutions must be accessible.

We are currently pricing to support implementation & support and ROI based on production deployments is exceeding 15X-20X.

We do not need to do anything with your data beyond using it to evaluate the best configuration options.

We have the ability to use your data to improve the quality of your specific deployment over time, and we can also use aggregated metrics to provide dashboarding tools, but this is not required.

We have a variety of options: interval-based batch files and application programming interfaces (APIs) are most common.

We can also deploy on-prem or using a variety of cloud options.

OpenAI, ChatGPT, and large language models are raising awareness for AI in healthcare. We are excited to monitor these transformative developments in artificial general intelligence.

While we commit to always using the best possible tools for our products, so far we feel confident that our Native AI approach allows us to best manage outcomes for our Clients.

Our platform is purpose-built to address the unique clinical needs of our patients and the teams that care for them. These needs require unwavering adherence to principles long established in our industry - trust, transparency, credibility, authenticity, and compassion. By building our own approach, we understand every facet of our models - how they are built, what data they require, how they were trained, and who trained them, which allows us to deliver superior results for our clients.