Eos AI Launches: Autonomous OS for Hospitals

EOS AI recently launched!

‍

^{"They healthcare system is failing the people it’s supposed to serve. At Eos AI, they are fixing that."}

‍

^{TL;DR: Eos AI helps hospitals turn their historical data into intelligence they can act on, catching operational and care breakdowns before they happen. They create standardized data representations across all systems and time, retrieving similar trajectories to generate actionable forecasts so administrators and physicians can intervene early, save staff hours, and recover revenue.}

‍

Founded by Arya Khokhar

Arya studied Math and CS at Caltech and did a lot of clinical AI and bio research at Stanford and Caltech. As long as she can remember, she has always wanted to be a doctor to help people (cliche, but true nonetheless!), and realized the best way to help as many people as possible is to build a tool that every doctor can use. And super excited to have Professor Kuo from Stanford on board as well!

‍

They are live (bless up!):

In their early clinics, they are seeing ~3x productivity improvements in admin workflows and 37% revenue recovery by identifying early intervention points and automating operational workflows.

#feedourdoctors

Today, hospitals have more data than any other industry in the world, but only 3% has been utilized to inform care decisions. And this is because healthcare is one of the most fragmented systems somehow still in play:

• a single patient’s data sits across EHRs, imaging systems, payer portals, specialty-specific software
• it exists in completely different formats and distributions
• and none of the systems can talk to each other

‍

So what’s the solution: move the intelligence to the data

Eos acts as an intelligent hub that helps healthcare systems collate all their data across fragmented sources, and make intelligent predictions on top of it. They first harmonize data across all platforms to create a unified and standardized patient data distributions and timelines, acting like a translation layer between different applications. Then they build a centralized index over it: a compressed representation that lets petabytes of data stay where they are yet allows us to search and reason across it as one system.

https://youtu.be/i4jSgAeSfMA

‍

What this enables them to do:

Instead of treating the visit or document as an isolated instance, Eos looks at the patient’s full history and compares it to thousands of similar patients over time. It predicts how a case will resolve, triggers the required approvals and actions, and does so while reducing staff workload and recovering hospital revenue.

‍

Learn More

‍

^{Visit www.helloeos.ai to learn more.}

‍

^{They are looking to scale their early successes. If you know anyone who works at health systems or independent clinics, would greatly appreciate an introduction!}

‍

^{Follow Eos AI  on LinkedIn & X.}

‍