AI report. Unstructured data. Big data earnings calls.
Scribbles ‘N Bits
One more thing about the Flatiron deal: Flatiron became a valuable company because it structured and cleaned data that existed in EMRs as well as even messier data including doctor’s notes, radiology reports, and lab results.
Healthcare is absolutely chock-full of areas where there are zero data standards, data is messy, or data is fragmented.
This is why I’m always skeptical of startups that claim to take data from a bunch of different unstructured sources and produce results. One route is for them to create a custom solution for each client. That would include A LOT of data scrubbing and so be hard to scale. Or the solution they’re building is so simple that it’s not super-defensible.
On the side of the client, it’s risky to partner up with a startup that may be a flash in the pan, especially if the time and cost of implementation is really high.
I think we’re much more likely to see success stories from companies using “home-built” AI on their own data.
One area we’re seeing this is in medical devices, where new companies are using AI on top of the data they capture to detect anomalies in their own specific data streams that are associated with specific diseases.