We left Google to start Delty because the most expensive failures in American healthcare are not clinical. They are operational. They look like a duplicate outreach call to the same patient by three different teams in the same week. They look like a diagnosis that fell off a 2024 problem list and is now untrumped under V28. They look like a 47-step closure window for a single Stars measure that nobody on the floor can complete during a busy clinic morning.

You can hire more nurses, more coders, more analysts. None of it solves the underlying problem, which is that the data is fragmented, the workflow is fragmented, and the AI is glued onto the side of both. Healthcare has spent fifteen years digitizing records and the last three years bolting language models onto everything. The work itself has not gotten meaningfully easier.

What we kept seeing

Catherine spent years at Google building generative AI products and, before that, doing clinical AI research at Stanford School of Medicine and working as a medical assistant at the SF Free Clinic. Lalit spent a decade at Google and YouTube building large-scale distributed systems and AI agents. We came at the problem from very different angles, but we kept landing on the same observation: healthcare operations teams are running 12 spreadsheets per problem, because that is what every vendor's UI eventually collapses into.

The shape of the failure is consistent. A risk adjustment team has a list of suspect HCCs in one system, MAO-004 reject reasons in a second, encounter scheduling in a third, and a payer-specific portal for the actual submission. A quality team has hybrid measure gaps in one tool, ECDS-eligible measures in another, supplemental data in a third, and a chart-chase queue in a fourth. A pharmacy team can see PDC trends but not the EHR notes that explain them. None of these teams can see what the others are doing to the same member.

The buyer is not asking for "more AI." The buyer is asking for "fewer tabs."

What we are building

Delty is the operating system for value-based care. Three layers, by design:

This is not a thin agent on top of a CRM. It is the system of record itself, with the AI sitting inside it.

Why now

Three things converged in 2025. First, V28 entered its final phase, and CMS made it clear that risk score normalization is permanent. Second, NCQA published the ECDS roadmap, which will increase supplemental data volumes 35x to 75x per measure by 2029. Third, foundation models finally got good enough to read clinical text reliably and operate inside structured workflows without breaking. The first two changes make the old vendor stack untenable. The third one makes the new stack possible.

So we started building. A physician-led IPA in New York managing 175,000 patients on a risk-bearing contract took the bet with us. Two quarters in, no new headcount, RAF lifted, gap closure improved 41%, outreach capacity tripled per coordinator, and 12 separate tools and 5 point vendors got retired in the process. That is the story we want to repeat, contract by contract.

An invitation

We are early. The platform is real, the customer outcomes are real, and the road is long. If you are operating a risk-bearing contract and you are tired of running your team off twelve spreadsheets, we want to hear from you. If you build healthcare data systems and you want to work on the part of the problem that actually matters, we are hiring.

The rest of this blog will be short, operator-grade notes on the actual work: V28 traps, RADV chain-of-custody patterns, what we are seeing in PDC adherence, the ECDS data engineering reality. No thought leadership. Just what shipped this week and what we learned doing it.

Catherine Zhao & Lalit Kundu
Co-Founders, Delty Health
founders@delty.ai