Why Healthcare needs a 'Palantir'

Data integration as a service – not AI Agents – will transform the industry

The conventional wisdom in Silicon Valley is that you should build pure software businesses. High margins, scalability, network effects – the standard playbook. But this misses a crucial insight: in complex industries like healthcare, software alone rarely solves the fundamental problems.

Palantir's model reveals why. They discovered that embedding engineers directly with customers – living in their world, understanding their workflows – was essential to building transformative solutions. This wasn't a failure of product-market fit; it was a recognition that context is a scarce resource.

At the time, this methodology was radical. Engineers didn’t sit in some fancy office in SF. They were deployed. Not for occasional visits, but for months at a time. These forward-deployed engineers spent their days in manufacturing plants, government offices, and client sites, experiencing firsthand how their customers actually operated.

One could argue, healthcare is an order of magnitude more complex than government. The organizational dynamics, regulatory constraints, and entrenched workflows make it nearly impossible for pure software companies to drive real change. Every health system is different. Every workflow has its quirks. Every state has its own regulations.

I believe there’s an opportunity to build the next ‘Palantir’ but for healthcare.

The Data Problem

The "data problem" in healthcare perfectly illustrates why this approach is necessary. Everyone talks about how messy healthcare data is. But just like Palantir discovered in other industries, the real challenge isn't technical – it's organizational. Getting access to and cleaning data requires navigating complex politics, working with privacy officers, compliance teams, and clinicians who are rightfully protective of patient information.

Walk into any hospital and you'll find critical patient data scattered everywhere: physicians' notes scribbled on rounding sheets, nurse handoffs on scraps of paper, patient intake forms, whiteboards containing crucial patient status information that disappears when erased. This isn't ancient history – it's healthcare in 2025. The "digital transformation" everyone talks about often means just scanning these papers into PDFs, creating a façade of digitization without actual utility.

Data is ‘barely digitized’ — existing as scanned PDFs in document management systems. Fine for regulatory compliance, but useless for actual analysis. Even more frustrating is data locked in legacy departmental systems. Each department has optimized for their own workflows, creating dozens of isolated data islands within a single hospital. Ironically, every new software vendor actually makes this problem worse. Each new tool becomes another silo, another source of fragmented data that needs to be integrated. Health systems already struggle to connect their EHR, billing systems, and operational tools – adding more point solutions just creates more integration headaches. It's the enterprise software equivalent of treating the symptom rather than the disease.

Palantir cracked this in manufacturing by building a Lego-like system for data integration. Instead of creating another end-product, they developed modular building blocks their engineers could rapidly assemble for each customer's needs. Need to pull data from legacy systems (Epic; which controls 70% of patient records)? Here's your connector piece. Need to transform messy data? Here's your cleaning block. Need to visualize operations? Here's your dashboard module.

Source — @arny_trezzi

This approach meant every new integration made the next one easier, instead of adding complexity. The system got smarter with each deployment while maintaining the flexibility to handle unique requirements. But crucially, it worked because they had engineers on the ground who understood both the technical and organizational landscape.

A pure software approach can't solve this. You need a human in the loop. One that can build trust with clinicians while also writing code. Who can navigate HIPAA compliance while also building AI/ML models.

Sell integration as a service

Palantir's initial work with intelligence agencies revealed a critical problem: analysts spent 80% of their time just trying to get data into a usable form. Each data source required custom integration work, and changes to source systems would break these integrations.

The breakthrough came when Palantir realized they could treat data integration itself as a software engineering problem. Instead of building one-off connectors or writing custom scripts for each data source, they developed a framework where the entire integration process – from data extraction to transformation to security controls – could be defined in code. This approach was inspired by the broader "software-defined" movement that was transforming infrastructure and networking at the time.

By 2010, this evolved into what we now know as SDDI. The core idea was that by making data integration programmable, you could combine the flexibility of custom integration work with the scalability of software. Engineers could write code that defined not just how to move data, but how to clean it, secure it, and make it usable – then deploy and modify these definitions across different environments.

Most AI companies want to skip straight to the fun part: building models and delivering automation. But they're missing the foundational challenge – and opportunity – in healthcare: data integration itself should be the core product.

First, you need to get the data. This sounds obvious until you realize it's often harder to get data access than to close the initial sale. It's not just bureaucracy – these barriers exist for good reasons. Healthcare data is sensitive. HIPAA violations can trigger massive fines. Security breaches can destroy patient trust. When a vendor shows up promising AI magic but can't explain their data governance approach in detail, hospitals are right to be skeptical.

This is why pure software players struggle. They treat data integration as a necessary evil – something to get through so they can sell their "real" product. But in healthcare, data integration is the product. It's the foundation everything else builds on.

Think of it this way: In complex industries, context isn't just king – it's the whole kingdom. The winners will be those who recognize that capturing this context requires boots on the ground, not just bytes in the cloud.