The Future of Public Health Technology Is More Exciting Than You Think

Program directors who understand their communities better than anyone are spending their days pulling data out of three different platforms to build a report that's already outdated by the time it's done. Case managers who got into this work to help people are buried in paperwork instead of talking to the person sitting across from them. Supervisors who should be asking "is this program working?" are stuck asking "are these numbers right?"

This isn't really a technology problem. The technology works fine. The dashboards look good. The portals are modern. The problem is bigger than that: the software keeps track of what people did, but people still have to do all the actual work.

Every eligibility decision, every compliance check, every step in a workflow, every report — it all depends on staff reading policy documents, remembering their training, and typing information into a system that exists to store their work. Not to do it for them. The system is a filing cabinet. A fancy, cloud-hosted, mobile-friendly filing cabinet — but still a filing cabinet.

There's a better way to do this. And we don't have to guess whether it works, because another industry already proved it does.

What Finance Already Figured Out

Over the last fifteen years, the financial world went through a change that matters a lot for government. Not because finance and government are the same — but because the pattern is the same.

It happened in three stages. First, banks bought software to store records and run reports. Then startups built better-looking apps on top of those same bank systems — nicer screens, but the same guts underneath. Then companies like Stripe and Square did something completely different: they rebuilt how money actually moves, as software. Compliance, fraud checks, tax reporting, regulations — all of it baked directly into the system, running automatically with every transaction. Not tracked after the fact. Not handled by a person reading a policy manual. Done by the software, in real time.

That's the difference between software that helps people follow the rules and software that follows the rules itself, by design.

Government is about a decade behind this curve. But the same pattern is starting to show up.

Where Government Technology Actually Is Right Now

Let's be honest about where most programs are today. Most of the public health and human services programs we talk to are still figuring out how to get off paper — or off an EHR that was never built for their program — and onto something that actually works for them. That's moving from stage 1 to stage 2: going from clunky, bad-fit systems to modern platforms with better screens, mobile access, and cleaner workflows.

That move matters. Nobody wants to go back to fax machines. But even the programs that have made it to stage 2 are hitting the same wall. Under the nice interface, nothing has really changed about how the work gets done. Policy is still a document that staff have to read and interpret. Eligibility is still something a person figures out case by case. Workflows are still just steps people follow because they were trained to. Reporting still means going back through old records to piece together what happened.

The software is just a place to write down what the program did. People still do all of it.

That used to be okay — when agencies had tenured, experienced staff who knew the program inside and out. Every program has those people: the ones who know which workarounds actually work, which edge cases the manual doesn't cover, and how the software was set up in the first place. They carry the program in their heads. But those people are leaving. Retirements, turnover, and hiring struggles mean agencies can't count on having that deep bench anymore. When someone like that walks out the door, they don't just leave a vacancy. They take the program's operating knowledge with them — knowledge that was never written down, never trained to anyone else, and certainly never built into the software.

On top of that, the federal government is pushing harder for real-time data, outcome tracking, and proof that programs are working — and these systems weren't built for that. You can't get real-time compliance data from a system that passively reflects case notes someone entered a week after the fact.

What Comes Next: The Software Does the Work

The next stage — the one finance already went through — changes what the software is actually for. Instead of writing down what happened, the software does the work.

Here's what that looks like, plainly. The program's rules get built into the system. Eligibility isn't something a person has to figure out from scratch every time — the system checks the criteria automatically, and staff step in for the hard calls instead of processing every single case by hand. Workflows aren't a checklist someone hopes staff remember to follow — they're paths built into the software that make sure the right steps happen in the right order, that nothing falls through the cracks, and that exceptions get flagged instead of missed. Reports aren't something you build after the fact — they're available in real time, always current, because the data is created as the work happens.

Think of it this way. A system of record is a place to write down what happened in the program. A system of action is the program — it runs the rules, all the time, automatically.

One more way to say it: right now, all the complexity of government programs — every federal regulation, every state-level rule, every funding requirement, every reporting obligation — lives in people's heads. People read the documents, interpret the rules, and do the work. In the next model, that complexity lives in the software. The software reads the rules and does the work. The first way depends on training, experience, and people sticking around long enough to learn it all. The second way depends on how well the rules were built into the system.

The complexity doesn't go away. But it moves out of people's heads and into the software — where it's consistent, where it can be checked, and where it doesn't leave when someone retires.

This Is Coming Faster Than You Think

If government is a decade behind finance, you might figure there's plenty of time to catch up. There isn't — because AI is speeding everything up.

When finance went through this change, turning business rules into software was slow, expensive work. Every rule, every edge case, every regulation had to be hand-coded by engineers who understood both the tech and the industry. It took years. AI changes that picture completely. AI tools can now read policy documents, help turn regulations into system logic, and catch conflicts across programs at a speed that wasn't possible even two years ago. The thing that slowed finance down — the sheer amount of work it took to build all that complexity into software — is getting easier and faster every day.

That means the stage 3 shift in government won't take a decade. It's going to happen faster than most people expect.

What Happens Next

If government technology follows the same path as financial technology — and everything we're seeing says it will — here's what the next few years look like.

First, the programs that already have modern platforms start asking a new question. Instead of "does the system store our data?" they start asking "why are my people still doing all of this by hand when the system should be handling it?" That question is the early signal. We're already hearing it.

Second, compliance and reporting move from backward-looking to real-time. Funders and federal agencies are already asking for this. The programs that can deliver real-time data will have a huge advantage — not just for audits, but because they'll actually be able to see what's working and make changes. Programs still running last month's reports will fall behind.

Third, AI starts handling the routine stuff that currently lives in people's heads. Not replacing human judgment on tough cases — but taking care of the straightforward decisions, flagging the unusual ones, and filling in the paperwork that eats up staff time today. This is where the staffing shortage stops being a slow burn and becomes an urgent problem for programs that haven't made the shift.

Fourth, the programs that reach stage 3 start clearly outperforming everyone else. Better outcomes data. Faster reporting. Less money spent on admin per case. That gap puts pressure on every other program to catch up — the same thing that forced old-school banks to modernize or lose customers.

This isn't guesswork. It's the same sequence finance went through. The only difference is that AI is compressing the timeline — which means programs that wait to make this shift may not get the runway they're counting on.

Persimmony Is Shaping This Future

We see this clearly because we've lived every stage of it with our customers.

We started by building a modern platform on top of what agencies were already doing — better screens, cleaner workflows, a system that didn't feel like it was built in 2004. That helped, and we're proud of it.

But we kept hitting the same wall: the smartest, most dedicated people in public health and human services were spending their days feeding the system instead of doing their real jobs. A better interface doesn't fix that. A nicer dashboard doesn't fix that. The problem is structural — when the system only records work, all the burden stays on staff.

We saw that wall for what it was: the line between stage 2 and stage 3. And we decided to build through it.

Program rules, eligibility logic, compliance requirements, reporting needs — we are building all of it directly into the platform so it runs automatically. Compliance doesn't have to be tracked through self-reported forms; the system shows you how your compliance is working in real time, as staff do their jobs. Supervisors don't build reports because the reports are already there, always current. Instead of being just a place to write down that work happened, the platform does the operational work — the rule-following, process-driven, compliance-generating work — so people don't have to.

What that frees up is the part of the job that actually needs a human being, and that no software will ever replace: the judgment, the relationships, the face-to-face conversations that are the whole point of health and human services. A case manager who isn't fighting with paperwork has time to actually help the person in front of them. A program director who trusts the data has time to ask whether the program is working — not just whether the spreadsheet adds up.

We're ahead of where most of the market is today. We know that. And we've seen where this is going — in the data, in what the federal government is asking for, in every conversation with program leaders who are tired of technology that creates work instead of doing it. We're not waiting for the industry to catch up. We're building the future of program delivery now, so that the people who run these programs can get back to the people those programs exist to serve.