Skilled nursing facilities run on care, coordination, and a surprising amount of paperwork. Every referral packet, intake form, clinical note, insurance detail, and claims file can affect how quickly a patient is admitted, how accurately care is documented, and whether a facility is paid fairly for the work it provides.
That is the problem Trent Hazy is taking on with Flax Health. As co-founder and CEO, he is building an AI-powered workflow automation platform designed for skilled nursing facilities, a part of healthcare that is essential but often overlooked by modern software companies.
The idea behind Flax Health is simple to understand but hard to execute well. Skilled nursing teams do not need more tools that create extra steps. They need technology that can read complex clinical information, organize it clearly, and help staff move faster without sacrificing accuracy. For facilities already dealing with staffing pressure, reimbursement complexity, and tight margins, that kind of support can make paperwork feel less like a burden and more like a manageable part of the care process.
Who is Trent Hazy
Trent Hazy is not new to building software around productivity and workflow problems. Before Flax Health, he founded MindSumo, a platform that helped companies run online competitions and innovation challenges. He grew the company to more than 350,000 users and 100 Fortune 500 clients before it was acquired in 2020.
That experience matters because Flax Health is also built around a workflow problem. The difference is that the stakes are higher. In skilled nursing, paperwork is not just internal admin. It touches patient care, admissions, compliance, reimbursement, and financial health.
After MindSumo, Trent Hazy worked on automation and productivity products at Microsoft, including work connected to Microsoft Teams and Microsoft 365. That chapter gave him experience building for large, complex organizations where software has to be reliable, easy to adopt, and useful across different teams. Those lessons carry naturally into healthcare, where even a small workflow mistake can create bigger problems downstream.
With Flax Health, Hazy appears to be bringing those two parts of his background together: the founder mindset from MindSumo and the enterprise product discipline from Microsoft.
What Flax Health is building
Flax Health is an AI-powered workflow automation platform built for skilled nursing facilities. Its focus is not broad, vague healthcare AI. The company is working on specific problems inside post-acute care, especially the heavy administrative work that follows patient referrals, admissions, intake, documentation, and claims.
A skilled nursing facility may receive a referral from a hospital with pages of clinical notes, medication lists, insurance details, therapy needs, behavioral notes, and discharge information. Staff then have to review that information quickly and decide whether the facility can safely and profitably accept the patient. After that, more documentation follows through intake, assessments, billing, and claims support.
This is exactly where Flax Health wants to help. The platform is designed to pull information from messy clinical records, organize the important details, and support the staff members who have to make decisions from that data.
Instead of asking teams to manually dig through every page, Flax Health uses AI to surface the information that matters. That can include clinical risks, referral details, documentation gaps, or information needed for reimbursement. In a setting where teams are often pressed for time, even small improvements in speed and clarity can add up.
Why paperwork is such a painful issue in skilled nursing
The paperwork problem in skilled nursing is bigger than forms. It is tied to how care is delivered, how facilities stay compliant, and how they get paid.
Admissions teams have to review referrals quickly. Nurses and clinicians need accurate patient information. Billing teams need clean documentation to support claims. Operators need workflows that do not collapse under staffing shortages or regulatory pressure. When clinical information is scattered across referral portals, electronic health records, PDFs, and manual notes, the work becomes slow and error-prone.
This is especially difficult in post-acute care, where reimbursement depends heavily on accurate documentation. Under models such as the Patient-Driven Payment Model, facilities need to capture the true complexity of each patient’s condition and care needs. If records are incomplete or details are missed, the facility may provide the care but fail to receive the proper reimbursement.
That creates a frustrating cycle. Staff are already busy, so documentation gets rushed. Rushed documentation leads to missing details. Missing details can lead to denied claims, weaker appeals, undercoding, and lost revenue. At the same time, staff morale can suffer because too much of the workday is spent on administrative tasks instead of direct patient care.
This is the kind of everyday healthcare problem that does not always get attention from the outside. But for skilled nursing operators, it can shape the entire business.
How Trent Hazy is connecting AI with real healthcare work
One reason Trent Hazy stands out in this story is the practical nature of the problem he is solving. Flax Health is not trying to sell AI as a magic layer over healthcare. It is using AI to handle the kind of repetitive, detailed, document-heavy work that skilled nursing teams already face every day.
That distinction matters. Healthcare teams are not looking for flashy demos. They need tools that fit into daily operations and help them work with more confidence. A referral review is not just a document summary. It is a decision that affects patient placement, staffing needs, reimbursement expectations, and care planning.
By focusing on these workflows, Flax Health is trying to put AI where it can be immediately useful. The platform helps turn unstructured clinical information into something teams can act on. In practice, that means less time digging through paperwork and more time making informed decisions.
For Hazy, this is a natural extension of his earlier work in automation. The common thread is helping people move faster through complex work. At MindSumo, that meant helping companies manage innovation challenges. At Microsoft, it meant building productivity and automation tools at scale. At Flax Health, it means helping healthcare workers get through paperwork without losing the clinical context that matters.
Admissions Intelligence helps teams review referrals faster
One of the main areas Flax Health focuses on is Admissions Intelligence. This tool is built to help skilled nursing facilities review hospital referrals more quickly and clearly.
Referral packets can be long, uneven, and hard to scan under pressure. Important details may be buried in clinical notes or spread across multiple documents. Admissions teams need to know whether a patient is a good fit, whether there are special care needs, whether the medication profile is costly, and whether there are any behavioral or insurance factors that could affect the decision.
Admissions Intelligence is designed to summarize patient information from referral sources and flag potential risks. That gives admissions teams a clearer view before they make a decision. Instead of relying only on manual review, staff can use AI-generated structure to see the important details faster.
This matters because admission speed can affect both patient flow and facility revenue. A delayed decision may mean losing a referral. A rushed decision may lead to surprises after admission. Better information at the start can help facilities accept the right patients with more confidence.
Intake Automation reduces repetitive form work
After a patient is accepted, the paperwork does not stop. Intake is another major pressure point. Staff have to move information from referral documents and clinical records into internal forms, assessments, and systems.
This is where Flax Health’s Intake Automation comes in. The tool is designed to pre-populate forms using existing patient data and support better MDS accuracy. The Minimum Data Set, often called MDS, is important in skilled nursing because it helps document patient condition, care needs, and reimbursement-related information.
Manual data entry is slow and easy to get wrong, especially when staff are already stretched. If information has already been captured in a patient record, it should not have to be retyped over and over. Intake Automation aims to cut down that repetitive work while improving documentation quality.
For skilled nursing teams, this can mean fewer hours spent copying details between documents and systems. It can also mean cleaner records from the beginning of a patient’s stay, which helps the clinical and billing workflows that follow.
Claims Support helps facilities protect legitimate revenue
The third major area is Claims Support. In skilled nursing, documentation and reimbursement are closely connected. If the documentation does not clearly support the care provided, claims may be denied or underpaid.
Flax Health’s Claims Support is designed to help facilities build clinically backed claims and appeals. The goal is not to inflate claims. It is to make sure the care that was actually provided is properly documented and supported by the available clinical record.
This can be especially important when facilities deal with denials, additional documentation requests, or appeals. Without the right information organized clearly, staff may spend hours searching through scattered records to build a case. AI can help by pulling relevant clinical details together and making the process less manual.
For operators, this part of the platform connects directly to financial sustainability. Skilled nursing facilities already operate under pressure from staffing costs, reimbursement rules, and regulatory requirements. Stronger claims support can help reduce avoidable write-offs and improve recovery rates.
Why Flax Health’s funding matters
Flax Health raised $3.5 million in pre-seed funding, co-led by Sorenson Capital and Pear VC, with participation from healthcare executives, skilled nursing operators, and strategic angels. For an early-stage company, that funding is a signal that investors see a real market need in skilled nursing automation.
The raise also says something about where healthcare AI is moving. For a long time, much of the attention around healthcare technology went to hospitals, insurers, telehealth, diagnostics, or consumer health apps. Skilled nursing facilities did not always receive the same level of software innovation, even though they play a major role in patient recovery after hospitalization.
Flax Health is entering that gap. Its work sits at the intersection of clinical AI, workflow automation, revenue cycle support, and post-acute care operations. Those may not sound glamorous, but they are exactly the areas where practical AI can have a measurable impact.
Funding from Sorenson Capital and Pear VC gives Flax Health room to keep building its platform, expand with customers, and prove that AI can solve real operational problems in skilled nursing without adding complexity for staff.
How David Kartchner strengthens the founding team
Trent Hazy is building Flax Health with co-founder David Kartchner, who brings deep technical experience in AI for healthcare. Kartchner’s background includes work connected to machine learning, clinical data extraction, and large language models.
That pairing is important. Skilled nursing automation is not only a product problem or only an AI problem. It is both. The company needs to understand how operators work, how staff make decisions, how documentation affects reimbursement, and how clinical data can be handled safely and accurately.
Hazy brings experience in product, automation, and scaling software. Kartchner brings technical depth in clinical AI. Together, they give Flax Health a founding team that can think about both the user experience and the underlying data problem.
That combination matters because healthcare AI cannot succeed by being clever alone. It has to be trustworthy. It has to fit the workflow. It has to handle sensitive information responsibly. And it has to make life easier for the people who already have too much on their plates.
The bigger shift behind Flax Health
The rise of Flax Health reflects a broader shift in healthcare operations. Facilities are moving beyond simply digitizing paperwork. The next step is making clinical data more usable.
Many healthcare organizations already have electronic records, referral portals, billing systems, and compliance tools. The problem is that information still does not always flow cleanly between them. Staff may have digital documents but still need to manually read, copy, summarize, and interpret them.
That is where AI-powered workflow tools can change the daily experience. If a system can understand clinical notes, extract key details, organize patient information, and trigger the next workflow step, it can reduce the friction that slows teams down.
For skilled nursing facilities, this shift is especially important because they sit between hospitals, patients, families, payers, and regulators. Their work is operationally complex, but their software stack has often lagged behind the complexity of the job.
Flax Health is trying to build for that reality. Its platform is not just about making paperwork faster. It is about making the information inside that paperwork easier to use.
What makes Trent Hazy’s work with Flax Health worth watching
The story of Trent Hazy and Flax Health is interesting because it shows a founder applying hard-earned product experience to a deeply practical healthcare problem.
Hazy has already built and scaled a company before. He has worked inside a major technology organization. Now he is focused on a narrow but meaningful area of healthcare where better workflows can help staff, operators, and patients at the same time.
That focus may be one of Flax Health’s biggest strengths. Instead of trying to become a general healthcare AI tool, the company is building around the specific pain points of skilled nursing facilities: referral review, intake documentation, MDS accuracy, claims support, and revenue recovery.
For the people working inside skilled nursing, paperwork is not an abstract problem. It is part of every shift, every admission, and every reimbursement cycle. If Flax Health can keep reducing that burden while improving accuracy, it could become a valuable part of how post-acute care teams operate.
That is why Trent Hazy’s work is worth following. He is not just building another AI startup. He is building a company around one of healthcare’s least glamorous but most important challenges: helping skilled nursing teams spend less time buried in paperwork and more time focused on care.