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Not all healthcare AI companies are the same. The market is flooded with SaaS vendors that call themselves healthcare AI companies because their product uses a model trained on clinical data. This guide is about the other category – the engineering firms that build custom healthcare AI systems for hospitals, health networks, billing service providers, and digital health startups. Not products to subscribe to. Builders to work with.

Did you know that the Software-as-a-Service (SaaS) industry is now worth more than $144B? It grows like bamboo too, at over 25% a year. It’s no wonder that many young unicorns choose to graze on this green SaaS pasture. So, what do you need to join the race?

Denied claims are often treated as a series of isolated issues. However, this $20 billion problem stems from deeper causes: fragmented data flows, inconsistent documentation practices, outdated integrations, and a lack of real-time validation. Understanding why denials happen and how to prevent them systematically is critical.

Integrating RCM into a modern SaaS platform may look simple on paper. However, engineers quickly run into endless quirks of payers, clearinghouses, EHRs, clinical workflows, privacy rules, and data standards. The result is brittle integrations and revenue leakage that undermine your product’s growth.

If you build for healthcare, your product touches money and compliance long before it touches patients. 2026 and 2027 deadlines figure in many regulations that affect revenue cycle management (RCM) requirements. With a push for interoperability, products with RCM functionality must expand the managed data, accelerate decision-making, and take privacy more seriously.

Customers won’t churn because of ugly UI. They’ll churn because your software can’t get them paid. MedTech products are now expected to handle not just clinical, but also financial workflows. Poor revenue cycle functionality leads to billing errors, compliance risks, and poor customer satisfaction.

Less than two years remain for healthcare payors to fully comply with CMS-0057-F (CMS Interoperability and Prior Authorization Final Rule). Impressive title aside, this requires the development or improvement of Patient Access APIs. This guide covers everything you need to know about the topic.

Cost optimization is again a priority for tech companies. Some engineers are uneasy about AI replacing them with codeless test automation (TA). But are these platforms as powerful as their marketing? What ROI can businesses expect in a real-world setting? What exactly do you need to maximize the return?

Healthcare startups face an uphill battle. How do they succeed in a highly regulated market and win the trust of doctors, nurses, and patients? Everything counts—features, security, marketing, and, of course, AI. Yet, many companies still overlook the hidden costs of healthcare UX design.

CMS-0057-F brings massive changes to the US healthcare. Our team has looked at the new CMS Interoperability and Prior Authorization Final Rule published on January 17, 2024. The regulation aims to make health information more accessible, and easier to exchange.

There has been considerable talk about AI software development. Will AI replace human engineers? Can startups make production-level software with AI? Beyond the hype and fear-mongering, there’s very little empirical evidence of its use on commercial projects.

Why would you want to import existing cloud resources into Terraform? Well, there are many reasons. I once joined as a Lead DevOps Engineer on a healthcare project developed outside the US. Since 2018, multiple teams have supported the project, fueled by coffee and bad decisions. Eventually, the founders sold the startup to a new owner and drove their Tesla Roadsters off into the sunset.