Topflight Apps

Most HIPAA violations in startups don’t stem from negligence — they come from quick, seemingly smart decisions made under pressure. That “we’ll fix it later” moment quietly snowballs into a six-figure audit nightmare. This isn’t another compliance checklist. It’s a field manual drawn from real-world failures — the kind that stall partnerships, kill pilots, and show up in OCR reports. If you’re building or scaling a health app, these are the 10 traps you can’t afford to ignore. #HIPAAcompliance #digitalhealth #healthcareappdevelopment

Integrating a health app with EPIC EHR/EMR? Check out the ultimate guide from steps involved to best practices, costs, and more. https://lnkd.in/gbdBEf9W

A group of industry veterans envisioned faster and cheaper medical coding and set out to create an AI platform to make a real difference for providers. On that journey, GaleAI founders realized they needed a versatile team to turn a proof of concept into a polished market-ready product. Enters Topflight. GaleAI

Dr. Josh Dégallier, CEO of RoundR, recognized a critical gap in the current desktop-focused EHR systems' ability to support hospitalists effectively. Driven by vision but lacking technical expertise, he set out to create a mobile companion app for doctors to access EHR records on the go during rounds.

So, this happened: Topflight just ranked in the Top 5 for Website Development & Web Design in Clutch’s 2025 Best-of Awards. We didn’t pay for it. We didn’t pitch for it. Honestly, we were deep in a sprint when we got the news. The recognition? It came from real feedback and real impact. That’s the only kind that matters. So here’s to Ryan Majoria, M.D. and the LnQ team—for the trust, the vision, and the kind of problem that’s actually worth solving.

The AI revolution in healthcare isn't about replacing humans – it's about enhancing their capabilities. Excited to share our new resource: "The Healthcare AI Playbook: 19 High-Impact Use Cases" – created to help healthcare organizations implement AI solutions that deliver real value. What makes this playbook different? Each case study is built from real-world implementations with documented returns and clear roadmaps for success. The future of healthcare isn't just about adopting new technology – it's about strategic implementation that improves patient outcomes while enhancing operational efficiency. Download the playbook here: https://lnkd.in/gTrcpr9F Who in your network is leading AI initiatives in healthcare? Tag them below. #HealthcareInnovation #AIinHealthcare #DigitalHealth #MedTech

We’re proud to announce that Topflight is a Best of Clutch Finalist. This honor reflects the standout digital experiences we’ve created —showcasing the measurable results we’ve delivered, the technical challenges we’ve solved, and the strong client relationships behind every launch - and we’re proud to be named among the top-performing agencies on Clutch. Thank you Ryan Majoria, M.D. for your faith in us. #BestofClutch

Data provenance might be healthcare's biggest AI blind spot that no one's talking about. EHRs have no consistent way to track where data comes from or when it entered the system, explains Topflight's Scott Rossignol. FHIR write-backs, extract imports, and Smart on FHIR applications all handle information differently - some merely displaying data without true integration. This creates a critical problem for AI: how can we track when AI outputs influenced clinical decisions? With so many integration paths and logical branches, there's no reliable method to record this in a discrete, meaningful way. The implications are enormous for clinical safety, regulatory compliance, and understanding AI's true impact on patient care.

A great chatbot doesn’t just answer a question. It holds a conversation. Even before LLMs, the best conversational systems were built by thinking through the entire flow as a dialogue. As Topflight's Terry Woodward clarifies - that means not just delivering structured answers, but doing so in a way that feels like an intelligent assistant is helping you. This still holds true today. For example, if a user asks for specific structured data, it’s not enough to simply present the answer. A good system will also understand where you are in the conversation, use that context to continue the dialogue, and keep the interaction moving forward naturally. That’s where semantic context and agentic memory come into play. When you design with that in mind, your chatbot doesn't feel like it's starting from scratch with every message. It feels like it remembers you and is actually trying to help. That’s the difference between a bot that works and a bot that feels human.

AI in EHRs often fails because the focus is on the product, not the provider’s workflow. You’re building inside someone else’s system so no matter how great your UI is, it won’t matter if it pulls providers out of their EHR. The key to success? Scott Rossignol at Topflight suggests meeting providers within their existing workflows. While Smart on FHIR and CDS Hooks offer potential, API-based write-backs often prove more effective by embedding insights directly into the tools providers already use. The golden rule in healthcare tech: never add extra steps. Your solution should fit seamlessly into the provider’s routine—not interrupt it.