Asellera: AI Operators for Healthcare Operations
I’m Shane Senha, founder of Asellera.
We’re building AI operators for healthcare and service-based businesses, starting with dental practices.
The idea is simple: most clinics don’t actually have a demand problem—they have an operational efficiency problem. Missed calls, scheduling friction, after-hours inquiries, and administrative overload quietly cost practices significant revenue every year.
Asellera is designed to fix that by automating and streamlining core clinic workflows like patient communication, appointment handling, follow-ups, and internal coordination. The goal isn’t to replace staff—it’s to remove the repetitive workload that slows them down so they can focus on patient care.
We’re currently focused on dental as the first vertical, with a long-term vision of building AI-driven operational systems across healthcare and other service industries.
Always open to connecting with others building in healthcare, AI, or automation.
Nixplora
SaaS Decision Intelligence platform
Comments (11)
Welcome Shane! Going dental-first is a smart call and instead of constantly trying to attract more new patients, focus on retaining the ones who are already trying to reach them. Curious though, how open are dentists to AI handling patient communication? Healthcare is usually slow to adopt new tech.
Hi Olga, thanks for the warm welcome!
You’ve pointed out the exact hurdle every builder in this space faces: healthcare operates on a foundation of absolute trust and strict compliance.
Because of that, the goal can't be total, hands-off automation. Instead, it’s about human-in-the-loop automation.
Our approach isn't to replace the human element, but to protect it.
The AI handles the repetitive, easily standardized administrative friction (like capturing missed after-hours calls or filling sudden gaps in the schedule), but always passes complex patient care, triaging, and final clinical decisions back to a human.
By ensuring everything built is fully compliant and keeps the clinic staff firmly in control, you turn a perceived risk into an operational superpower.
Appreciate you bringing up such a critical piece of the puzzle!
Makes total sense to keep the AI on the admin side and leaving the human-in-the-loop for clinical decisions. Good luck with the rollout!
Thank you for your kind words, I’d love to keep you updated!
Let’s connect on LinkedIn
https://www.linkedin.com/in/shane-senha
Welcome to the community, Shane! 🙋🏻♂️
Grateful to be here with you.
The "human-in-the-loop automation" answer you gave Olga is exactly the balance I landed on with FounderFlow too. When you're running something people depend on (a clinic, or in my case three separate businesses at once), full hands-off automation is scary, but going back to zero automation isn't realistic either. My compromise was having the AI grade its own confidence on every insight, Verified, Very Likely, Needs Review, Monitor Only, so the human always knows when it's safe to act on autopilot versus when they need to actually read the message themselves. For missed calls and after-hours inquiries specifically, does Asellera ever act autonomously, or does it always queue things for staff to approve first?
Really appreciate this perspective. That balance between automation and human oversight is exactly where we see the future going.
For Asellera, the goal is not to remove the human element from patient communication. It’s to handle the repetitive operational work that slows practices down while keeping teams in control. For things like missed calls, SMS campaigns, appointment requests, scheduling, confirmations, and follow-ups, Asellera can assist and automate workflows based on defined practice rules, while escalating situations that require human attention.
Especially in healthcare, trust and accountability matter. AI should create more capacity for teams to focus on patients, not make decisions that require clinical judgment or replace the relationships practices have with their patients.
Shane, the missed calls and after-hours inquiry problem is one I hear constantly from multi-location service operators, and it rarely gets fixed until someone actually measures how much revenue leaks through it. I am building FounderFlow, an AI Executive Chief of Staff. It watches your business, identifies what matters, protects your revenue, and tells you exactly what to do next. Right now we are onboarding the first 30 founding members personally rather than opening to the public. Curious how you are currently tracking which missed call or delayed follow up actually cost a practice real revenue, do you have a way to quantify that yet?
Great point, and I really like what you’re building with FounderFlow. Having AI surface what matters most and guide operators toward the right actions is a powerful direction.
This is exactly why visibility and measurement are so important. At Asellera, we’re building this into our operational dashboard with analytics, performance tracking, and audit logs so practices can understand what’s happening across patient communications and workflows.l
The goal is to help teams identify missed opportunities, track follow-up performance, and understand the operational impact of every interaction rather than just automate tasks blindly. Creating that visibility is what allows practices to make better decisions and continuously improve.
↳ Replying to Shane Senha
Shane, building analytics and audit logs directly into the dashboard instead of bolting reporting on after the fact is the right order to do it in. Most tools I see try to add the reporting layer once the workflow is already live, and by then nobody fully trusts the numbers enough to change behavior based on them. If you get to the point where you can show a practice a real dollar figure attached to missed calls or delayed follow ups over a month, that number alone probably does more to build trust in the automation than any feature list would. Are practices asking you for that kind of proof before they trust AI with patient communication, or does the trust come first and the numbers end up being more of a confirmation afterward?
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