Powering your digital workforce of AI agents.
.avif)
The SpinSci platform is purpose-built for patient access, orchestrating interactions across voice, digital, and human touchpoints. Faster access for patients. Less friction for your teams. More growth for your health system.
Meet your patients exactly where they are. Modernize your digital front door to support patients with an efficient, reliable experience across phone calls, SMS, chat, and email.
AI agents that reason, act, and resolve, without human escalation. They own the entire workflow, from the first patient interaction to resolution, automating scheduling, billing, referrals, pharmacy, and more.
Turn operational knowledge and rules into intelligence to drive every patient interaction. Whether human-led, automated, or hybrid, confidently execute workflows with consistency and speed.
Seamlessly integrate your existing tech stack. Natively connects with EHR, telephony, and contact center systems to deliver personalized patient experiences, increase staff productivity, and reduce administrative burden.
Designed for trust at scale, our platform embeds guardrails, system reliability, and deep observability into every workflow. Operate confidently while maintaining transparency and control.
Privacy. Patient information is safeguarded by following strict healthcare privacy standards, limiting access, and honoring consent.
Security. We protect your data with strong encryption, secure infrastructure, continuous monitoring, and proven safeguards.
Access. Our secure authentication, role-based access, and strict permission controls ensure only the right people can interact with sensitive systems and data.
Compliance. We meet leading industry standards and regulations through regular audits, strong controls, and transparent reporting.
Deliver an intelligent, humanized experience, driven by your workflows and designed for outcomes. Resolve routine calls quickly and equip agents with full context when high-touch care is needed.
Connect patients to the help they need 24/7, without delays or hold times.
Give every patient the experience and first-time resolution they expect.
Shield your team from routine inquiries so they can focus on what matters most.
Book a demo with our expert team to see how our AI agents can transform patient access at your organization.
Get the Latest Insights from our team
%20(10)%20(1).png)
.svg)
What is an AI Front Door for Healthcare Systems?
.svg)
AI Agents in Healthcare: What CIOs Need to Know
How AI agents are transforming patient access, reducing costs, and helping health systems serve more patients.
%20(16)%20(1).png)
.svg)
Ready to get started?
Learn why leading health systems are tapping into the power of the SpinSci AI platform for patient access.
Frequently Asked Questions
The Healthcare AI Framework (HCAF) is the proprietary platform that powers every SpinSci AI agent. It extracts your EHR's decision logic, ingests the unstructured data your health system runs on every day, and converts all of it into an AI-ready foundation that drives modern, automated patient access workflows. It is not a product you deploy on its own. It is what makes SpinSci's AI agents smarter and more capable than anything built on a generic platform.
Patient access automation uses AI agents to handle interactions between a health system and its patients across every channel. Inbound, AI agents handle voice calls autonomously, managing scheduling, billing, prescriptions, and referrals without hold times or staff involvement. When a human is needed, AI works alongside contact center agents in real time so staff can resolve calls faster. Outbound, AI agents run proactive campaigns across voice, text, and email to reduce no-shows, recover unfilled prescriptions, convert referrals, and collect more revenue.
An AI agent is software that can reason, make decisions, and complete tasks autonomously on behalf of a user. That's fundamentally different from a chatbot, which follows a fixed script and typically hands off or fails when the conversation goes off-script. The practical difference shows up in outcomes: a chatbot might confirm an appointment exists, an AI agent can reschedule it, update the record, and end the call resolved.
A healthcare AI platform is the foundational layer of technology that powers AI inside a health system. It's not a single application or chatbot. It's the intelligence layer underneath the tools your staff and patients actually interact with, responsible for ingesting data, applying healthcare-specific reasoning, and orchestrating AI agents to complete work across voice, digital, and human touchpoints.
General-purpose AI is trained on broad knowledge and can approximate answers about healthcare, but it doesn't know your health system's specific workflows, your EHR's decision logic, or your patients' histories. Healthcare AI that's actually fit for patient access is trained on and integrated with EHR platforms like Epic, contact center systems, scheduling logic, billing rules, and more.
Yes. SpinSci's AI agents integrate natively with Epic, Oracle Health, and athenahealth, the platforms that power the majority of large health systems in the US. This matters because the EHR is where patient data lives: schedules, insurance, prescriptions, referrals, billing history. An AI agent that isn't connected to your EHR can only have a conversation. An AI agent that is connected can actually complete the task, scheduling an appointment, processing a refill request, updating a record, without a staff member ever touching it.
Three things need to be true before AI agents can work reliably in healthcare. First, the data has to be cleaned, vectorized, and structured for AI reasoning. Second, the health system's decision logic, the rules that govern how workflows like scheduling, referrals, and billing actually run, has to be built into the model. Third, the AI has to be integrated natively with the EHR and contact center. Skip any of these and the agents will either fail or behave like a generic bot, not a trained staff member.
Most healthcare AI is built on general-purpose models that weren't designed for healthcare workflows. They get bolted onto health systems without solving the underlying data problem: EHR data is messy, inconsistent, and structured in ways that AI can't reason over without significant preprocessing. When the data isn't AI-ready, the agents aren't reliable. The health systems seeing real results are the ones that start with an intelligence layer that operationalizes the data first.