# Video: patient onboarding through digital ticket triage

> Kognitos webinar: how payers and providers automate patient onboarding, vaccine scheduling, digital support, and claims — with AI that's safe enough for HIPAA workloads.

**Page**: https://www.kognitos.com/videos/automate-healthcare-workflows-from-patient-onboarding-to-digital-support-ticket-triage/
**Watch on YouTube**: https://www.youtube.com/watch?v=d7SsAn63XpU
**Length**: 51m 25s

## About this webinar

A 51-minute Kognitos webinar focused on what it actually takes to put AI automation into a regulated healthcare environment — for both payers and providers.

## Speakers

- **Andrew Novage** — leads the Kognitos sales team in the West. Comes from a family of physicians.
- **George Williams** — Solution Engineering at Kognitos. Leads the live demo of patient-onboarding and ticket-triage automations.

## The three reasons healthcare has been slow to adopt AI

- **Lack of trust**: ask ChatGPT, Grok, or Gemini the same question ten times and you can get nine different answers. Inconsistency is a feature of how LLMs work — but it's a liability when a wrong answer becomes a patient complication, a missed payment, or a wrongly denied claim.
- **Lack of control**: no guard rails, no way to audit exactly what the AI is doing — and HIPAA data privacy makes this concern especially sharp.
- **Investment risk**: pilots that don't go to production are widely visible. Healthcare executives want predictable ROI before committing.

## How Kognitos addresses each concern

- **Trust**: the LLM is used for understanding and creativity; the runtime is deterministic English-as-code. The same input always produces the same answer.
- **Control and audit**: every step of every run is logged as English “facts.” A compliance officer can read what happened without parsing developer logs. Sensitive data flows can be scoped per department.
- **HIPAA-grade deployment**: tenancy and data handling are designed for regulated industries up front, not retrofitted.

## Use cases shown in the demo

- Patient onboarding — extract patient identifiers from new-patient forms, validate across documents, file to SharePoint, and email the intake team.
- Vaccine scheduling — high-volume, repetitive scheduling work prone to manual errors.
- Claims registration — get from FNOL to a structured claim faster, with the audit trail regulators expect.
- Digital support ticket triage — classify inbound tickets and route to the right team without dropping context.

## FAQs

**Q: Why has healthcare been slow to adopt AI according to this webinar?**

Three reasons: lack of trust (LLMs give inconsistent answers, and in healthcare a wrong answer becomes a patient complication or a wrongly denied claim), lack of control (no guard rails or audit trail, plus HIPAA data privacy concerns), and investment risk (pilots that don't make it to production).


**Q: How does Kognitos make AI safe enough for HIPAA-regulated workloads?**

By separating the creative LLM layer from the deterministic execution layer. The LLM helps with understanding and extraction; the runtime executes English-as-code deterministically and logs every step as English “facts” for audit. Data handling and tenancy are designed for regulated industries from the start.


**Q: Which healthcare workflows does the demo cover?**

Patient onboarding (extract and validate patient identifiers, file to SharePoint, email the team), vaccine scheduling (high-volume scheduling automation), claims registration (FNOL to structured claim), and digital support ticket triage (classify and route inbound tickets).


**Q: Why won't a black-box LLM work for claims and patient data?**

Because the answers aren't reproducible — the same question can return different answers on different runs. In healthcare, that translates directly to clinical or financial harm. Kognitos's deterministic English-as-code runtime ensures the same input always yields the same output, which is the bar regulators and compliance officers actually need.