# Meet Us at HLTH 2026 | Certilytics

> Meet Certilytics at HLTH 2026, Booth #3253, Las Vegas, NV, November 15–18. Take our quiz, join our booth sessions, and schedule time with our team.

Source: https://certilytics.com/hlth-2026

HLTH · Booth #3253 · Las Vegas, NV | November 15–18, 2026

## Smarter Than Generic AI. We Can Prove It.

Healthcare Decision Intelligence from Certilytics

- Before HLTH, find out if you need more than generic AI for your healthcare organization.
- At HLTH, visit our booth to learn why generic AI doesn't work for healthcare.

## Our Experts. Sharing Perspectives on Healthcare Intelligence.

Check Out These Sessions at Booth #3253 — Tuesday, 11/16 and Wednesday, 11/17

**10 a.m. — Why Generic AI Doesn’t Work in Healthcare**

Why healthcare decisions require more than AI that can simply read data—and what it takes to deliver intelligence leaders can trust.

Presented by Robert Dwyer, PhD (EVP, Chief Data Scientist)

**1 p.m. — CertHLM - The Gateway to Decision Intelligence**

A demonstration on how CertHLM combines healthcare reasoning with organizational knowledge to help teams move from questions to trusted answers and action faster.

Presented by Caroline Duke (VP, Data Solutions)

**3 p.m. — What is a Healthcare Intelligence Layer and Why It Matters?**

Explore the critical layer between data and decisions—and how governed data, proven healthcare logic, validated models, and organizational context build confidence in every answer.

Presented by Andy Ottum, MPH (Executive Vice President)

## Do You Need More Than Generic AI? Take Our Quiz.

Questions about your data, your language, your governance, and where decisions actually get made.

- **Answer-ready data** — When someone on your team asks your AI tool a question, where does the answer actually come from?
- **Healthcare semantics** — When your clinical, financial, and operations teams talk about "risk" or "cost," are they speaking the same language?
- **Domain expertise** — How much real healthcare knowledge, quality measures, coding logic, risk models, is actually built into the AI tools you use?
- **Governed workflows** — If a regulator or auditor asked you to explain an AI-driven decision tomorrow, how would that go?
- **Right experience** — Where do the people making decisions actually encounter these AI insights?
- **Trust to act** — When AI gives your team an answer, how often do you act on it without double-checking everything manually?

**Signal: strong — You're already running on healthcare intelligence.**
Your data, your language, and your workflows already reflect the context healthcare decisions demand. The opportunity now isn't fixing gaps, it's extending that same intelligence layer everywhere decisions get made.

**Signal: mixed — You have the tools. Not yet the context.**
You're using AI, but pieces of the healthcare intelligence layer, validated data, shared semantics, domain logic, governance, or workflow embedding, are still missing. That gap is exactly where generic answers turn into risk.

**Signal: weak — You're running on generic AI.**
Right now, your AI is likely answering healthcare questions with non-healthcare intelligence. That's a gap between confidence and correctness, and in healthcare, that gap has consequences.

## News & AI Insights from Certilytics

- Why Generic AI Doesn’t Work for Healthcare
- CertHLM — 5 Questions We Get Asked About Our Healthcare Language Model
- Certilytics, Inc. Launches AI Accelerator to Help Healthcare Organizations Operationalize AI and Move from Dashboards to Answers