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Newsroom

Audacion AI Labs is an independent AI safety research lab studying what AI systems actually do after they leave training. This page is for journalists. The press contact, media kit, boilerplate, and story angles are below, built to be grabbed, copied, and downloaded.

Press Contact
[email protected](424) 999-0548
Speaking
[email protected]
Response time: 24 to 48 hours
Media Kit
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PRISM Framework Graphic
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Founder Biography
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Lab Fact Sheet
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Research at a Glance (one-pager)
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About Audacion AI Labs
Audacion AI Labs is an independent AI safety research lab studying what AI systems actually do after they leave training. Founded in 2026 by Dee Williams, the lab focuses on post-deployment behavior, runtime research, interaction dynamics, substrate governance, and multi-agent safety, the five pillars of the PRISM Research Framework. Audacion AI Labs is building a citizen science model for AI safety in which the people who use AI every day are part of the research, not the audience for it. Headquartered in Los Angeles.
About the Founder
Dee Williams is the CEO and Founder of Audacion AI Labs and ReSkillify Group. Her work began inside enterprise AI deployments, where she observed post-deployment AI behaviors that did not yet appear in the published safety literature. Audacion AI Labs is built around closing that gap. For the full founder biography, visit dee-williams.com.
Key Facts
Founded
2026 (research development began 2024)
Research Origins
Operational fieldwork inside enterprise AI deployments via ReSkillify Group
Headquarters
Los Angeles, California
Legal Structure
Independent research lab
Founder
Dee Williams, CEO and Founder
Mission
Make post-deployment AI safety a field anyone can contribute to.
Vision
1,000,000 contributors. 1,000,000,000 observations. An open record of what AI actually does.
Team Size
Founding team forming. Open roles across research, engineering, behavioral health, operations, and policy.
Research Framework
PRISM, Post-deployment behavior, Runtime research, Interaction dynamics, Substrate governance, Multi-agent safety
AI Advisory Council
Forming
Impact Goal
Close the gap between what AI is trained to do and what it actually does in the world.
Annual Conference
PEAQ Summit
For Reporters

What makes us different.

The 98% Gap
Roughly 98% of published AI safety research studies models before deployment. Audacion AI Labs studies what happens after, the behaviors that only appear under real operational conditions, over time, with real users.
Citizen Science at Scale
Audacion AI Labs is building post-deployment safety as a citizen science. The teachers, nurses, small business owners, and parents who use AI every day are part of the research, not the audience for it.
PRISM is a Research Architecture
PRISM is not a framework name slapped on existing work. It is a five-pillar research architecture for the parts of AI safety that begin after deployment: behavior drift, runtime conditions, interaction effects, substrate dispositions, and multi-agent dynamics.
The AI Advisory Council
Audacion AI Labs's advisory model bridges the gap between operational practitioners, academic researchers, and frontier model teams, three groups that rarely share a research table.
Story Ideas

Five categories. Fourteen angles.

The 98% problem in AI safety research.
Most published AI safety work ends at deployment. Audacion AI Labs has a behavioral drift taxonomy of 31 types that do not appear anywhere in the literature. Why the field stopped studying AI at the exact moment it started mattering.
What frontier labs see but cannot publish.
Operational AI teams inside enterprise deployments observe behaviors that academic researchers cannot access. Audacion AI Labs's lived operational findings are running ahead of the published literature. The story of why the data lives in the wrong places.
Post-deployment is the missing field.
Pre-deployment safety has labs, conferences, and funding. Post-deployment safety has none of those. Why the discipline that matters most has the least infrastructure.
Press Releases
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Media Coverage
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Speaking

Dee Williams is available for keynotes, panels, podcast interviews, and conference presentations.

Post-deployment AI safety and the limits of pre-deployment evaluation
Building citizen science models for emerging research disciplines
Operational fieldwork as a source of safety findings
Workforce transformation in the age of frontier AI
Interaction dynamics and the human side of long-running AI use
Governance gaps between trained behavior and deployed behavior
For speaking inquiries: [email protected]
Learn more about the lab →See our research pillars →Follow the lab's work →