June 22, 2026
How are modern enterprises surviving ransomware and minimizing their blast radius? In this Trace3 PressBox session, N-able breaks down why true security requires moving from simple cyber resiliency to holistic business resiliency.
Discover how converging IT Operations and Security Operations (SecOps) simplifies infrastructure management, how AI speeds up behavioral analytics in modern Data Lakes, and how to automate compliance reporting using the NIST Framework without extra overhead with Trace3's Boomchi Kumar and Chris Joe from N-able.
Key moments:
00:00 - The Shift from Cyber Resiliency to Business Resiliency
01:30 - Single Vendor vs. Best-of-Breed Infrastructure Strategy
03:45 - What Keeps Technology Decision Makers Up at Night?
05:16 - Defining Your Minimum Viable Business (MVB)
05:57 - What is a Digital Resiliency Recovery Assessment?
06:33 - How AI Compresses Threat Data & Reaction Times
08:05 - Human Experience + AI: The Power of Partnering Right
09:08 - How AI Processes MDR Data Lakes to Neutralize Threats
10:43 - The Convergence of IT Operations and SecOps
13:45 - Mapping Security Platforms to the NIST Framework & Risk Scores

In Episode 17 of Trace3’s Live AI series, Trace3 CTO Tony Olzak and Kevin Geron, CIO of Farm Credit Mid-America, tackle one of the biggest hurdles facing enterprise leaders today: managing the overwhelming influx of AI use cases.
While generative and enterprise AI offer limitless potential, organizations must establish clear frameworks to prioritize, govern, and execute high-impact initiatives without getting bogged down by noise or technical debt.
In this episode, we cover:
How to filter and prioritize AI ideas based on business ROI and feasibility.
Establishing governance and risk controls without slowing down innovation.
Best practices for moving from experimentation to scalable enterprise deployment.
Real-world frameworks Trace3 uses to help organizations align AI strategy with business goals.
CHAPTERS:
0:00 - Introduction & The AI Influx Challenge
01:45 - Why Organizations Struggle with AI Prioritization
04:10 - Frameworks for Evaluating AI Business Impact & ROI
07:30 - Governance, Risk, and Compliance in Rapid AI Adoption
10:50 - Transitioning from Proof of Concept to Production
13:40 - Key Takeaways & Building an AI Roadmap
15:30 - Final Thoughts & Closing
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Learn more about how Trace3 accelerates enterprise AI: https://www.trace3.com/
Connect with Trace3 on LinkedIn: https://www.linkedin.com/company/trace3/posts/

In Episode 16 of LiveAI, host Josh Lindstrom (Senior Director of Data & Analytics at Trace3) sits down with industry leaders Jason Hardy (VP of Storage Technology at @NVIDIA ) and Kaycee Lai (VP of Enterprise AI at @everpure-data ) to discuss how enterprises can move past the proof-of-concept phase and turn dormant data into tangible business outcomes.
From the evolution of data storage to extreme co-design, the explosion of agentic workflows, and the reality of physical and edge AI, discover what it truly takes to fuel modern AI factories and achieve measurable ROI.
Key Topics & Timestamps:
00:00 – Welcome to LiveAI: Moving AI from Philosophy to Production
01:03 – Guest Introductions: Jason Hardy (NVIDIA) & Kaycee Lai (Everpure)
02:07 – The Power of Co-Design: Building the Modern AI Factory
03:52 – Beyond Speeds & Feeds: Activating Stored Data for AI
06:00 – Fueling the AI Factory: Data Prep, Libraries & Blueprints
08:30 – Data Resilience, Readiness & Overcoming the Governance Hurdle
14:41 – Moving Out of PoC: How Enterprises Uncover & Prioritize AI Use Cases
18:05 – Aligning AI Blueprints to Industry Verticals & Clear ROI
27:10 – Model Strategy: Open Weights, Frontier Models & Tokenomics
30:38 – What’s Next in AI: Agent Swarms, Physical AI & Edge Inferencing
37:00 – Advice for the Next Generation: Creativity as the Superpower
42:50 – Closing Thoughts & Next Steps
Key Takeaways:
Data Is the Fuel: High-performance infrastructure means nothing if your data isn't prepared, resilient, and accessible to AI agents.
Use-Case Driven ROI: Successful enterprises don't just buy hardware—they align specific business pain points to tailored AI blueprints and workflows.
The Agentic Shift: Future enterprise productivity will be driven by swarms of 24/7 autonomous agents handling both structured and unstructured data across the network.

AI can transform customer experience—but without the right guardrails, it can also create new friction.
In this Trace3 PressBox conversation, Trace3's Asher Lohman and Michael Burr from @NICE-Systems discuss how organizations can use AI to augment contact-center teams, protect the human element, and connect automation to measurable business outcomes.
Topics include:
How CX is evolving from individual interactions to end-to-end customer relationships
Where organizations should begin with AI adoption
How to identify low-risk, high-value use cases
Why business problems should come before technology decisions
The role of human oversight, data access controls, and AI guardrails
How agentic and deterministic workflows can work togetherA CX transformation involving 7,700 agents
Chapters:
00:00 - Introduction: The Balancing Act of AI in CX
00:56 - Trace3 & NICE Partnership & Customer Journey Evolution
02:24 - NICE’s Cognigy Acquisition & CXAI Strategy
03:24 - Navigating People, Processes, and Tech in AI Adoption
05:07 - Identifying Real CX Pain Points vs. Symptoms
07:05 - Augmentation First: Preserving the Human Element
08:15 - Guardrails, Governance, and AI Risk Management
10:12 - Agentic Flows vs. Deterministic Workflows in Cognigy
12:13 - Case Study: Transforming a 7,700-Agent Financial Institution
14:00 - Key Takeaways & Closing Thoughts