Data Driven

Welcome back to another episode of Data Driven!
This time, hosts Andy Leonard and Frank La Vigne sit down with Jim Spignardo, Director of Cloud Strategy and AI Enablement at ProArch, to explore the transformative role of AI and data engineering in critical industries. From the challenges of bringing modern AI solutions into traditional sectors like power generation and manufacturing, to the real-world impact of tools like Copilot, this episode dives deep into automation, return on investment, and the importance of outcome-driven technology adoption.
Along the way, Jim Spignardo shares hands-on stories and key lessons learned, such as how modernization happens gradually in high-stakes environments, and why ROI modeling and project management are crucial to successful innovation. Whether you’re curious about Azure AI Foundry or the future of workplace automation, this is an episode packed with practical insights and tales from the cutting edge of AI implementation.
Links
Jim on LinkedIn -https://www.linkedin.com/in/spignardo/
Watch on YouTube -https://youtu.be/XBDpsi4f0YY

Time Stamps
00:00 ROI Journey with Copilot
04:57 Building with Azure AI Foundry
08:23 Implementing AI for Power Plants
12:22 Discussing 19.2K networks in power plants
14:00 Ensuring data security in devices
17:59 Cloud integration for IT operations
23:30 Discussing RPO, RTO, and ROI modeling
24:48 Switching from hobbyist to manufacturing
30:15 Introducing our AI platform Vector
34:34 AI Spend and ROI Dashboard
36:47 Improving meeting notes integration
40:48 AI in Manufacturing for Troubleshooting
45:41 Managing AI Tool Adoption
47:51 Tracking ROI and user intensity
52:03 Consulting firms spotting product chances
55:17 Increasing delivery speed with AI
56:55 Automating the house routine

In this episode, hosts Frank La Vigne and Andy Leonard sit down with Lawrence Snapp, CEO and board member of TrustScale, an innovative AI trust and verification platform. Together, they explore the crucial topic of trust in artificial intelligence—how hallucinations from AI models can spiral out of control and why it’s essential to catch them early.
Lawrence Snapp pulls back the curtain on TrustScale’s journey from early AI and translation work in the 1980s and call center solutions, to its modern-day mission: empowering humans to verify and trust AI outputs with products like Argus.
You’ll hear about real-world impacts in fields like healthcare, legal, and research, learn how TrustScale’s deterministic engine outpaces humans in hallucination detection, and dive into debates around truth, trustworthiness, and the future of configuring AI values. Whether you’re an industry veteran or just curious about how we build trustworthy AI, this episode is packed with insights on technology, responsibility, and the power of rigorous engineering.
Links
Watch on YouTube -https://www.youtube.com/watch?v=RjM7lxn3Qk8
Lawrence on LinkedIn -https://www.linkedin.com/in/lawrence-snapp-408339/

Time Stamps
00:00 Funny AI-generated story
03:37 Company's Evolution from Translation to AI
07:32 Developing the TrustScale engine
11:35 Using AI for collaboration
13:39 Building a trust scoring system
18:12 Working at BASF and AI testing
19:32 New developments in voice assistants
23:41 Trust scale and company confidence
26:13 AI mishap in medical drama
32:48 Overcoming AI recency and cost challenges
36:54 AI's impact on career growth
38:50 Interviewing and developing talent
43:31 Starting with Polaroids and AI goals
46:54 Discussing TrustScale and AI interactions
50:42 Empowering AI customization for users
51:45 AI ethics discussion in Los Altos

In this episode, host Andy Leonard sits down with Ilan Man, founder and CEO of Paradox Machines, a full-stack data and AI company based in Brooklyn. Ilan shares his fascinating journey from an actuarial career to the dynamic field of data science, exploring the rise of big data, the art of translating complex mathematics into code, and the importance of numeracy in society.
Together, they discuss the paradoxes at the heart of data and AI, the challenges of decision-making under uncertainty, and why intuition, risk management, and storytelling remain critical in a world driven by data. Whether you're a data enthusiast, decision-maker, or just curious about how numbers shape our lives, this conversation delivers valuable insights and a healthy dose of skepticism about the limits, and possibilities, of analytics.
Links
https://www.linkedin.com/in/ilanman/

Time Stamps
00:00 Starting a career in data science
03:34 Discovering a career in actuarial science
08:17 Learning coding and joining Squarespace
11:40 Understanding Probability in Code
15:36 Questioning Confidence in Decision-Making
20:06 Discussing COVID vaccine effectiveness
21:09 Understanding vaccine effectiveness
24:41 Consumers interacting with unpredictable AI
29:35 Discussing disease perception and interpretation
33:01 Casino audiobook and extra details
35:41 Balancing data-driven decisions
40:07 Career journey to founding Paradox
40:49 Building a data platform with AI
46:41 Data's Role in Decision Making
47:30 Value and limits of data-driven decisions

In this episode, Frank La Vigne sits down with Pradnesh Patil, co-founder and CEO of Altima AI, to explore how AI is revolutionizing the world of data engineering. Together, they dive into the challenges of modern data stacks, the explosion of tools and technologies, and how AI-powered agents are transforming the way data teams build and maintain complex systems. From automating data pipeline management to optimizing infrastructure and safeguarding governance, Pradnesh Patil shares insights on the next wave of data engineering and what the future holds for professionals in the field. Whether you’re a veteran data engineer or a student curious about the evolving landscape, this episode offers practical advice, industry trends, and an optimistic look at how embracing AI can supercharge your career and your organization’s capabilities.
Links
Pradnesh's LinkedIn - https://www.linkedin.com/in/pradneshpatil/
Watch on YouTube -https://youtu.be/vxQrjE-U3gw

Time Stamps
00:00 Evolution of data technology tools
04:11 Managing tool stack complexity
09:09 Discussion on AI guardrails and future
10:55 Managing MCB server outputs
14:32 Streamlining Data Pipeline Efficiency
18:48 Managing and Deleting Memories
21:12 AI security and virtual employees
27:16 AI transforming jobs and automation
30:43 Impact of AI on IT Industry
32:32 Upgrading legacy systems with AI
37:10 Importance of Data Engineering
39:10 Changing role of data managers
42:45 Home lab challenges and data management

In this episode, hosts Candace Gillhoolley and Frank La Vigne are joined by Neil Katz, Chief Product Officer at Valantor AI—a four-time Emmy winner whose unconventional journey spans from technology startups to award-winning journalism, and now to the forefront of enterprise AI innovation.
Neil shares his unique perspective on the evolution of AI, from the early days of digital design and machine learning, to building large-scale AI and document intelligence platforms for major organizations. The conversation explores the critical challenges of knowledge extraction, document comprehension, and securing sensitive data in today's era of sovereign AI. Together, they uncover the hidden complexities behind Retrieval-Augmented Generation (RAG), discuss the importance of hybrid search strategies, and reflect on where the field is heading as enterprise needs push the boundaries of what AI can do.
Whether you're a data professional, an AI enthusiast, or just curious about how language models are transforming how we understand information, you won’t want to miss this candid and thought-provoking deep dive into the future of AI and data integrity.
Links
Neil on LinkedIn -https://www.linkedin.com/in/neilkatz/
Watch on YouTube -https://www.youtube.com/watch?v=qf8qifz_RL8

Time Stamps
00:00 Early career in tech and journalism
04:01 Early consumer AI experiences
06:49 Early AI and machine learning developments
11:43 Anthropic's new findings on AI models
16:15 Data sovereignty in AI systems
19:27 Implementing open source AI models
22:49 Breaking down documents for models
25:45 Understanding the RAG system process
28:47 Challenges in AI data processing
31:22 Challenges in RAG with Insurance Data
36:35 Understanding and managing data security
39:35 Early days with OpenAI GPT
40:48 Explaining vector and similarity search
46:57 The evolution of computing models
47:29 Computing evolution to cloud and edge