Kris Krisco, Co-founder of Synopsis, is building AI-native data infrastructure designed specifically for the middle market. After scaling and selling a company under private equity, he saw firsthand why most AI initiatives fail — not because of ambition, but because of broken data foundations. In this episode, he explains how to move from fragmented systems and unreliable dashboards to real-time, operational AI that actually drives EBITDA.

You’ll Learn

Why 97% of middle-market AI projects fail — and the hidden infrastructure gap most companies ignore

The critical role of master data management (MDM) and entity resolution in making AI outputs trustworthy

How AI agents can replace months of traditional data engineering work with one-week iteration cycles

Real examples of workflow automation that reduce operational waste and improve field execution in real time

How private equity-backed companies are using AI in live board meetings to answer strategic questions instantly

Chapters

00:00 Intro
01:00 Why Most AI Initiatives Fail
04:40 The Synopsys Approach to Data Infrastructure
10:40 The MDM Problem No One Talks About
17:15 How Much of Your Data Are You Actually Using?
20:45 Workflow Automation & Real-World Use Cases
25:15 Disaster Recovery Case Study
33:00 AI Inside Private Equity Board Meetings
36:30 The Future: Rule of 40 Becomes Rule of 70+

Links

• Explore more expert interviews: https://checkpluris.com/expert-interviews
• Watch on YouTube: https://youtu.be/a6H8SxJTsOc
• Connect with Kris Krisco: https://www.linkedin.com/in/kris-krisco/

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Mollie Amkraut Mueller, Founder of Watch Me AI and former strategist at IDEO and EY, helps non-technical leaders turn AI into a chief of staff, analyst, and revenue engine. In this episode, she breaks down a practical, business-first approach to AI adoption—showing how one recorded meeting can become 10 high-value assets. If you lead a team or operate in the middle market, this is a tactical blueprint for saving time, increasing output, and unlocking ROI without hiring a dev shop.

You’ll Learn

• How to turn a single meeting transcript into LinkedIn posts, proposals, client deliverables, and course content in minutes
• Why most AI projects fail—and how to scope high-ROI use cases that actually stick
• A simple diagnostic framework to uncover 1–10 immediate AI opportunities inside any workflow
• How off-the-shelf tools like Claude and Relay can replace expensive, over-engineered automation projects
• A real-world PR agency case study that cut multi-hour manual research down to 10 minutes per client request

Chapters

00:00 Intro
01:58 Mollie’s background and founding WatchMe AI
05:09 The 90-minute AI diagnostic that reveals hidden ROI
12:17 One transcript → 10 revenue-generating assets
18:55 Why jumping into automations can backfire
20:32 PR agency case study: automating conference research
25:16 Busting myths about AI adoption
29:09 Who should start using AI now

Links

• Watch on YouTube: https://www.youtube.com/watch?v=XEP3Vs5ml4g
• Connect with Mollie Amkraut Mueller: https://www.linkedin.com/in/mollieamkraut/
• Explore more on Just Curious https://www.justcurious.io/articles/ai-for-non-technical-leaders-turn-one-meeting-into-10-revenue-generating-assets

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Ryan Kurt, CEO & Founder of The AI Lab, advises middle-market CEOs on how to turn AI from hype into measurable operational advantage. A 13-year veteran of generative AI, he’s helped leaders move beyond “AI strategy decks” to real workflow transformation — including a healthcare network that used computer vision to improve care quality and performance-based pay with 99% accuracy. His perspective is clear: the technology isn’t the hard part — leadership ownership is.

You’ll Learn

• Why most AI initiatives fail because CEOs delegate ownership instead of leading transformation themselves
• How to rebuild workflows from first principles instead of layering AI onto broken processes
• What “total ownership” actually means — and why third-party vendors can’t carry your AI strategy
• How agentic workflows unlock capacity by automating repetitive work before it hits your desk
• A behind-the-scenes case study of using computer vision and human-in-the-loop systems to improve care quality, culture, and compensation

Chapters

00:00 Intro
01:00 Ryan’s path from early AI startup to founding The AI Lab
04:15 Why “AI strategy” is the wrong starting point
08:10 The leadership readiness test most companies fail
12:00 What total ownership actually looks like
18:00 Why agentic workflows change the economics of work
23:00 Case study: Using AI to improve caregiver performance
27:30 Human-in-the-loop systems and hybrid AI architecture
30:00 Cultural and operational impact
31:45 How to sequence AI adoption the right way
34:25 Who The AI Lab works with

Links

• Watch on YouTube: https://youtu.be/bdSq4S2_PZU
• Connect with Ryan Kurt: https://www.linkedin.com/in/ryankurt/
• Explore more interviews: https://www.justcurious.io/articles/how-ai-caught-what-bonuses-training-and-pay-raises-couldnt-fix"

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Adam Schwartz, Co-founder and CEO of Parable, explains why most enterprise AI initiatives fail before they ever touch the P&L. Drawing on firsthand work with Fortune 500 and private equity–backed companies, he breaks down how hidden operational inefficiencies block real transformation—and what leaders must measure to unlock durable AI-driven value.

You’ll Learn

• Why executives consistently misjudge how teams actually spend their time—and how that blind spot derails AI strategy
• How “keep-the-lights-on” work and operational debt quietly consume 50–70% of enterprise capacity
• Why data warehouses and dashboards lack the context required for effective AI agents and decision-making
• How mapping work at the activity level enables AI use cases to be prioritized by ROI, not intuition
• What Sunrun uncovered when it quantified technical and operational debt—and how that led to $80M+ in savings

Chapters

00:00 Intro
01:33 Why leaders lack visibility into real work
05:12 The hidden cost of “keep the lights on” work
09:10 Why data warehouses fail at operational understanding
13:20 What a contextual work graph actually looks like
18:29 Measuring AI impact beyond adoption
23:46 Operational debt and resource allocation
30:01 Sunrun case study: uncovering $80M in inefficiencies
35:43 AI vs. process change—what to automate and why
41:57 The mindset shift leaders need for AI at scale

Links

• Watch on YouTube: https://youtu.be/zDDspYqT_7o
• Connect with Adam Schwartz: https://www.linkedin.com/in/adamgregoryschwartz/
• Explore more interviews: https://www.justcurious.io/articles/how-sunrun-found-80m-in-hidden-costs-by-finally-understanding-its-data

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Arman Hezarkhani is the Co-founder & Managing Partner of Tenex, an AI transformation firm helping middle-market and growth companies turn AI from hype into real P&L impact. Drawing from experience scaling Google’s cloud AI tools and building venture-backed startups, Arman breaks down how leaders can actually operationalize AI — not just talk about it. This episode is a practical guide for investors and operators who want measurable results, fast.

You’ll Learn

Why AI adoption is easy for individuals but structurally hard for organizations — and how to close that gap

How to identify high-ROI AI use cases by starting with business goals, not technology

What “AI slop” looks like in practice and how to avoid wasting capital on vaporware

Why Tenex charges on output (story points) instead of hours — and how incentives unlock 10x productivity

How to get your first AI win inside a company to build momentum and executive buy-in

Chapters

00:00 Intro
00:49 Arman’s background and founding Tenex
02:30 Why AI is different from past tech waves
05:26 What AI changes — and what it doesn’t — in business
07:08 How companies should prepare for an AI-native future
09:01 How Tenex identifies and executes AI opportunities
12:15 Diagnostic process and opportunity mapping
15:13 Why CEO-level buy-in is critical
16:31 The Tenex output-based business model
21:28 Generative AI, agents, and AI-powered software builds
23:25 Avoiding “AI slop” and navigating the AI bubble
27:00 Build vs. buy decisions in an AI world
28:39 Real client example: AI-driven revenue and efficiency gains
33:24 Ruthless focus on business goals
34:02 Advice for new Heads of AI

Links

• Watch on YouTube: https://youtu.be/xRV_OnkK9eA
• Explore more interviews: https://www.justcurious.io/
• Connect with Arman Hezarkhani: https://www.linkedin.com/in/ahez/

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Evan Glaser, Founder & CEO of Alongside AI, joins Just Curious to break down how middle-market companies can actually deploy AI, without blowing up risk, compliance, or trust. Drawing on a decade of Fortune 100 experience, Evan explains why governance isn’t a blocker to AI value creation, but the accelerator most operators are missing.

You’ll Learn

Why AI governance is the fastest way to unlock real productivity—not slow it down

How to design practical AI guardrails that let teams innovate safely and move faster

Where middle-market companies typically underestimate their AI risk exposure

How to turn siloed institutional knowledge into a scalable, AI-powered asset

A real-world case study showing how AI reduced onboarding time and unlocked new revenue

Chapters

00:00 Intro
01:24 Why middle-market leaders struggle to start with AI
02:59 Governance as an accelerator, not a brake
04:41 Defining AI guardrails that actually work
06:47 Common governance gaps and blind spots
09:03 What “good” AI governance looks like in practice
14:02 Unlocking trapped institutional knowledge with AI
19:59 Case study: AI-powered onboarding and faster ramp times
30:23 Turning AI questions into a new advisory revenue stream
33:54 The risks of shadow AI
36:13 Lessons from regulated industries that apply everywhere

Links

• Watch on YouTube: https://youtu.be/OXYdxzPgPKg
• Connect with Evan Glaser: https://www.linkedin.com/in/glaserevan/
• Explore more interviews: https://www.justcurious.io/experts/evan-glaser

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Alex Gruebele and Chandler Gonzalez, co-founders of Tau9 Labs, build custom AI systems that solve the messy, high-value problems generic manufacturing software can’t touch. With roots in robotics, hyperscale software, and logistics, they focus on the workflows where context matters most—quoting, downtime, document analysis, and technician knowledge. Their work shows how applied AI can transform mid-market industrial operations in months, not years, by fitting the way factories actually run.

You’ll Learn

• Why generic SaaS breaks in manufacturing—and how custom AI can match real-world workflows without forcing process changes.
• How decades of unstructured documents hide the root causes of downtime, warranty costs, and defects—and how AI can surface them.
• A practical approach to turning vague “AI requests” into solvable, ROI-positive operational problems using on-site discovery and the five whys.
• How AI-accelerated engineering compresses build cycles from quarters to weeks, enabling tools like instant quoting platforms.
• When to build vs. buy: the signals that indicate a custom solution will outperform configurable off-the-shelf tools.

Chapters

00:00 Intro
01:00 Backgrounds & the origin of Tau9 Labs
03:20 Why manufacturing lags in software adoption
05:10 Common operational problems & unstructured data
07:15 Downtime, tribal knowledge, and automation
08:50 Quoting workflows and workflow automation
09:50 How Tau9 diagnoses the “real” problem
12:20 On-site discovery and the five whys
15:20 Case study: injection molding quoting platform
18:10 Designing for speed and user behavior
20:15 Building the platform in four months
22:50 Results: conversion lift & revenue impact
25:10 Build vs. buy in industrial AI
28:45 Why on-site U.S. engineers outperform remote teams
31:20 How AI changes software design principles
33:50 Who Tau9 Labs is best suited to help
35:50 Closing

Links

• Explore more interviews: https://www.justcurious.io/articles/how-tau9-labs-helped-a-manufacturer-cut-quoting-time-from-hours-to-seconds----and-double-win-rates
• Watch on YouTube: https://youtu.be/njuUtQucqHU
• Connect with Alex Gruebele: https://www.linkedin.com/in/alexgruebele/
• Connect with Chandler Gonzalez: https://www.linkedin.com/in/chandlergonzales/

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Felix Rösner, Co-founder of Marble AI, builds AI-driven workflow “clones” that reveal what really happens inside complex enterprise operations. His team helps private equity operators and middle-market leaders uncover hidden inefficiencies, quantify real ROI, and automate with precision instead of guesswork. In this episode, Felix shares why deep context—not tools—is the final moat in AI-enabled organizations.

You’ll Learn

How capturing keystrokes and screen activity uncovers the real workflow variations that break most automation efforts.

Why PE roll-ups routinely misjudge operational reality—and how AI clones surface true time, cost, and redundancy patterns.

How sharing internal best practices (revealed through data) can unlock major efficiency gains even before automation begins.

How to translate thousands of workflow observations into programmatic specifications for reliable, end-to-end digital workers.

The specific types of repetitive, customer-facing tasks where automation consistently returns 100–250 hours per month to teams.

Chapters

00:00 Intro
01:03 Felix’s background and Marble AI’s mission
03:12 Why context—not tools—is the last AI moat
05:06 What it means to instrument real workflows
07:30 The insight that sparked Marble’s approach
10:31 Why PE roll-ups struggle to see operational reality
12:24 AI clones vs. traditional process diagrams
13:34 Balancing workflow capture with privacy and compliance
15:21 Signals a company doesn’t understand its operations
17:03 Case study: diagnosing a PE-backed roll-up
20:40 Deploying the capture stack across teams
23:43 What Marble does with the collected data
26:27 Findings: redundancy, best practices, and ROI
34:05 The 40% redundancy insight
37:26 Practical advice for operations leaders

Links

• Watch on YouTube: https://youtu.be/sc-A0MPiZxE

• Connect with Felix Rösner: https://www.linkedin.com/in/felix-roesner/

• Explore more interviews: https://www.justcurious.io/articles/how-marbles-ai-clones-uncovered-40-redundant-work-and-saved-250-hours-month

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jack Weissenberger, Co-founder & CTO of Ciridae, shares how his team rebuilds core systems and deploys AI agents that remove bottlenecks across finance, operations, and project management. Ciridae works with private-equity-backed companies to identify the real constraints inside a business and replace slow, manual workflows with AI-native software built in days, not months. Jack’s perspective matters because he’s led AI teams at Apple and Salesforce-acquired 10X and now drives full-stack AI transformations in the middle market.

You’ll Learn
• How to identify high-leverage AI opportunities that sit behind the obvious pain point—like uncovering that insurance negotiations, not AR, were the true constraint in a restoration business.
• Why unscoped, natural-language workflows (invoice routing, proposal comparisons, nuanced judgment tasks) are often the best candidates for AI agents.
• How AI-native platforms shrink traditional timelines—enabling full-stack applications, including ERP components, to be rebuilt in days or weeks instead of quarters.
• The operational impact of linking AI automation directly to key financial levers: cycle time, DSO, throughput, and leadership bandwidth.
• Why data readiness—not model quality—is the silent blocker in most failed AI rollouts, and what companies must do before any automation can work.

Chapters
00:00 Intro
01:00 What Ciridae Does
02:48 Why the Middle Market Is Ripe for AI
03:44 Inside the Ciridae Platform
05:04 How Clients Engage & How Audits Work
07:03 Identifying Unscoped Problems for AI
08:44 Why AI Projects Fail
11:08 Rebuilding AI-Native Sources of Truth
12:39 How Fast Can You Rebuild an ERP?
14:13 Where Custom Software Is Heading
15:26 Why Finance & AP/AR Are Perfect for Automation
16:43 Why Home Services Companies Are a Strong Fit
18:29 What “Large Enough” Means for AI Transformation
19:02 Case Study: Uncovering the Real Bottleneck
20:21 Automating Insurance Rebuttals
21:31 Deploying a Production System in 48 Hours
22:42 How AI Cut a 3-Hour Workflow to 10 Minutes
24:18 How This Solution Could Double Enterprise Value
25:32 Staying Open-Minded in AI Audits
26:33 Data Readiness & Integrations
27:59 Who Should Reach Out to Ciridae
29:01 Practical First Steps for Leaders

Links
• Watch on YouTube: https://youtu.be/2PXce31N3IY?si=5PCQaM6DcS9236aM

• Connect with Jack Weissenberger: https://www.linkedin.com/in/jack-weissenberger-9b8549144/

• Explore more interviews: https://www.justcurious.io/articles/how-ai-cut-a-3-hour-workflow-to-10-minutes-for-a-home-restoration-company

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com

Jordan Gurrieri, Co-founder & CEO of BlueLabel, explains how mid-market and enterprise operators can finally escape pilot purgatory and deploy AI systems that scale reliably. Drawing on two decades of automation experience and hundreds of shipped products, he breaks down why AI initiatives fail, how to design for workflow fit from day one, and what it takes to turn tribal knowledge and inconsistent pilots into production-grade, agentic workflows.

You’ll Learn:

• Why AI pilots break when more than a handful of people rely on them—and how to rebuild them for consistency, accuracy, and cost efficiency.
• How to identify high-friction workflows by mapping real user behavior, pain points, and dependency chains.
• How to convert tribal knowledge into durable, queryable agentic systems that support frontline teams in real time.
• Why agentic, workflow-embedded AI drives true competitive advantage while personal productivity tools do not.
• How a regional telecom automated dispatch operations and doubled field technician throughput with an AI-powered workflow system.

Chapters:

00:00 Intro
00:32 Jordan’s background & BlueLabel’s focus
02:09 How early automation shaped his AI worldview
03:31 Why pilots break when scaling AI
05:05 Common traps between pilot and production
07:15 What scaling AI actually requires
10:26 Personal productivity vs. organizational advantage
12:45 Telecom case study: the dispatch bottleneck
15:02 Agentic tools for field technicians
17:59 Change management inside legacy workflows
19:36 Rebuilding the pilot on a scalable API foundation
21:50 Lessons for future AI deployments
23:35 Identifying high-fit workflows
26:08 What makes a strong AI use case
28:05 A myth about AI implementation
30:15 Who should work with BlueLabel
31:52 Advice for leaders under AI pressure

Links:

• Explore more interviews and Jordan Gurrieri's expert profile:  https://www.justcurious.io/experts/jordan-gurrieri
• Connect with Jordan Gurrieri: https://www.linkedin.com/in/jordangurrieri/
• Watch on YouTube: https://youtu.be/T7lhyDkZca0

Just Curious is the content and podcast brand of Pluris, helping leading operators and investors cut through a noisy AI market and find the right partners — from strategy and assessments to full-stack AI development. Our network of applied AI experts spans generative and agentic AI, workflow automation, and custom AI-powered software, helping teams turn curiosity into measurable value.

Explore more interviews and connect with experts at https://www.checkpluris.com

Subscribe to our newsletter at https://just-curious-ai.beehiiv.com