Alex Urist is helping solve one of the biggest barriers to EV adoption: charging infrastructure that can scale without waiting years for grid upgrades. As co-founder of XCharge North America, he is leading the development of EV charging and energy storage solutions designed for the North American market. XCharge’s GridLink platform recently won a BIG Innovation Award for its battery-integrated DC fast charging technology.

In this episode, Russ and Alex explore why EV charging is harder to deploy than many people expect. Alex explains how grid limitations, transformer delays, permitting, financing, and utility capacity can slow down new charging sites, especially when high-speed DC fast chargers require power that many locations do not already have.

They dive into GridLink, XCharge’s battery-integrated, bi-directional DC fast charger. Alex explains how the system stores energy in an onboard battery, boosts output to vehicles, accepts solar power directly, and can even support buildings or the grid when needed. This approach can help reduce dependence on immediate utility upgrades while making more sites viable for fast charging.

The conversation also covers the economics of EV charging, including utilization, demand charges, equipment costs, operational costs, and the importance of choosing the right real estate. Alex shares why fleets, hospitality sites, dealerships, travel centers, and commercial properties all represent major opportunities for battery-backed charging infrastructure.

Along the way, Alex discusses solar integration, bidirectional energy, energy storage, fleet depot charging, the future of grid resiliency, and why EV charging stations may become part of a broader distributed energy network.

Topics Covered:

[00:00] Welcome and intro, Alex Urist and XCharge’s BIG Innovation Award win

[00:40] XCharge’s background in EV charging and energy storage

[01:55] Why charging availability affects EV adoption

[02:31] Why grid limitations slow EV infrastructure deployment

[04:19] What 480 three-phase power means in practical terms

[05:20] Matching charging locations to real-world activity

[07:31] EV charging speed and the smartphone charging comparison

[08:19] Perceived charging availability and consumer confidence

[10:08] Grid competition from AI data centers and other energy users

[10:51] Where deployments break down: financing, permitting, and power availability

[12:27] How battery-integrated charging works

[12:48] AC, DC, and how fast chargers transfer power to vehicles

[15:12] How integrated batteries can speed deployment timelines

[16:03] Why financing is critical to EV infrastructure growth

[18:13] Demand charges and how they affect charging economics

[18:59] Modeling ROI for charging networks

[20:36] Using solar and batteries to address grid capacity issues

[21:27] GridLink’s ability to support buildings and return power to the grid

[23:45] Benefits for property owners and commercial sites

[24:07] What a 60 kilowatt solar array looks like in practice

[25:05] Why direct solar integration improves charging efficiency

[26:08] Efficiency loss from energy conversion

[26:34] Fleet depot use cases and load balancing

[28:56] Why utilities are becoming interested in battery-backed chargers

[29:07] Charging stations as part of local energy infrastructure

[31:42] How EV charging stations become part of the broader energy grid

[33:44] What the next five years could look like for EV charging

[35:35] Why real estate matters most in EV charging investments

[36:15] Why gas stations are not always easy charging sites

[37:37] Convenience stores, hotels, rentals, and dealerships as charging opportunities

[39:03] Finding power availability and working with utilities

Madan Moudgal is helping healthcare organizations use AI to improve operations without removing the human judgment that sensitive clinical decisions require. As Chief Digital Officer at Sagility, he leads technology transformation for a healthcare operations company serving U.S. payers and providers. Sagility’s Nurse Assist solution recently won an AI Excellence Award for helping clinical teams review prior authorization cases faster and more accurately.

In this episode, Russ and Madan explore why healthcare is one of the hardest industries to modernize with AI. Madan explains how legacy systems, strict regulation, data privacy requirements, and complex workflows make healthcare transformation different from other industries.

They dive into prior authorization, one of healthcare’s most difficult and controversial processes. Madan explains why the process exists, how it helps address waste, fraud, and abuse, and why the challenge is balancing cost control with patient access to appropriate care.

The conversation also covers why Sagility uses the term augmented intelligence instead of full automation. Madan explains that AI can summarize documents, extract relevant clinical details, compare information against guidelines, and provide recommendations, but nurses and clinical experts still need to make the final decision.

Along the way, Madan discusses domain-specific AI models, clinical language models, guardrails, PHI protection, data curation, AI governance, change management, and why successful healthcare AI requires careful testing, incremental rollout, and trust-building over time.

Topics Covered:

[00:00] Welcome and intro, Madan Moudgal and Sagility’s AI Excellence Award win

[00:32] Sagility’s background as a healthcare operations company

[01:21] Why healthcare and payment systems are so complex

[01:43] The challenge of adopting AI in a regulated healthcare environment

[02:37] Lessons from implementing technology change in healthcare

[02:47] Working around large legacy healthcare systems

[03:45] Why prior authorization is such a difficult healthcare problem

[03:57] Balancing waste reduction, cost control, and patient access to care

[05:27] Why Sagility uses augmented intelligence instead of automation

[05:40] Keeping humans in the loop for clinical decision-making

[06:46] Where AI can help and where humans must remain accountable

[09:14] Extracting and summarizing clinical data from case documents

[10:27] Why Sagility focuses on domain-specific AI models

[11:03] Building trust through clinical language models

[12:01] Why accuracy is essential in healthcare AI

[13:18] Guardrails for compliance, PHI, and regulatory requirements

[14:37] Reducing review time and what that means for patients

[15:35] Reviewing medical records, clinical guidelines, and recommendations

[16:34] How Nurse Assist supports nurse reviewers

[17:43] Early benefits from speed, efficiency, and lower costs

[18:38] Integrating AI with legacy healthcare systems

[18:56] Why data curation matters before AI can work effectively

[20:24] AI governance and aligning with client policies

[20:47] Change management in enterprise healthcare workflows

[21:50] Balancing innovation and risk management in healthcare

[22:42] Why healthcare AI rollouts cannot be rushed

[24:44] Whether healthcare will ever become fully automated

[25:06] Why healthcare is more likely to remain augmented than fully automated

[27:44] Other healthcare areas ready for AI transformation

[28:22] Automating simpler member and patient interactions

[29:27] Virtual agents and consumer expectations in healthcare

[30:50] Claims accuracy and payment integrity opportunities

[32:04] What healthcare may look like in the next 30 years

Asaf Goldstein is helping IT support teams use AI to create faster, more proactive, and more human customer experiences. As Senior Director of Global Customer Care at SysAid, he leads a global support organization using AI to identify trends, resolve issues faster, deflect routine tickets, and give agents better context before they ever speak with a customer.

In this episode, Russ and Asaf explore how AI is changing customer care from a reactive cost center into a proactive driver of customer loyalty. Asaf explains why the future of support is not just automation, but the right balance between AI, human empathy, and expert problem solving.

They dive into how SysAid uses AI across its support organization, including AI copilots, internal AI agents, sentiment analysis, ticket deflection, quality scoring, and proactive issue detection. Asaf shares examples of how AI helped his team identify critical issues, assemble engineering and DevOps teams quickly, and resolve customer problems before they escalated.

The conversation also covers the risks of over-automation. Asaf explains why AI should solve simple questions, summarize context, and guide agents, but also know when to hand a customer to a human. He shares how SysAid reduced unhappy customer survey responses from around 40 per quarter to 5 by combining AI-enabled insights with personal follow-up from team leads.

Along the way, Asaf discusses the rise of AI managers, the skills support agents need to stay relevant, why guardrails matter, and how companies can create customer service experiences that feel faster, smarter, and more personal.

Topics Covered:

[00:01] Welcome and intro, Asaf Goldstein and SysAid’s customer service award win

[00:28] SysAid’s background in IT service management software

[01:10] What is changing in AI-powered customer support

[01:26] Moving support from reactive to proactive

[02:33] Managing global customer care in an AI-driven environment

[02:39] How AI helps identify trends before customers report issues

[03:20] Using AI and Discord to detect critical customer issues

[04:22] Why a great support experience can increase customer loyalty

[04:57] Creating a “wow experience” in support

[05:41] Where pressure to automate support comes from

[05:57] How SysAid uses AI to resolve routine tickets

[07:30] Why complex support still needs expert human agents

[07:50] The risk of over-automating customer interactions

[08:55] Defining the human layer in modern support organizations

[09:26] Why personal touch still matters in technical support

[10:18] When humans are still absolutely critical

[10:30] Reducing unhappy customers through personal follow-up

[13:00] Empathy as a core part of customer service

[13:36] Where AI works well and where it falls short

[15:38] Deciding what gets automated and what stays human

[17:14] How AI changes the role of support agents

[19:04] Skills that matter most for the future of customer care

[20:38] The rise of AI managers inside support teams

[21:13] How AI helps agents personalize customer interactions

[22:27] How customer expectations will change as AI becomes common

[23:27] Common mistakes when rolling out AI in support

[23:47] Why AI answers need validation, formatting, and guardrails

[25:23] Lessons from the shift from phone support to chat support

[26:10] Metrics AI support managers should track

[27:52] Principles for adding AI without losing the human experience

[28:15] Guardrails, monitoring, and continuous improvement

[29:43] Final thoughts on creating wow moments with AI and people