This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking.Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience.

Visit https://www.extremenetworks.com/ to learn more.

JotForm began nearly twenty years ago as a simple online form builder.

Today, it has grown into a platform powering millions of users and has recently stepped into a new era of AI. In this episode, Aytekin Tank, founder and CEO of JotForm, shares the story of how the company pivoted from forms to launching AI Agents that are changing the way small and medium-sized businesses handle customer support and automation.

Aytekin explains how JotForm’s AI journey started as an internal experiment to fill out forms by voice, only to discover that most users wanted it for customer service. That insight sparked the creation of JotForm AI Agents, tools that don’t just answer questions, but perform tasks, scale support teams, and transform the customer experience.

Beyond the technology, Aytekin outlines a bold vision of the future where every business, no matter the size, will have its own AI-powered agent available around the clock to schedule appointments, answer questions, and even process transactions.

This conversation explores how AI is reshaping customer service and why small businesses, nonprofits, and educators stand to benefit the most from this wave of innovation.

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(00:00) The Scale of JotForm Today and the AI Vision
(01:32) Aytekin’s Journey: From Developer to Bootstrap Founder
(03:36) The Pivot: From Voice Forms to AI Customer Service
(05:25) Building and Launching JotForm AI Agents
(06:20) Using AI Internally: Cutting Tickets and Boosting Resolution Rates
(08:13) Why AI Agents Go Beyond Chatbots
(12:22) Demonstrating JotForm AI in Action
(21:40) The Tech Stack Behind JotForm’s AI Agents
(24:59) Training and Teaching Your Own AI Agent
(33:27) Competition, Differentiation, and Market Strategy
(36:55) Why Small Businesses Need AI the Most
(38:24) The Future: Every Business With Its Own AI Agent
(40:19) Pricing, Growth, and Lessons in Scaling AI
(42:26) Slow Growth vs Explosive Scale and Lessons Learned
(43:55) Aytekin’s Vision for AI in Business

Try OCI for free at http://oracle.com/eyeonai

This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved.

Matthew Carroll, CEO and co-founder of Immuta, joins the Eye on AI podcast to explore how data access governance is evolving in the age of generative AI.

As AI drives a surge in both human and non-human data consumers, traditional security models are no longer enough. Matthew explains how Immuta automates compliance, enforces policies across global jurisdictions, and scales secure access for enterprises—from blinded clinical trials in pharma to cross-border data sharing.

Discover why AI-powered governance agents, risk-based access controls, and native cloud integration are the future of compliant, scalable data use.

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(00:00) How Immuta Governs Data in the AI Era
(02:59) Security Alone Isn’t Enough in AI
(05:24) From U.S. Intel Roots to Immuta’s Platform
(07:38) Pharma Trials: Protecting Billions in Drug Development
(12:58) The Data Marketplace & Access Negotiations
(16:07) Why Native Integration Beats Proxy Models
(20:33) Managing Data Across Borders & Sovereignty Laws
(25:33) The Data Governor Bottleneck (and AI Solution)
(31:05) Inside Immuta’s SaaS Model & User Roles
(33:26) Big Data Lessons Driving AI ROI
(41:05) The Growing Data Governance Market
(45:48) Storage Portability & Apache Iceberg Explained
(48:32) Future Shift to Risk-Based, AI-Driven Access

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.


How does a 150,000-employee global leader make AI work at scale?

In this episode of Eye on AI, host Craig Smith sits down with Julia Peyre, Head of AI Strategy & Innovation at Schneider Electric, to explore how the company is pioneering enterprise AI adoption through its AI Hub, hybrid AI systems, and real-world digital twin applications.

From breaking data silos and embedding AI into hardware, to partnering with startups and building predictive maintenance solutions, Julia shares a blueprint for bringing AI from pilot programs to full-scale deployment, across both internal processes and customer-facing products.


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(00:00) Preview and Intro
(01:58) Meet Julia Peyre & Her Role
(03:19) Inside Schneider’s AI Hub
(05:51) AI in Industrial Automation & Robotics
(08:43) Internal vs External AI Applications
(13:54) Why Schneider Is Ahead in AI Adoption
(15:57) Centralized AI Hub Model
(19:38) Hybrid AI: Combining Physics & Data
(25:44) Early Steps in Multi-Agent Systems
(29:54) Breaking Data Silos for AI at Scale
(32:02) Predictive Maintenance with Hybrid AI
(37:03) Long-Term View on AI Automation
(42:37) Advice for Young Professionals in AI
(44:21) Framework for Evaluating AI Solutions
(50:19) Involving End Users in AI Testing

In this episode of Eye on AI, host Craig Smith sits down with Alex Salazar, co-founder and CEO of Arcade.dev, to explore what it really takes to build secure, scalable AI agents that can take real-world actions.

While everyone’s talking about the future of autonomous agents, most never make it past the demo stage. Why? Because agents today lack secure infrastructure to connect with real tools like Gmail, Slack, Notion, GitHub—and do so on behalf of users without breaking authentication protocols.

Alex shares how Arcade solves the missing layer in AI agent development: secure tool execution, user-specific authorization, OAuth flows, and production-ready consistency.

Whether you're building with GPT‑4, Claude, or open-source models, Arcade handles the hard part—making agent actions actually work.


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(00:00) Why AI Agents Can’t Take Action (Yet)
(01:27) Meet Alex Salazar: From Okta to Arcade
(03:39) What Arcade.dev Actually Does
(05:16) Agent Protocols: MCP, ACP & Where Arcade Fits
(07:36) Arcade Demo: Building a Multi-Tool AI Agent
(11:16) Handling Secure Authentication with OAuth
(14:40) Why Agents Need User-Tied Authorization
(19:25) Tools vs APIs: The Real Interface for LLMs
(23:41) How Arcade Ensures Agents Go Beyond Demos
(25:48) Why Arcade Focuses on Developers, Not Consumers
(27:55) The Roadblocks to Production-Ready Agents
(31:15) How Arcade Integrates Into Agent Workflows
(33:16) Tool Calling & Model Compatibility Challenges
(34:49) Arcade’s Pricing Model Explained
(36:20) Competing with Big Tech: IBM, AWS & Others
(38:38) Future of Agents: From Hype to Workflow Automation
(41:58) Real Use Cases: Email Agents, Slack Bots, Finance & More
(46:17) Agent Marketplaces & The Arcade Origin Story

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.


What happens when AI meets the chaos of real-world customer support?

In this episode of Eye on AI, we sit down with Ryan Wang, co-founder and CEO of Assembled, to unpack how AI is transforming the future of customer service, without replacing humans.

Ryan reveals how Assembled went from a workforce scheduling tool to a full-stack AI support platform used by companies like Stripe, Robinhood, and Honeylove.

You’ll learn how conversational AI agents are handling up to 75% of support inquiries, why voice is the next big frontier, and how AI copilots are helping human agents become 15% more productive.

But this isn’t just hype. Ryan shares the hard economic truths behind automation—why humans aren’t going away, how companies are navigating global workforce optimization, and why hybrid AI + human systems are here to stay.

This episode gives you a front-row seat into how the smartest companies are rethinking support at scale.

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(00:00) Preview and Intro
(01:37) Ryan Wang’s Journey from Stripe to Assembled
(04:55) Launching Assembled
(09:49) From Scheduling Tool to AI-Powered Support
(12:11) Who Uses Assembled: Companies vs. BPOs
(14:57) Building Conversational and Voice AI Agents
(21:10) Competing with Zendesk, Salesforce & Crescendo
(23:07) How Assembled Integrates with Customer Support Stacks
(25:40) The Niche Power of Workforce Management Tech
(31:16) Why the Customer Support Market Is Ripe for Disruption
(33:47) How Assembled Swaps Between OpenAI, Claude & Others
(37:56) Evaluating LLMs with Golden Datasets and 'Vibe Checks'
(41:20) Multilingual Support and the Challenge of Europe
(45:11) Industry Focus vs. Complexity Focus
(47:43) Voice AI: The Next Big Frontier?
(50:18) The Truth About AI Replacing Jobs in Support
(54:39) The Automation Paradox: Why Labor Isn’t Shrinking

What if the biggest challenge in AI isn't how fast chips can compute, but how quickly data can move?

In this episode of Eye on AI, Nandan Nayampally, Chief Commercial Officer at Baya Systems, shares how the next era of computing is being shaped by smarter architecture, not just raw processing power. With experience leading teams at ARM, Amazon Alexa, and BrainChip, Nandan brings a rare perspective on how modern chip design is evolving.

We dive into the world of chiplets, network-on-chip (NoC) technology, silicon photonics, and neuromorphic computing. Nandan explains why the traditional path of scaling transistors is no longer enough, and how Baya Systems is solving the real bottlenecks in AI hardware through efficient data movement and modular design.

From punch cards to AGI, this conversation maps the full arc of computing innovation. If you want to understand how to build hardware for the future of AI, this episode is a must-listen.

Subscribe to Eye on AI for more conversations on the future of artificial intelligence and system design.


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(00:00) Why AI’s Bottleneck Is Data Movement
(01:26) Nandan’s Background and Semiconductor Career
(03:06) What Baya Systems Does: Network-on-Chip + Software
(08:40) A Brief History of Computing: From Punch Cards to AGI
(11:47) Silicon Photonics and the Evolution of Data Transfer
(20:04) How Baya Is Solving Real AI Hardware Challenges
(22:13) Understanding CPUs, GPUs, and NPUs in AI Workloads
(24:09) Building Efficient Chips: Cost, Speed, and Customization
(27:17) Performance, Power, and Area (PPA) in Chip Design
(30:55) Partnering to Build Next-Gen Photonic and Copper Systems
(32:29) Why Moore’s Law Has Slowed and What Comes Next
(34:49) Wafer-Scale vs Traditional Die: Where Baya Fits In
(36:10) Chiplet Stacking and Composability Explained
(39:44) The Future of On-Chip Networking
(41:10) Neuromorphic Computing: Energy-Efficient AI
(43:02) Edge AI, Small Models, and Structured State Spaces

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.

Grammarly is no longer just a writing assistant. It's building an AI productivity platform that could rival Microsoft Copilot. In this episode, Luke Behnke, VP of Enterprise Product at Grammarly, shares how the company is moving beyond grammar correction into intelligent agents, enterprise workflows, and real-time AI tools.

We dive into Grammarly’s new Authorship feature, why AI fluency is becoming essential at work, how Grammarly is integrating tools like Coda and Superhuman, and what the future of multi-agent systems looks like.

If you're curious about where AI at work is really heading, this conversation will give you a clear and powerful glimpse.

(00:00) Preview and Intro
(03:37) Meet Luke Behnke
(05:00) Grammarly's Origin Story and Early Vision
(09:11) Grammarly’s UX Advantage
(13:30) Competing With Microsoft Copilot and Built-In Assistants
(17:48) What Is “Authorship” and Why It Matters
(20:31) AI Detection vs Authorship Tracking
(25:05) The Future of AI Transparency
(27:43) Why AI Fluency Will Be a Job Requirement
(32:04) Grammarly's Agentic Vision
(34:11) The Rise of Context-Aware Enterprise Agents
(38:24) Use Cases: Automating Tasks Across Tools with AI
(40:21) The Coda Acquisition & Building the Agent Platform
(44:48) The Future of Interoperable AI Agents
(47:43) Why Agent Oversight Is Crucial in Enterprise AI
(55:57) Measuring Grammarly’s ROI in the Enterprise

This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking.Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience.

Visit https://www.extremenetworks.com/ to learn more.

In this episode, Craig Smith sits down with Benjamin Encz, co-founder and CEO of Ashby, the AI-powered recruiting platform that is transforming how companies hire.

Ashby is disrupting the $650B recruiting industry by combining automation, data, and large language models to streamline the entire hiring process, from job postings to resume screening and interview scheduling. With clients like OpenAI and Shopify, Ashby is setting a new standard for modern recruiting.

Benji shares how AI is boosting efficiency while keeping human judgment at the center, and what the future of hiring could look like as these tools continue to evolve.

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