Enterprise Aligned AI

✉️ Subscribe for free to receive new episodes: https://enterprisealignedai.com/subscribe

Reena Patil, SVP of Product Management at Expedia Group, and Navin Thadani, co-founder and CEO of Evinced, explain how Expedia deploys AI agents and why accessible code makes agents work better. Expedia's onboarding agent cut partner onboarding from up to 14 days to under a day. Expedia keeps its agents inside hard limits and checks their work. Evinced makes software that finds and fixes accessibility defects in websites and mobile apps. Navin explains why Claude Code can't make a site accessible on its own, and how a deterministic harness cut a bank's forecast accessibility bill from $27 million a year to $3 million. They also cover the AI trust gap in travel, agents that hire humans, and how accessible sites can make browser agents 30X to 100X cheaper.

💡 KEY INSIGHTS

• Intent-based travel answers: Travelers now ask detailed questions in plain language, such as whether the pool is heated and when it closes, requiring new information.

• Autonomous supply: Expedia's onboarding agent cut partner onboarding from up to 14 days to under a day, by proactively capturing partner insights.

• Bounded autonomy: Expedia lets agents act on their own only inside hard limits, such as price floors and a fixed set of ZIP codes.

• Verification: Expedia cross-checks agent output against its own data and handsoff to its human sales team.

• Deterministic AI 45X advantage: Pages built by Claude average 45 accessibility issues, but Evinced's test, fix, retest loop brings that under one.

• The AI trust gap: Expedia's data shows about 68% of travelers still only feel comfortable booking with a trusted brand rather than via AI

📺 WATCH ON YOUTUBE

https://youtu.be/gjYamaZQVhA

⏱ CHAPTERS

0:00 Welcome and Guests

1:25 Reena Career Journey

2:01 Navin Founding Story

3:16 Why Accessibility Is Hard

4:22 Expedia Marketplace Overview

5:34 Agentic AI Use Cases at Expedia

7:07 Measuring AI ROI

9:58 Expedia Partner Adoption

11:25 Automating Accessibility Fixes

14:25 What Accessibility Issues Look Like

18:39 Why Claude Code Can't Fix Accessibility

20:24 Deterministic AI is 45X better: Test, Fix, Retest

23:22 Unharnessed AI Burns Tokens and Time

26:24 Bounded Autonomy at Expedia

27:43 How Expedia Verifies AI Agents

30:44 Accessible Sites Help AI Agents

34:55 The AI Trust Gap

37:00 Fraud and Agents That Hire Humans

38:04 Booking on Expedia From Claude or Gemini

40:03 Looking Ahead and Closing

👤 GUESTS

Reena Patil, SVP of Product Management, Expedia Group: https://www.linkedin.com/in/reenanorapatil/

Navin Thadani, Co-founder and CEO, Evinced: https://www.linkedin.com/in/nthadani/

🔗 CONNECT

Website: https://enterprisealignedai.com

LinkedIn: https://www.linkedin.com/in/apsinha/

X: https://x.com/aparnabsinha

📖 Episode insights: https://enterprisealignedai.com/episodes/marketing-ai-with-cohesity-and-sumble/✉️ Subscribe for free to receive new episodes: https://enterprisealignedai.com/subscribeCarol Carpenter, Chief Marketing Officer of Cohesity, and Anthony Goldbloom, CEO and co-founder of Sumble join Aparna Sinha in this deeply insightful conversation about the impact of AI in Marketing and go-to-market organzations. Carol's team built custom agents for translation and brand compliance, targeting a 60% benefit in translation cost. She talks about about where AI is not a game changer, and how much human work is required to make agents work. Anthony sold Kaggle to Google in 2017 and founded Sumble to build the most pristine go-to-market data layer for grounding agents. He explains why a language model on its own cannot tell you which team inside an account is ready to buy, how to create clean data, and how he keeps Sumble out of the LLM kill zone.

💡 KEY INSIGHTS

• 152 touch points: Enterprise B2B took 57 touches to close a decade ago. Carol now sees 152.

• Real ROI: Lead follow-up moved from 20% to 80% of MQLs, and translation cost on track to fall 60%.

• Agents still need people: The customer journey does not automate itself. Human creativity is required to design the sequences and the strategy.

• Grounding Agents in Hard-to-Find Data: Language models handle the thinking. A hard-grounded corpus supplies the facts about what companies are doing.

• Team-level intelligence: Sumble maps tech stacks and buying windows to individual teams inside an account, not just to the company.

• The unglamorous part: Building Sumble is 80% cleaning data and 20% complaining about cleaning data.

Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-agents-depend-on-clean-data-cohesity-cmo-kaggle-founder/id1890781384?i=1000784472053

YouTube Video: https://youtu.be/JVO3V2rORhg

⏱ CHAPTERS

00:00 152 Touch Points to Close One Enterprise Deal

01:04 Meet the Guests: Cohesity's CMO and Sumble's CEO

02:49 How Cohesity Uses AI

04:09 Founding Kaggle and Sumble

05:50 Where CMOs See Real ROI from AI

07:33 Busting the Hype of AI in Marketing

09:04 Agents Require Humans: Don't Underestimate the Work

11:23 Cutting Translation Cost 60% and Moving MQLs 20% to 80%

14:55 Sumble Provides Team-Level Tech Stacks and Buying Windows

17:43 Sumble's Moat: Pristine Data on 40,000 Companies

21:57 Data Privacy Is Paramount for Enterprises

24:06 Building Sumble Is 80% Cleaning Data

27:02 Build vs Buy: Should Cohesity Build Its Own Knowledge Graph

31:22 Cohesity's Brandi Agent and the Pre-Event ROI Calculator

36:51 Organization and Talent: Defining the GTM Engineer

38:37 Hiring for AI: "Tell Me About Your Latest Prompt"

40:30 Sumble: Staying Out of the LLM Kill Zone

42:13 Closing Thoughts

👤 GUESTS

Carol Carpenter, Chief Marketing Officer, Cohesity:

https://www.linkedin.com/in/carolwcarpenter/

Anthony Goldbloom, CEO and Co-founder, Sumble: https://www.linkedin.com/in/anthonygoldbloom/

🔗 CONNECT

Website: https://enterprisealignedai.com

LinkedIn: https://www.linkedin.com/in/apsinha/

X: https://x.com/aparnabsinha

#EnterpriseAI #AgenticAI #Cohesity #Sumble #MarketingAI

Enterprise Aligned AI — Episode 5: Who Owns the Legal AI Harness? Featuring global law firm Baker McKenzie and Legora, the rapidly growing legal startup.

⏱ CHAPTERS00:00 Legal AI: Whose Harness Is It Anyway?

00:33 Meet the Guests: a Global Law Firm and a $5.6B Legal AI Startup

01:45 Why a Law Firm Started Building Its Own AI

03:10 Legora: How This High-Growth AI Startup Was Founded

04:57 Legora's Vision: Making Law More Accessible and Creative

06:57 Baker McKenzie on the New Legal Work AI Enables

09:24 Baker McKenzie: The Three Waves of AI in Law

10:57 Legora's "Legal Engineer": A Lawyer Who Builds AI

12:50 Legora's Real Moat: Deep Enterprise Integration

17:42 What Legora's Legal Harness Does That Claude Code Can't

21:05 Baker McKenzie: When to Own vs Rent Your AI Harness

22:26 Baker McKenzie: Use Human Judgment Upstream to Design the System

25:05 Baker McKenzie: From Billable Hours to Fixed Fees

26:25 Legora: Why It Moved to Consumption-Based Pricing

28:01 How Legora Scaled From $1M to $100M in Under 18 Months

34:03 Baker McKenzie: Same-Day Legal Work in a Cyber Attack

38:15 When a Local Lawyer Beats a Frontier AI Model

39:46 When Using AI Costs the Client More

40:37 Build vs Buy for Legal AI

44:12 How Legora Stands Out in a Crowded Vendor Market

47:10 The Future of Law and Lawyers

👤 GUESTS

Danielle Benecke, Founder and Global Head of Applied AI, Baker McKenzie: https://www.linkedin.com/in/daniellebenecke/

Max Junestrand, CEO and Co-Founder, Legora: https://www.linkedin.com/in/maxjunestrand/🔗

CONNECTWebsite: https://enterprisealignedai.com

LinkedIn: https://www.linkedin.com/in/apsinha/

X: https://x.com/aparnabsinha

#EnterpriseAI #AgenticAI #LegalAI #Legora #BakerMcKenzie

📖 Episode summary + insights: https://enterprisealignedai.com/episodes/coursera-becoming-ai-native/✉️ Subscribe for free to receive new episodes: https://enterprisealignedai.com/subscribeCoursera is fourteen years old and public, in an industry everyone assumes AI will replace. Instead of blocking AI, CTO Mustafa Furniturewala leaned way in, building the enablement and guardrails to make it safe. I talk with Mustafa and Jiquan Ngiam, founder of Mint MCP, about becoming AI-native: the MCP gateway that governs data access, migrating a decade of code in hours, background agents that work like coworkers, and how business users now build their own AI skills.💡 KEY INSIGHTS • Block or Embrace: blocking AI pushes people to unsafe workarounds, enablement is safer • MCP vs APIs: MCPs built for agents with security boundaries an API key cannot express • MintMCP Gateway: governs MCP sprawl and bundles tools by role, empowering IT and users • Migrating Code with Tech Debt: what took weeks now runs in hours across 200+ repos • Background agents: a sandboxed Claude and Codex review loop, triggered from Slack • Business users: Coursera forked Anthropic's knowledge-work skills, and a quarter of AI usage now comes from non-coder business users🎧 PREFER Apple: {Apple URL — pending}YouTube: https://youtu.be/hcKmyD27mms⏱ CHAPTERS 00:00 Migrations and Tech Debt: Rewriting in Hours at Coursera 02:03 AI in Education: To Block or Embrace? 05:46 Personalization at Scale: Assessments and AI Tutors 10:02 MCP vs APIs and CLIs: Secure Data Access for Agents 14:07 Skills: Teaching AI your SOPs as Markdown 18:03 MCP Governance: Coursera's Requirements 21:53 AI Native Enterprise: Coursera's Journey 24:37 AI Does the Grunt Work, Engineers Do the Rest 27:24 GraphRAG vs Inline Context for Large Codebases 30:37 Building a Culture of AI Adoption 32:35 The New Agentic Engineering Lifecycle 35:28 Background Agents That Act Like Coworkers 39:41 When a Supply-Chain Attack Turns Your AI Against You 43:28 Unlocking Business Users with Claude Cowork 47:42 The Future of Personalized Learning👤 GUESTSMustafa Furniturewala, CTO, Coursera: https://www.linkedin.com/in/mustafaf/

Jiquan Ngiam, Founder & CEO, Mint MCP: https://www.linkedin.com/in/jngiam/🔗 CONNECTWebsite: https://enterprisealignedai.comLinkedIn: https://www.linkedin.com/in/apsinha/X: https://x.com/aparnabsinha#EnterpriseAI #AgenticAI #Coursera #MCP #MintMCP

📖 Episode summary + insights: https://enterprisealignedai.com/episodes/agentic-commerce-with-logitech-and-typesense/

✉️  Subscribe for free to receive new episodes: https://enterprisealignedai.com/subscribe                                          
This episode of Enterprise Aligned AI explores how agents are reshaping eCommerce.

💡 KEY INSIGHTS

• Deepa Shekhar (Logitech) outlines Three Tracks of Agentic Commerce: shopping inside LLMs, brand-owned agents, and agents as autonomous buyers that rely on structured data and operational excellence over ads and storytelling
• Jason Bosco (TypeSense) explains why search and retrieval are critical for agents, emphasizing fast, structured pre-processing of large data, unified product and business data, and approaches like hybrid search and LLM-assisted intent-to-query mapping.
• The Missing Product Catalog: no universal real-time product API for LLMs, fragmented product catalog and commerce protocols (ACP, UCP, MCP)
• Content Strategy Inverts: from brand storytelling to answering customer questions, structured for LLMs to read via llms.txt
• Brand Agents Need Shared Intelligence: isolated chatbots fragment the experience; one shared AI layer should power web, app, WhatsApp, and RCS
• Autonomous Agents that make decisions on real-time inventory and upto date operational status. Post-purchase gaps, legacy OMS/WMS constraints, emerging efforts like ONX• Guardrails for the Buy Click: financial controls, auditability, observability, and defenses against hallucinations and prompt injection

⏱ CHAPTERS

• 00:00 Agents Disrupt E-Commerce and Advertising
• 00:21 Introduction to Agentic AI and E-commerce Transformation
• 02:34 Exploring the Three Tracks of Agentic Commerce
• 05:49 Role of Search in Agentic Retrieval
• 08:14 Integrating Product Catalogs, Data and Protocols
• 10:55 Future of Real-Time Data and Search13:49 Shifts in Content Strategy for E-commerce
• 17:09 Modern Retrieval Stack
• 22:08 Building Intelligent Brand Agents
• 26:32 Evolving Protocols for Payments, Inventory and Operations
• 33:16 Track Three Personal Agent Buyers
• 35:58 Agents Evaluate Vendors
• 40:12 Security Guardrails and Governance

📺 WATCH ON YOUTUBE  https://youtu.be/vFNzd3rh3wY         

🎧 ALSO ON APPLE PODCASTS  https://podcasts.apple.com/us/podcast/ep3-agentic-commerce-with-logitech-and-typesense/id1890781384?i=1000769162471   

👤 GUESTS                                                                                                                         

Deepa Shekhar, Director of E-commerce & Digital Marketing Technologies, Logitech: https://www.linkedin.com/in/deepa-shekhar-677779/

Led the move to composable commerce architecture on Logitech.com (~$349M in direct-to-consumer revenue). Logitech.com was named PCMag Reader's Choice 2025 Best Manufacturer Online Store and won the "Growth Engine" award in Semrush's inaugural 2025 AI Visibility Awards for Consumer Electronics, measured across thousands of real prompts in ChatGPT and Google AI Mode.

Jason Bosco, CEO & Co-founder, Typesense: https://www.linkedin.com/in/jasonbosco/

Typesense is an open-source search engine running 10B+ queries a month on Typesense Cloud, with 25,000+ GitHub stars and 12M+ Docker pulls. Built as a single C++ binary, Typesense is the open-source alternative to Algolia and Pinecone, and is revenue-funded, not VC-backed. Before Typesense, Jason was VP of Engineering at Dollar Shave Club and VP of Technology at Verishop.

  🔗 CONNECT    

Website: https://enterprisealignedai.com

LinkedIn: https://www.linkedin.com/in/apsinha/

X: https://x.com/aparnabsinha

📖 Episode summary + insights: https://enterprisealignedai.com/episo... ✉️ Subscribe for free to receive new episodes: https://enterprisealignedai.com/subsc... This episode focuses on Royal Bank of Canada’s (RBC) $1B AI transformation - how one of the world's largest financial institutions is moving beyond experimentation to Enterprise-wide AI deployment. Our guest is Vinh Tran, Vice President of Data and AI Platforms and RBC Fellow

💡 KEY INSIGHTS • The $1B Investment: RBC committed ten figures to transform the entire organization with AI • Self-Serve Agents: RBC assist automates complex workflows while maintaining strict compliance • Build vs buy in regulated industries: Building is easier than ever and enables greater control • MCP Gateway + OpenTelemetry deliver security and observability for regulated agentic AI • Lumina, RBC's modern data platform, is the foundation making "AI for All" possible • Engineers become "builders" who orchestrate AI tools, not only write code🎧 PREFER VIDEO or APPLE PODCASTS?

YouTube: https://www.youtube.com/watch?v=pVWtq0yCrEA Apple: https://podcasts.apple.com/us/podcast... ⏱ CHAPTERS 00:00 Introduction to Vinh Tran 03:34 The Scope of RBC's $1B AI Transformation 06:10 Transforming Customer Service 08:47 Measuring ROI of AI Across Business Units 14:23 Build vs. Buy: Why Build in Regulated Enterprises 18:37 Self-Service Agents at RBC 22:25 Setting Platform Standards: MCP and OpenTelemetry 26:00 Preparing Data for AI: Best Practices 30:33 Overcoming Data Readiness Challenges 33:16 RBC's Control Plane for Reliable Agentic AI 37:10 Use Cases for LLMs in Banking 40:37 RBC Assist: Productivity Chatbot or Superpower? 43:13 Workforce Transformation through 'AI for All' 45:58 Hiring the Next Generation of Builders 49:25 Advice for Enterprise AI Leaders 👤 GUEST Vinh Tran,   / vinhbtran   🔗 CONNECT Website: https://enterprisealignedai.com LinkedIn:   / apsinha   X: https://x.com/aparnabsinha #EnterpriseAI #AgenticAI #RBC #MCP #FinancialServices

In this podcast episode, host Aparna Sinha discusses the current landscape of enterprise AI with guests Victor Sulaiman from Wayfair and Aman Khan from Arize AI. They explore the integration of AI in retail, the importance of evaluating AI systems, and the emerging field of Agentic Commerce. Aman explains Arize’s approach to scalable, AI workflow evaluation and governance, emphasizing open-source tools. The conversation also delves into optimizing logistics and support with AI, the necessity of human oversight on autonomous agents, and techniques for measuring ROI of enterprise AI investments. The episode concludes with insights on the build vs. buy dilemma and strategies for scaling AI from pilot projects to full production.

00:00 Introduction to Enterprise AI and Guests

02:16 AI in Retail: Enhancing Customer and Associate Experience

06:00 Evaluating AI: Arize's Unique Approach

10:36 Open Source: Power of Community Engagement in AI

13:41 Adapting to Generative AI: Evolving Use Cases

15:31 Agentic Commerce: The Future of Retail

19:08 Agentic Logistics: Can Reasoning Optimize Delivery?

22:24 Measuring Reliability and Determinism in AI Systems

25:52 Launching AI Agents: The Importance of Real-World Feedback

28:52 LLM as a Jury with Human Oversight in AI Systems

33:25 Navigating Autonomous Agents in Business

37:43 Understanding ROI in AI Investments

42:58 Build vs. Buy: Strategies for AI Deployment

45:44 Scaling AI from Pilot to Production