Watch this episode in Video Format on Spotify.

Are autonomous agents about to replace your traditional CRM? In this episode, Anaiya Raisinghani (Sr. Tech. Evangelist, AI Startups & Ventures at MongoDB) sits down with Ishan Mukherjee, Co-Founder and CEO of ROX. They dive under the hood of ROX, the world’s largest-scale revenue agent company that is building AI to handle the end-to-end revenue cycle autonomously.Ishan breaks down his founder journey—from Amazon Robotics to Apple's Knowledge Graph—and opens up about the technical realities of building AI agents today.What you’ll learn in this episode:

• The AI Agent Architecture: Discover ROX's "three-layered cake" approach, including their context system, Agent Swarms, and application layer.
• The Database Migration: Why ROX started on DynamoDB for speed but ultimately migrated to MongoDB to handle massive spikes and unstructured data at scale.
• Agents vs. SaaS: The fundamental difference between traditional SaaS platforms (where humans do the work) and autonomous agents (where the AI does the outreach, research, and contracts).
  Advice for AI Founders: Why you need to be highly opinionated about your architecture but extremely iterative with your product experience.
• ⏱️ Chapter Timestamps
  00:00 - Intro & Ishan's Journey
  01:57 - What is ROX?
  04:52 - ROX's Technical Architecture
  06:56 - Migrating to MongoDB
  08:17 - Why Context is King
  11:13 - Internal AI Adoption
  13:05 - The Future of AI and B2B
  14:33 - Lightning Round

Watch this episode as a video on Spotify!
In this episode, Luis Pazmino, Industry Principal for Financial Services at MongoDB, sits down with Saurabh Khandelwal from Capgemini to explore how financial institutions can transform payments data into a strategic revenue engine.
The conversation dives into GenPAL, Capgemini’s solution powered by MongoDB’s modern data platform, and how it enables organizations to move beyond data storage toward real-time intelligence, AI-driven insights, and data monetisation.
In this episode, we discuss:
• Evolving Payments Landscape: Key shifts shaping data strategies and opportunities in payments
• Modern Data Foundations: Building scalable, real-time architectures to support high-volume transactions and compliance needs
• From Data to Value: Turning payments data into actionable insights and new revenue streams
• AI at Scale: Leveraging gen AI and agentic AI for fraud detection, customer intelligence, and operational efficiency
• Pragmatic Modernization: How to adopt AI and modern data platforms without a “big bang” approach
Whether you’re a fintech innovator or a financial institution navigating legacy systems, this episode offers practical insights on unlocking the full value of payments data with AI and modern data platforms.

Timestamps

• 00:09 – Introduction

• 01:05 – Introducing GenPAL

• 02:38 – The tactical shift: From standard BI to Agent AI

• 04:56 – Identifying strains

• 06:59 – Solving payment failures

• 08:48 – Sub-millisecond latency

• 12:48 – The "Experience Gap"

• 15:01 – Strategic advice

• 18:14 – High-level architecture

• 21:35 – Real-world success

• 24:09 – Future outlook

Watch this episode in video format on Spotify!

If you're building Python applications on MongoDB and still writing raw queries by hand, you're leaving a lot of developer productivity on the table. Beanie, the async-first ODM built on Pydantic, was created to fix exactly that — and this episode goes deep on how and why it works.

You'll learn how Beanie maps Python objects to MongoDB documents without sacrificing atomicity or performance, why async-first design matters for modern Python stacks, how schema migrations actually work in a document database, and what the deprecation of Motor means for your existing codebase. The episode also covers Beanie's integration with FastAPI, how it handles indexes and aggregation pipelines under the hood, and what's coming in the next phase of the library.

Ramon, the creator of Beanie and a senior software engineer at Microsoft, built this library five years ago to fill a gap nobody else had addressed. He's joined by Shubham, MongoDB's product manager for Python client libraries, for a live demo and Q&A.

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• [00:00] Introduction & Guest Welcome
• [01:00] What Is Beanie? The ODM Explained
• [04:10] ODM vs ORM — What's the Difference?
• [05:20] Why Ramon Built Beanie (The Origin Story)
• [06:30] Core Design Principles: Atomicity & Async-First
• [08:00] FastAPI + MongoDB: The Rising Python Stack
• [11:00] Bonnet: The Synchronous Beanie Backport
• [12:55] Live Demo: Defining Document Schemas with Pydantic
• [16:00] Nested Documents, Links & Polymorphic Collections
• [18:45] Best Practices for Schema Design
• [20:30] Index Management in Beanie
• [22:40] Complex Queries: Beanie vs Raw PyMongo
• [24:30] Aggregation Pipelines in Beanie
• [28:05] Schema Migrations: Forward, Backward & Freefall
• [31:30] Motor Is Deprecated — What That Means for You
• [34:00] Beanie v2: What Changed and What Didn't
• [36:20] FastAPI, Flask & Django Integration
• [37:45] What's Next for Beanie: Performance & Lambda Optimization
• [39:30] How to Contribute to Beanie
• [41:00] Resources, Community & Audience Q&A