Is building the backend for your AI application slowing you down? In this episode of the MongoDB Podcast, host Jesse Hall sits down with Srikar and Jimmy, the creators of Daemo AI, a revolutionary tool designed to eliminate the tedious "plumbing" of backend development.

Discover how Daemo AI is building upon deprecated MongoDB features like Realm App Services, creating a more powerful and flexible solution for developers. We dive deep into their tech stack, including Next.js, Deno, and Express , and explore why they chose MongoDB for its speed and flexibility in AI applications.

Plus, you'll see a live demo of Daemo's new SDK and CLI , learn how it can generate data migrations and dummy data on the fly , and get a real answer to the big question: Is AI going to take your job?

In This Episode, You Will Learn: What Daemo AI is and how it accelerates development. * How to build AI agents and integrate them with frameworks like LangChain. Why MongoDB is the ideal database for rapid-growth startups and AI. The future of developer jobs in the age of AI.

🔴 LIVE: How MongoDB Atlas Is Redefining Elasticity for Cost-Optimized PerformanceWelcome to this special episode where we explore the cutting-edge elasticity features in MongoDB Atlas—designed to help organizations optimize costs without sacrificing performance.Whether you're a software engineer, DevOps lead, or IT decision-maker, this conversation will show you how to scale smarter, faster, and more reliably.

Is waiting months for employee feedback a thing of the past? Dive into the future of work with Shane McAllister and L10 founders, Zyrian Chung and Keith Chan. Discover how their AI-powered platform collects daily insights to transform workplace culture, empower managers, and address issues like silent quitting before they escalate. Learn how real-time feedback and AI can create more engaged and productive teams, and get a peek into the tech (including MongoDB) that makes it possible. Stop guessing, start understanding your team today!

TAGs:

#EmployeeEngagement, #AIinHR, #WorkplaceCulture, #FutureofWork, #EmployeeFeedback, #RealTimeInsights, #TeamManagement, #Leadership, #HRTechnology, #MongoDB, #L10, #ZyrianChung, #KeithChan, #SilentQuitting, #EmployeeMorale, #TeamProductivity, #PerformanceManagement, #AITools, #EmployeeSurveys, #PeopleAnalytics

✨ Heads up! This episode features a demonstration of the SnapLogic UI and its AI Agent Creator towards the end. For the full visual experience, check out the video version on the Spotify app! ✨

(Episode Summary)Tired of tangled data spread across multiple clouds, on-premise systems, and the edge? In this episode, MongoDB's Shane McAllister sits down with Peter Ngai, Principal Architect at SnapLogic, to explore the future of data integration and management in today's complex tech landscape.

Dive into the challenges and solutions surrounding modern data architecture, including:

• Navigating the complexities of multi-cloud and hybrid cloud environments.
• The secrets to building flexible, resilient data ecosystems that avoid vendor lock-in.
• Strategies for seamless data integration and connecting disparate applications using low-code/no-code platforms like SnapLogic.
• Meeting critical data compliance, security, and sovereignty demands (think GDPR, HIPAA, etc.).
• How AI is revolutionizing data automation and providing faster access to insights (featuring SnapLogic's Agent Creator).
• The powerful synergy between SnapLogic and MongoDB, leveraging MongoDB both internally and for customer integrations.
• Real-world applications, from IoT data processing to simplifying enterprise workflows.

Whether you're an IT leader, data engineer, business analyst, or simply curious about cloud strategy, iPaaS solutions, AI in business, or simplifying your data stack, Peter offers invaluable insights into making data connectivity a driver, not a barrier, for innovation.

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Keywords: Data Integration, Multi-Cloud, Hybrid Cloud, Edge Computing, SnapLogic, MongoDB, AI, Artificial Intelligence, Data Automation, iPaaS, Low-Code, No-Code, Data Architecture, Data Management, Cloud Data, Enterprise Data, API Integration, Data Compliance, Data Sovereignty, Data Security, Business Automation, ETL, ELT, Tech Stack Simplification, Peter Ngai, Shane McAllister.

**(Note: Spotify listeners can also watch the screen sharing video accompanying the audio. Other podcast platforms offer the audio-only version.)**

In this episode of MongoDB Podcast Live, host Shane McAllister is joined by Sachin Hejip from Dataworkz. Sachin will showcase “Dataworkz Agent Builder” which is built with MongoDB Atlas Vector Search, and demonstrate how it can use Natural Language to create Agents and in turn, automate and simplify the creation of Agentic RAG applications. Sachin will demo the MongoDB Leafy Portal Chatbot Agent, which combines operational data with unstructured data for personalised customer experience and support, built using Dataworkz and MongoDB.

Struggling with millions of unstructured documents, legacy records, or scattered data formats? Discover how AI, Large Language Models (LLMs), and MongoDB are revolutionizing data management in this episode of the MongoDB Podcast.Join host Shane McAllister and the team as they delve into tackling complex data challenges using cutting-edge technology. Learn how MongoDB Atlas Vector Search enables powerful semantic search and Retrieval Augmented Generation (RAG) applications, transforming chaotic information into valuable insights. Explore integrations with popular frameworks like Langchain and Llama Index.Find out how to efficiently process and make sense of your unstructured data, potentially saving significant costs and unlocking new possibilities.Ready to dive deeper?

#MongoDB #AI #LLM #LargeLanguageModels #VectorSearch #AtlasVectorSearch #UnstructuredData #Podcast #DataManagement #Dataworkz #Observability #Developer #BigData #RAG

**(Note: Spotify listeners can also watch the screen sharing video accompanying the audio. Other podcast platforms offer the audio-only version.)**

Struggling with millions of unstructured documents, legacy records, or scattered data formats? Discover how AI, Large Language Models (LLMs), and MongoDB are revolutionizing data management in this episode of the MongoDB Podcast.Join host Shane McAllister and the team as they delve into tackling complex data challenges using cutting-edge technology. Learn how MongoDB Atlas Vector Search enables powerful semantic search and Retrieval Augmented Generation (RAG) applications, transforming chaotic information into valuable insights. Explore integrations with popular frameworks like Langchain and Llama Index.Find out how to efficiently process and make sense of your unstructured data, potentially saving significant costs and unlocking new possibilities.Ready to dive deeper?#MongoDB #AI #LLM #LargeLanguageModels #VectorSearch #AtlasVectorSearch #UnstructuredData #Podcast #DataManagement #RAG #SemanticSearch #Langchain #LlamaIndex #Developer #BigData

MongoDB staff developer advocate Jesse Hall teams up with Storecraft creator Tomer Shalev to dissect how this open-source commerce platform leverages MongoDB for scalable, AI-driven workflows. Watch them live-code integrations (vector search, dynamic pricing, email automation) and explore real-world use cases—from custom discount logic to OpenAI-powered product recommendations.

Perfect for developers building modular, future-proof commerce solutions.

Ever wondered how companies like Amazon or Pinterest deliver lightning-fast image search? Dive into this episode of MongoDB Podcast Live with Shane McAllister and Nenad, a MongoDB Champion, as they unravel the magic of semantic image search powered by MongoDB Atlas Vector Search!

🔍 What You’ll Learn:

• Why semantic search is a game-changer for AI-driven applications (spoiler: it’s all about meaning, not just keywords!).

• How to transform images into vectors (embeddings) and store them alongside your data—no clunky ETL pipelines required!

• A live demo showcasing real-time image search on a 40,000+ product dataset (spoiler #2: it’s blazing fast and shockingly simple to build!).

• Pro tips on choosing embedding models, optimizing indexes, and avoiding common pitfalls.

• Why MongoDB’s unified data model crushes traditional databases for AI/ML workloads.

  
  

  👥 For Developers & Data Engineers:
  Whether you’re a JavaScript, AI enthusiast, or just tired of JOINs, this episode is your roadmap to building smarter, faster apps. Plus, learn why companies like Toyota and Verizon trust MongoDB for mission-critical AI workloads.