Anaconda, Inc.

AI agents handle routine tasks easily, but what about the gray areas? Anaconda Senior Developer Relations Engineer Daina Bouquin shows how “human-in-the-loop” agents keep automation efficient while pausing for human judgment when nuance matters. Her LangGraph tutorial walks through building one from scratch — starting simple, then adding Claude to handle more complex, natural-language decisions. Watch to see how humans and AI can make smarter calls together 🧠

Join Anaconda & NVIDIA at Amazon Web Services (AWS) re:Invent today! Stop by NVIDIA’s booth #1022 today at 6:30 PM to hear from Anaconda’s VP of Engineering Alan McCarty about how automation is simplifying CUDA dependency management and making installation smoother. 💡 Don’t miss this opportunity to discover how Anaconda and NVIDIA are improving the developer experience together — and don’t forget to stop by our booth #1327: https://bit.ly/4nIhKOW

Compliance, data sensitivity, and cost challenges are creating friction for enterprises moving AI experiments to deployment. In TechSpective, Anaconda’s VP of AI Product Seth Clark discusses how AI Catalyst helps close that gap—offering transparency, governance, and flexibility through a VPC-first approach and curated open source models. Meet the pragmatic path to making enterprise AI predictable and secure. Read the full story: https://bit.ly/4ioAul1

ICYMI: AI Catalyst launched last week in the Anaconda Platform. The gap we're closing: Teams want to move fast with open source AI, but security reviews, infrastructure setup, and model validation create weeks of delays. What AI Catalyst delivers: → Curated model catalog – Pre-vetted open source models with complete AI Bills of Materials, security assessments, and performance benchmarks → Production-ready optimization – Quantized models that reduce infrastructure costs while maintaining performance → Flexible deployment – Customers on @AWS can run locally for development, deploy to GPU endpoints in their Amazon Virtual Private Cloud for production → Enterprise governance – Custom policies, audit trails, and compliance documentation built in Organizations are using AI Catalyst to move from prototype to production in days instead of months – without compromising on security. See how it works: https://bit.ly/4rb5tok

The November edition of Numerically Speaking just dropped! 🗞️ This month, our newsletter covers: 🚀 The AI Catalyst launch ⚖️ How to differentiate good AI models from bad 💪 New support tiers 🗓️ Upcoming webinars and events, including Amazon Web Services (AWS) re:Invent Dec. 1-5 Check out the full newsletter here: https://bit.ly/4ihXFx6

With Thanksgiving around the corner, our engineering team cooked up something special — a new Thanksgiving channel! 🦃 With just a single command, you can “prepare” a full Thanksgiving dinner (or install dishes à la carte like turkey, mashed potatoes, gravy, and more). Check it out on anaconda.org, and from all of us at Anaconda, Happy Thanksgiving! 🍂🥧

Amazon Web Services (AWS) re:Invent is right around the corner — and we’d love to meet you there! Whether you’re exploring how to scale AI securely or accelerate data science innovation, the Anaconda team will be on-site and ready to connect. Stop by booth #1327 from Dec 1-5 to learn how Anaconda can power your AI strategy in 2026 and beyond. Secure your meeting slot with us today 👉 https://bit.ly/4oP3UuX

“In AI, standardization and innovation aren’t opposites — they’re partners. Standards create the stable foundation that lets innovation flourish at speed.” AI isn’t stuck because of a lack of talent or investment, but because organizations are building on quicksand. For Fast Company, Anaconda Co-Founder and Chief AI & Innovation Officer Peter Wang explains why only 22% of companies have moved beyond AI pilots — and how open-source standards are the foundation for true scalability and ROI. Read Peter’s full perspective: https://bit.ly/3LZOjKi

We had a great time at the #DataAIWorldTour stops in Toronto and NYC! 💚 It was inspiring to connect with data leaders and showcase how Anaconda’s native integration with Databricks accelerates secure access to trusted Python packages within the Data Intelligence Platform. Thanks to everyone who joined us to explore the future of data, AI, and open source!

Most enterprises hit a wall after early AI wins — not because of tech limits, but because their systems aren’t built for AI’s speed. As Anaconda VP Seth Clark notes, some use cases demand different approaches, especially with regulated or complex data. With AI Catalyst, Anaconda empowers organizations to build the right foundation: secure, transparent, and governed environments where innovation can scale safely. Speed comes from structure, not shortcuts. Read the full story in Forbes: https://bit.ly/3LRjI1C