Arvind Jain on Building Glean and the Future of Enterprise AI

Arvind Jain on Building Glean and the Future of Enterprise AI

Author: Lukas Biewald August 5, 2025 Duration: 43:41

In this episode of Gradient Dissent, Lukas Biewald sits down with Arvind Jain, CEO and founder of Glean. They discuss Glean's evolution from solving enterprise search to building agentic AI tools that understand internal knowledge and workflows. Arvind shares how his early use of transformer models in 2019 laid the foundation for Glean’s success, well before the term "generative AI" was mainstream.

They explore the technical and organizational challenges behind enterprise LLMs—including security, hallucination suppression—and when it makes sense to fine-tune models. Arvind also reflects on his previous startup Rubrik and explains how Glean’s AI platform aims to reshape how teams operate, from personalized agents to ever-fresh internal documentation.

Follow Arvind Jain: https://x.com/jainarvind

Follow Weights & Biases: https://x.com/weights_biases

Timestamps:

[00:01:00] What Glean is and how it works

[00:02:39] Starting Glean before the LLM boom

[00:04:10] Using transformers early in enterprise search

[00:06:48] Semantic search vs. generative answers

[00:08:13] When to fine-tune vs. use out-of-box models

[00:12:38] The value of small, purpose-trained models

[00:13:04] Enterprise security and embedding risks

[00:16:31] Lessons from Rubrik and starting Glean

[00:19:31] The contrarian bet on enterprise search

[00:22:57] Culture and lessons learned from Google

[00:25:13] Everyone will have their own AI-powered "team"

[00:28:43] Using AI to keep documentation evergreen

[00:31:22] AI-generated churn and risk analysis

[00:33:55] Measuring model improvement with golden sets

[00:36:05] Suppressing hallucinations with citations

[00:39:22] Agents that can ping humans for help

[00:40:41] AI as a force multiplier, not a replacement

[00:42:26] The enduring value of hard work


Lukas Biewald hosts Gradient Dissent: Conversations on AI, a series that moves beyond theoretical discussions to examine how artificial intelligence is actually built and deployed. Each episode features a direct, unscripted talk with a leading practitioner-you’ll hear from engineers and researchers at places like NVIDIA, Meta, Google, Lyft, and OpenAI. The focus is on the tangible challenges and breakthroughs they encounter, from initial research to the complex reality of putting models into production. This isn't about abstract futures; it's a grounded look at the decisions shaping the field right now. Biewald, bringing his perspective from Weights & Biases, steers conversations toward the practical trade-offs and collaborative efforts that define modern AI work. For anyone in technology or business who wants to understand the mechanics behind the headlines, this podcast offers a rare, candid window into the process. You’ll come away with a clearer sense of how ideas become functional systems and what it really takes to operate at the cutting edge.
Author: Language: English Episodes: 100

Gradient Dissent: Conversations on AI
Podcast Episodes
Mircea Neagovici — Robotic Process Automation (RPA) and ML [not-audio_url] [/not-audio_url]

Duration: 46:22
Mircea Neagovici is VP, AI and Research at UiPath, where his team works on task mining and other ways of combining robotic process automation (RPA) with machine learning for their B2B products.Mircea and Lukas talk about…
Peter & Boris — Fine-tuning OpenAI's GPT-3 [not-audio_url] [/not-audio_url]

Duration: 43:39
Peter Welinder is VP of Product & Partnerships at OpenAI, where he runs product and commercialization efforts of GPT-3, Codex, GitHub Copilot, and more. Boris Dayma is Machine Learning Engineer at Weights & Biases, and w…
Ion Stoica — Spark, Ray, and Enterprise Open Source [not-audio_url] [/not-audio_url]

Duration: 53:42
Ion Stoica is co-creator of the distributed computing frameworks Spark and Ray, and co-founder and Executive Chairman of Databricks and Anyscale. He is also a Professor of computer science at UC Berkeley and Principal In…
Chris Padwick — Smart Machines for More Sustainable Farming [not-audio_url] [/not-audio_url]

Duration: 1:00:59
Chris Padwick is Director of Computer Vision Machine Learning at Blue River Technology, a subsidiary of John Deere. Their core product, See & Spray, is a weeding robot that identifies crops and weeds in order to spray on…
Kathryn Hume — Financial Models, ML, and 17th-Century Philosophy [not-audio_url] [/not-audio_url]

Duration: 52:08
Kathryn Hume is Vice President Digital Investments Technology at the Royal Bank of Canada (RBC). At the time of recording, she was Interim Head of Borealis AI, RBC's research institute for machine learning.Kathryn and Lu…
Sean & Greg — Biology and ML for Drug Discovery [not-audio_url] [/not-audio_url]

Duration: 55:25
Sean McClain is the founder and CEO, and Gregory Hannum is the VP of AI Research at Absci, a biotech company that's using deep learning to expedite drug discovery and development.Lukas, Sean, and Greg talk about why Absc…
Chris, Shawn, and Lukas — The Weights & Biases Journey [not-audio_url] [/not-audio_url]

Duration: 49:13
You might know him as the host of Gradient Dissent, but Lukas is also the CEO of Weights & Biases, a developer-first ML tools platform!In this special episode, the three W&B co-founders — Chris (CVP), Shawn (CTO), and Lu…
Pete Warden — Practical Applications of TinyML [not-audio_url] [/not-audio_url]

Duration: 53:28
Pete is the Technical Lead of the TensorFlow Micro team, which works on deep learning for mobile and embedded devices.Lukas and Pete talk about hacking a Raspberry Pi to run AlexNet, the power and size constraints of emb…