Introducing the Glean agent toolkit: a Python library for building context-aware AI agents that tap into your company's unique data. Define tools once and reuse them across frameworks like OpenAI, LangChain, CrewAI, and Google ADK. Steve Calvert walks us through using the toolkit to debug a CI/CD pipeline by aggregating signals from GitHub logs, Jira tickets, Confluence docs, Slack threads, and more. Thanks to MCP, we deployed the agent directly into the Cursor IDE, so engineers can troubleshoot right where they code. 💥
Glean
Software Development
Palo Alto, CA 138,324 followers
The Work AI platform connected to all your company data. Find, create, and automate anything.
About us
Work AI for all. The Work AI platform connected to all your data. Find, create, and automate anything.
- Website
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https://glean-it.com/glean
External link for Glean
- Industry
- Software Development
- Company size
- 501-1,000 employees
- Headquarters
- Palo Alto, CA
- Type
- Privately Held
- Founded
- 2019
Products
Glean
Enterprise Search Software
The Work AI platform connected to all your company data. Find, create, and automate anything.
Locations
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Primary
Palo Alto, CA 94306, US
Employees at Glean
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Ravi Mhatre
Founder, Managing Director, Lightspeed Venture Partners
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Brett Roeder
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Benton Williams
Corporate Development and Strategic Partnerships at Glean
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Michael Moore
VP, Head of Legal, Company Secretary at Glean Technologies Inc - IAM300, AIGP, FIP, CIPP-US, CIPP-E, CIPP-C, CIPM, CIPT
Updates
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We’re exploring what it really takes to make AI work at work. If that’s a conversation you want to hear at SXSW 2026, vote to bring it to the stage. 🗳️ 🔷 Enterprise AI at scale with Arvind Jain, CEO at Glean, David Beitel, CTO at Zillow, and T. Alexander Puutio at Forbes: https://lnkd.in/gVTRhhmr 🔷 Getting the most out of your enterprise data with AI with Arvind Jain, CEO at Glean, and Baris Gultekin, VP of AI at Snowflake: https://lnkd.in/gAqTHEa2 🔷 AI Alignment and distributed work with Arvind Jain, CEO at Glean, and Dan Spaulding, CPO at Zillow: https://lnkd.in/gtPTUUus Your voice is important! 🗣️ Community voting makes up 30% of SXSW final selection. Voting closes August 24, so don’t miss your chance! Thanks for your help in bringing our ideas to SXSW 🙌
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Hot take: Building AI agents that demo well ≠ building agents your team actually uses That's where evaluations come in – evaluations help you refine agents based on real user data. We cover how you can evaluate individual agents to make them better, and how we approach evaluations at scale to keep agents reliable across the enterprise in our latest blog 👉 https://lnkd.in/gt9uSiM6
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What's it like interning at Glean? ✨ For National Intern Day, we asked our interns to share their biggest takeaways from their time at Glean – advice, lessons, and favorite moments. Swipe through to see what Christina Wu, Sriram Varun Vobilisetty, Sydney Schirrmeister, Jennifer Ying, and Abhishek Khandelwal had to say 👉
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Glean reposted this
🐌 Playing around with Glean agents and the no-code workflow builder is pretty seamless. In this example, I created a simple OKR coach where I just updated the system prompt. The workflow builder feels a bit like Zapier in that I define 1) the steps in the agent (e.g. nodes in the graph) 2) system prompts for each step/node and 3) which internal data sources I want the agent to read before performing the inference. I think these simple chatbots and workflow builders are good enough for 80% of the use cases out there if your company is just looking for better answers to questions and summarizing disparate data sources on internal data. The time to value is super quick because Glean already has been approved to read a bunch of internal data sources like Gong, Coda, Slack, Confluence, and more.
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Writing launch notes doesn’t have to be a chore 🙂↔️🙅 The Launch Documentation Agent handles it for you – pulling completed Jira tickets, summarizing features, and drafting a polished PR so you can save hours and keep shipping. It’s fully customizable: choose your LLM, set your templates and fields, and define the output format to match your team’s exact workflow. Kat Crichton from our customer experience team shows how it works 👇
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Glean reposted this
I built our first AI-powered Content Design assistant at Intercom! 🤖 Creating UI content is a daily task for most of our Product Designers. But the tools that help them do it – our style guides, our messaging, our research – are scattered across docs and decks, making it hard to guarantee consistent content across teams. So I trained an AI agent to fill this gap. It’s called VERBI and it uses Glean to pull from a curated collection of internal resources. Most importantly, it can read our design system, meaning it knows how to write for every component in our product. Toggles, toasts, labels, tooltips? VERBI knows every content rule and is ready to help. This new agent can: - Write: create content from scratch in our tone of voice - Edit: instantly improve clarity, consistency and style - Review: offer content feedback and critiques - Name: suggest new names for product features - Strategise: help to rationalise content choices - Guide: deliver content guidelines on demand - Jam: find alternative words, phrases, headlines - Inform: pull in our latest research and data It’s not a replacement for good thinking or good writing. It’s how we scale both of these across a growing team, setting new benchmarks for quality and speed. It’s also not perfect (yet). I’ll probably be tweaking the system prompt for weeks to come. But it’s live, it’s working, and it’s helping us get better one iteration at a time 📈 #ContentDesign #AI #ProductDesign #UXWriting #DesignTools #Innovation
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How much happier would your customers be if they got the right answer in 1 hour instead of 6? Shishir Verma made that happen by equipping his support team with fast, accurate answers using Glean. Now, they resolve issues faster and feel like experts with every response. See how they did it 👇
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Support teams are stretched thin. Call center turnover is up to 45% annually, and over half of consumers will switch brands after just one bad experience. It’s clear that burnout is real — and unsustainable. In our upcoming webinar, April Ho-Nishimura from Infineon Technologies, and our own Greg Bakken will explore how AI is transforming customer service operations. What you’ll learn: ⏱️ How to cut resolution times and reduce escalations ⚡ Empower agents to get faster answers with fewer handoffs 🚀 Scale support using AI that fits your existing tech stack 👉 Sign up now to learn how your peers are leveraging AI to supercharge support: https://lnkd.in/dfE55vWS
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