Unstructured Data Governance

7/13/2026

Introduces new Glean connectors for sales tools, specifically meeting transcript connectors (Zoom, Granola, Fathom, Otter), sales intelligence connectors (Salesloft Conversation Intelligence), and sales enablement connectors (Crayon, Showpad). These connectors integrate customer conversation history, forecasting, pipeline, account signals, approved content, and competitive context into Glean, making them searchable and usable within Glean's Assistant, answers, and workflows. This expands the existing unstructured data governance framework by incorporating these new data sources relevant to sales execution.

6/8/2026

This post introduces Glean meeting notes, a new capability that integrates meeting transcription, note-taking, and AI-generated summaries directly into the Glean platform. It emphasizes making meeting content searchable and referenceable alongside other enterprise data, thereby enriching the unstructured data governance framework. The technical implementation involves capturing audio (transcribed text only), processing it for summaries, and indexing these notes as first-class artifacts within Glean's existing search and context engine. It also details how the system integrates with existing meeting platforms (Google Meet, Microsoft Teams, Zoom, Slack huddles) without acting as a bot, and clarifies data handling for privacy and security (no raw audio storage, adherence to retention policies).

6/8/2026

Introduces AI-powered meeting notes that transcribe meetings, identify action items, and integrate them into the enterprise context, making meeting knowledge searchable and reusable alongside other enterprise data. Also introduces the ability to collaborate on and analyze data directly within Glean using spreadsheets in canvas, allowing users to perform dynamic data analysis with full access to enterprise context without manual data exports or reliance on data analysts.

6/8/2026

Introduces the ability to generate refreshable, interactive artifacts and spreadsheets within Glean's canvas. These artifacts are grounded in enterprise context and personal graphs, enabling users to build dynamic content like ROI calculators, task lists, customer datasheets, and perform data analysis for product adoption, campaign performance, deal reviews, and customer feedback prioritization. This extends the existing unstructured data governance framework by providing new output formats and interactive capabilities for leveraging governed data.

5/3/2026

This post elaborates on the enterprise AI copilot landscape, detailing the technical requirements for a robust solution. It emphasizes the importance of secure access to diverse enterprise data sources, the application of retrieval-augmented generation (RAG) for grounded answers, real-time inheritance of granular permissions, and the necessity of workflow execution capabilities beyond simple chat interactions. The post also outlines an evaluation framework for AI copilots, focusing on data and grounding, security and permissions, actions and workflows, breadth and scalability, and governance and improvement, which directly relates to the technical implementation and operationalization of such systems.

3/31/2026

This post introduces a new capability focused on unstructured data governance. It details a multi-step process for managing unstructured data, including inventorying assets, establishing taxonomies, automating enrichment and indexing with ML techniques (OCR, embeddings) and hybrid search strategies (inverted indexes, vector stores), codifying policies, implementing stewardship and access controls (RBAC/ABAC), and continuous monitoring. The system aims to make unstructured data searchable, contextual, and trustworthy, supporting AI initiatives.