Glean¶

What it is¶

Glean is an AI-powered enterprise search and knowledge management platform that connects all of a company's disparate data sources—from Slack and Google Drive to Jira and GitHub—into a single, unified search and chat experience.

What problem it solves¶

It eliminates "information silos" by providing a centralized gateway to institutional knowledge. Glean understands the context of a company's people, projects, and permissions, allowing employees to find exactly what they need without having to know which specific app the information lives in.

Where it fits in the stack¶

Enterprise Search / Knowledge Management Layer. It serves as the primary "connective tissue" for information discovery across the organization.

Key Features¶

Unified Search: Search across 100+ popular SaaS applications with a single query.
Enterprise Knowledge Graph: Maps the relationships between people, documents, and activities to deliver context-aware results.
Glean Assistant: A generative AI coworker (Claude 4.7 and GPT-5.5 optimized) that answers questions based on internal documentation.
Glean Waldo: A specialized agentic search model that delivers frontier intelligence with ~50% lower latency and ~25% fewer tokens.
Glean Canvas: An interactive workspace for synthesizing information and generating presentations or interactive pages.
MCP Gateway: Provides secure, governed access to enterprise context for external agents using the Model Context Protocol.
Health Agents: Specialized agents for proactive infrastructure monitoring and assessing health across cloud deployments.
Permissions-Aware: Strictly respects existing source-system permissions; users only see information they are already authorized to access.

Typical use cases¶

Employee Onboarding: Helping new hires find internal policies, project history, and key contacts.
Customer Support: Enabling support agents to find technical answers across internal wikis and past tickets.
Engineering Productivity: Finding relevant code documentation, Jira issues, and architectural decisions across repositories.

Getting started¶

Glean is an enterprise-grade SaaS platform. It typically requires administrative integration with the company's SSO and primary SaaS providers.

Minimal Concepts¶

Connectors: The integrations used to pull data from external apps (e.g., Slack Connector).
Verification: A feature where subject matter experts can "verify" specific answers to ensure accuracy.
Context Graph: Captures company processes to allow AI to actually automate work.

CLI examples¶

[!NOTE] Glean is an enterprise search platform and does not provide an official public CLI for end-users as of June 2026. Administrative tasks are managed via the web console.

API examples¶

Glean provides a REST API for searching programmatically. Below is a Python example using the requests library.

import requests

API_KEY = "your_glean_api_key"
GLEAN_DOMAIN = "your-company.glean.com"

def search_glean(query):
    # API v1 Endpoint (2026 pattern)
    api_url = f"https://{GLEAN_DOMAIN}/api/v1/search"
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "query": query,
        "pageSize": 5,
        "model": "gpt-5.5" # Optional: Specify model preference if permitted
    }
    response = requests.post(api_url, json=payload, headers=headers)
    return response.json()

Strengths¶

Relevance: Superior search ranking compared to basic app-specific search.
Security: Robust enterprise-grade security (Glean Protect), including SOC2 compliance and deep permission integration.
Actionable AI: Moves beyond just finding files to performing tasks via agent orchestration and the Agentic Engine.

Limitations¶

Cost: High-tier enterprise pricing; may not be cost-effective for very small teams.
Implementation Time: Full indexing and fine-tuning the knowledge graph can take time for large organizations.

When to use it¶

When your organization has information spread across 10+ different SaaS platforms (Slack, Jira, Drive, GitHub, etc.).
When employees spend significant time searching for "who knows what" or "where is that doc."
When you need a permissions-aware AI assistant (GPT-5.5 or Claude 4.7 based) that only reveals information the user is authorized to see.

When not to use it¶

For very small teams (e.g., <20 people) where information is easily managed in one or two tools.
If you only need to search public web data (use Perplexity instead).
If your primary knowledge base is exclusively in Notion or Confluence.

Notion AI (Internal knowledge search within Notion)
Perplexity (Alternative for external/web search)
Hebbia (Analytical synthesis for finance/legal)
Fyxer AI (Executive assistant and inbox management)
Ramp (Financial automation and spend management)
tldv (Meeting transcription and knowledge extraction)
Langfuse (Observability for custom LLM integrations)
AgentOps (Monitoring for autonomous agents)
n8n (Workflow automation)
Model Context Protocol (MCP) (Standard for tool-agent connectivity)

Sources / References¶

Contribution Metadata¶

Last reviewed: 2026-06-07
Confidence: high