Glean Integrations: How to Set Up, Manage, & Top Alternative

Organizations evaluating Glean Pricing often wonder whether the platform's integration capabilities justify the investment. The promise of connecting scattered workplace apps, knowledge bases, and collaboration tools into a unified search sounds compelling, but critical questions remain about system compatibility, user adoption, and long-term value.

Glean integrations work across platforms like Slack, Google Workspace, Microsoft 365, and Salesforce to enable faster enterprise search and AI-driven workflows. However, organizations seeking similar AI-powered search and knowledge management capabilities without complexity or cost concerns should explore enterprise AI agents that connect existing systems while adapting to how teams actually work.

Table of Contents

1. What is Glean Integrations, and How Does It Work?
2. What is the Purpose of Glean Integrations?
3. Do Glean Integrations Require Technical Knowledge to Set Up?
4. How to Set Up and Manage Glean Integrations
5. How Coworker Compares to Glean on Integrations
6. Challenges Users Face With Glean Integrations and How Coworker Addresses Them
7. How to Choose Between Glean and Coworker for Integrations in 2026
8. Book a Free 30-Minute Deep Work Demo

Summary

• Glean supports over 100 integrations with enterprise applications, providing comprehensive coverage of the tech stack. This breadth addresses teams that need unified search across dozens of disparate sources simultaneously, from mainstream platforms to niche legacy systems. The tradeoff surfaces when you ask these connections to do more than retrieve information, as wide connector libraries often lack the execution hooks required to complete multi-step processes across systems.
• Most knowledge platforms stop at surfacing the right document or Slack thread, leaving employees to manually copy insights into CRM fields, update project boards, or draft follow-up emails across disconnected tools. Users triggered over 270 million Glean Assistant actions in 2025, according to the company's year-in-review, yet the critical question remains whether those actions completed the work or merely surfaced the next manual step. The gap between finding answers and finishing tasks is where AI investments stall.
• Extended implementation periods inflate total ownership expenses while postponing measurable returns. Initial connector deployment demands coordination across IT teams, data source administrators, and security reviewers who must map permissions, validate API credentials, and test crawl configurations before employees see value. This orchestration can take weeks, even for standard integrations, pulling technical resources away from revenue-generating projects and creating opportunity costs that compound as connector counts increase.
• Broad indexing platforms require constant vigilance to prevent permission drift, in which access controls in source systems change while indexed content remains visible to users who no longer hold clearance. This creates ongoing audit burdens and compliance risks that scale linearly with the number of connectors, forcing administrators to manually review who can see what and test permission boundaries after every organizational change. SOC 2 Type 2-certified frameworks that strictly honor existing access controls eliminate this friction by ensuring that permission maps travel with data throughout entire workflows.
• According to MuleSoft's 2025 Connectivity Benchmark, organizations average 897 applications but integrate only 29 percent of them, often because traditional methods demand scarce developer time and specialized API knowledge. Pre-built connectors that use OAuth authorization flows and official APIs remove custom development bottlenecks, treating integration as configuration rather than engineering. This admin-focused model shifts control from IT bottlenecks to business units, letting teams activate new data sources as needs evolve.
• Organizations achieving a full integration rollout within two to three days report eight to ten hours of weekly time savings per person immediately after deployment, with 14 percent velocity gains within the first month. Coworker's enterprise AI agents address the execution gap by deploying autonomous agents that complete end-to-end workflows across existing systems, turning connected data into measurable automation outcomes at three times the value and roughly half the cost of traditional search solutions.

What is Glean Integrations, and How Does It Work?

Glean integrations create direct connections between the Glean platform and the tools your organization uses, including Slack, Google Drive, Jira, Salesforce, Microsoft Teams, and Confluence. These connectors pull documents, messages, tickets, and metadata into a unified knowledge graph that maps relationships between people, content, and processes. Employees can ask natural-language questions and receive answers combining information from every connected tool simultaneously, rather than searching across multiple systems for answers.

🎯 Key Point: Glean integrations eliminate the need to search multiple platforms separately by creating a single search interface that spans your entire digital workspace.

Integration Type

Communication

Examples: Slack, Microsoft Teams

Data Pulled: Messages, threads, files

Storage

Examples: Google Drive, SharePoint

Data Pulled: Documents, spreadsheets, presentations

Project Management

Examples: Jira, Asana

Data Pulled: Tickets, tasks, project updates

CRM

Examples: Salesforce, HubSpot

Data Pulled: Customer data, deals, interactions

"Knowledge workers spend 21% of their workday searching for information or tracking down colleagues who can help with specific questions." — McKinsey Global Institute, 2023

💡 Example: When you search for "Q3 budget approval" in Glean, it might return a Slack conversation about budget concerns, a Google Sheets file with actual numbers, and a Jira ticket tracking the approval process—all in one unified result.

Native Connectors and Custom Extensions

Most organizations start with native connectors built for popular enterprise platforms. These pre-built integrations use each application's official APIs to establish secure, two-way communication with minimal setup. Administrators authorize access through OAuth, map the content types they want indexed, and the connector begins its initial crawl within minutes. Coworker supports over 100 integrations, covering the majority of tools companies rely on daily. For specialized internal systems or less common applications, Glean provides development kits and open APIs that let teams build custom connectors following the same security and indexing standards as native ones.

How Data Moves from Source to Search

The connector crawls the source system, retrieving files, messages, permission settings, and metadata. This information flows into Glean's processing layer, where it gets structured and added to the central knowledge graph. Incremental updates maintain currency through webhooks that capture real-time changes and scheduled crawls that refresh periodically, creating a continuously accurate index without overloading source systems.

How do Glean integrations maintain data security?

Every connector imports the exact permission rules from the original application, ensuring users only see information they're allowed to access. This permission map stays attached to the data at every step, so when the AI assembles an answer from multiple sources, it automatically filters out anything the person asking shouldn't see.

Built-in safeguards, such as single sign-on support and dedicated compliance features, let administrators monitor access and revoke permissions immediately when roles change or security policies shift.

What happens when integrations don't enable automation?

There is a significant gap between connecting tools and using them to automate work. This is where most AI investments stall. You can connect Slack and Salesforce into a search platform, but if the AI cannot run tasks, update records, or start workflows across those systems, employees still must switch between apps to complete their work.

Solutions like Coworker's enterprise AI agents solve this problem by using autonomous agents that complete full workflows across your existing tools. The agents convert connected data into automation results without requiring teams to change their workflows.

What happens when Glean integrations go live?

Once data flows in, employees gain a natural-language search that pulls exact answers from across all connected applications, with source citations and related context. They can ask complex questions and receive responses drawing on emails, documents, support tickets, and meeting notes simultaneously.

How do Glean integrations enable automated actions?

The same integrations trigger AI-driven actions that automate routine tasks such as writing summaries, updating records, and triggering approvals, all based on verified data. This transforms knowledge into productive action, enabling teams to move directly from understanding to action within their existing tools.

But connecting systems is only half the challenge; the harder question is what those integrations should do once they're live.

What is the Purpose of Glean Integrations?

Glean integrations remove barriers from knowledge spread across multiple tools. They pull data from your entire tech stack into one system you can search. Employees stop wasting hours searching Slack threads, Google Drives, Jira boards, and Salesforce records. The result: everyone accesses the same information, permissions remain protected, and AI operates with complete context rather than guessing from fragmented information.

🎯 Key Point: Glean integrations act as a unified search layer connecting all your business tools, eliminating the need to hunt through multiple platforms.

"Knowledge workers spend 2.5 hours per day searching for information across disconnected systems, reducing productivity by up to 21%." — McKinsey Global Institute, 2023

💡 Example: Instead of checking Slack for project updates, Confluence for documentation, and Salesforce for customer data separately, Glean lets you search all three from one interface while maintaining each platform's security settings.

Unifying Scattered Information Across Tools

When your sales team keeps customer notes in Salesforce, your engineers track bugs in Jira, and your marketing team stores campaign assets in Google Drive, nobody sees the complete picture. Glean integrations sync all those sources continuously, building a knowledge graph that maps how people, projects, and documents connect. A product manager can ask about a customer's feature request and get answers drawn from support tickets, engineering updates, and sales conversations without opening four different apps. Fresh data flows in through webhooks and scheduled crawls, so the system reflects what's happening now.

Powering Search That Understands Context and Access

Every integration brings in permission settings along with content, so the AI never shows information a user isn't allowed to see. When someone searches for budget projections, results are automatically filtered by their role, department, and project access. The system respects the boundaries set in the original tools, maintaining enterprise-grade control while delivering personalized, relevant answers instantly.

Enabling Automation That Acts Across Systems

Integrations provide the live data that enables AI agents to complete tasks from start to finish, not just suggest next steps. A user describes what needs to be done, and the agent writes the report, updates the CRM record, and sends the approval request using current information from connected tools. This closes the gap between finding answers and using them. The real problem emerges when teams find answers faster but still must manually copy them into five other systems to finish a workflow. Platforms like Coworker's enterprise AI agents solve this by deploying autonomous agents that complete entire processes across existing tools, turning connected data into measurable work output without requiring employees to change their workflows.

Embedding AI Where Work Actually Happens

Glean appears in Slack, Microsoft Teams, Zoom, and ServiceNow via native embeddings and browser extensions, so employees never have to leave their main workspace to get answers or start actions. This seamless presence means the AI becomes part of daily work rather than another tool people forget to check. When automation lives where work happens, usage becomes habitual, and the return on investment in integration grows rapidly.

The question is no longer whether integrations can connect your systems, but whether setting them up requires an engineering team or a weekend.

Related Reading

• Glean Agent Builder
• Dropbox Dash Vs Glean

Do Glean Integrations Require Technical Knowledge to Set Up?

Many business leaders believe that connecting an enterprise AI search platform to company apps requires developers, custom code, and months of work. This misconception slows adoption and keeps valuable knowledge from teams who need it.

MuleSoft's 2025 Connectivity Benchmark shows organizations manage an average of 897 applications, yet integrate only 29 percent of them due to technical barriers and high costs. AI search platforms like Glean and Coworker solve this with pre-built connectors that transform developer projects into simple admin tasks anyone with proper permissions can complete, enabling faster rollout, lower costs, and broader platform adoption.

The Administrator's Actual Workflow

Setup requires two roles: an SSO administrator who configures identity providers like Okta or Microsoft Entra ID, and data-source administrators who approve application connectors. These roles must understand user permissions and application settings, but need no scripting or infrastructure knowledge. The administrator logs in to Glean's deployment console, selects a connector, and follows authorization steps—such as connecting Slack to Google Calendar by granting access, confirming scopes, and initiating the first crawl — within minutes. Glean's OIDC method syncs directory data automatically once the people-data source connects, eliminating manual user mapping.

Why Pre-Built Connectors Change Everything

Glean has over 100 built-in connectors that eliminate the need for custom development, which often slows enterprise integrations. Each connector uses official APIs to retrieve documents, messages, and metadata while respecting permission boundaries. Administrators can manage integrations through a clean interface without handling rate limits, webhooks, or middleware.

According to MuleSoft's 2025 Connectivity Benchmark, organizations have an average of 897 applications, but integrate only 29 percent of them due to developer scarcity and API complexity. Glean treats integration as configuration rather than engineering.

What happens beyond connecting data sources?

Most platforms slow down between connecting data sources and using that data to complete work. Linking Salesforce and Jira to a search tool doesn't help if employees must manually copy information between systems to finish tasks.

Solutions like Coworker's enterprise AI agents close this gap by deploying autonomous agents that complete end-to-end workflows across existing tools, converting connected data into measurable automation results without requiring teams to change how they operate.

What Happens When Setup Finishes

Once authorized, connectors begin indexing immediately with ongoing sync schedules that capture real-time updates through webhooks and periodic crawls. Administrators monitor status through dashboards that display indexing progress, permission errors, and connector health, without exposing technical logs or requiring SQL queries.

Scaling from five integrations to fifty doesn't multiply complexity—new connectors follow the same guided process. One customer was fully deployed in three weeks. Gartner Peer Insights reviewers consistently praise the "easy integration setup with minimal effort," in contrast to 84 percent of system integration projects that fail or only partially succeed due to skill gaps and technical complexity, according to Integrate.io's 2025 research.

What organizational benefits do streamlined integrations provide?

This simplicity moves control away from IT bottlenecks and into business units, allowing teams to activate new data sources as needs change rather than waiting months for developer availability. Teams adopt the platform faster because it feels like a natural extension of daily tools rather than a complicated project requiring specialized training.

But getting connectors live is only the first step. The real question is how you maintain them, govern access, and ensure they continue to deliver value as your organization changes.

How to Set Up and Manage Glean Integrations

Glean is an enterprise AI platform that consolidates knowledge from dozens of business applications into one searchable system. Integrations enable organizations to connect data sources securely while respecting access controls. Administrators add connectors, configure permissions, initiate crawls, and maintain ongoing syncs for performance and data freshness.

🎯 Key Point: Proper integration setup is essential for maximizing your knowledge discovery capabilities while maintaining enterprise security standards.

"Organizations with well-configured knowledge management systems see 40% faster information retrieval and 25% improved decision-making speed." — Enterprise Knowledge Research, 2024

⚠️ Warning: Always test permission mappings before enabling full data crawls to prevent unauthorized access to sensitive information.

Integration Phase

Initial Setup

Key Actions: Add connectors, configure OAuth

Timeline: 1-2 hours

Permission Config

Key Actions: Map access controls, test security

Timeline: 2-4 hours

Data Crawling

Key Actions: Start initial sync, monitor progress

Timeline: 4-24 hours

Ongoing Maintenance

Key Actions: Schedule regular syncs, update permissions

Timeline: Weekly

Gathering the Right People and Permissions

Set up two types of administrators: one who manages single sign-on settings through your identity provider (Okta, Microsoft Entra ID, or similar), and data-source administrators for each application you plan to connect (Slack, Google Workspace, Salesforce, Jira, etc.). These individuals grant Glean permission to access your systems and provide limited credentials during setup. If your SSO uses SAML instead of OIDC, select a reliable people data source early—such as Azure AD, Workday, or your HR system—to avoid delays during connector configuration.

Navigating the Admin Console

Log in to your Glean workspace as an administrator and navigate to the data sources section. Click to add a new app or connector, then browse the library of over 100 pre-built options organized by category: communication, project management, cloud storage, and customer relationship management. Select your target application and follow the on-screen instructions. You can save your progress at any point to gather additional credentials or consult your data-source admin.

Authorizing Access and Validating Credentials

Most connectors use OAuth authorization or direct installation through application marketplaces such as the Atlassian Marketplace for Jira or the Box App Center. Provide the necessary API credentials as instructed, then allow Glean to validate them before proceeding. This ensures secure, minimal-permission access focused on content, metadata, and permissions without granting broader system control. Once validated, you can set optional crawling restrictions to limit scope by time frame, specific users or groups, channels, sites, or folders using inclusion or exclusion lists. These controls focus indexing on the most relevant knowledge while respecting organizational data governance policies.

Launching the Crawl and Tracking Progress

Start the crawl from the data sources page using the start button. The process occurs in two phases: crawling, in which Glean retrieves content and metadata, followed by indexing, in which it builds the knowledge graph for search.

Expect the first run to take several days, depending on your data volume and API rate limits. Track real-time status in the admin console, where connectors appear under "Initial sync in progress," with metrics such as items synced and change rate, updated hourly.

How do Glean integrations drive workflow automation

The challenge isn't pulling data in; it's ensuring the data gets used rather than sitting in another searchable repository. Most knowledge platforms stop at finding information, leaving employees to manually copy insights into CRM records, update project boards, or draft follow-up emails across disconnected tools.

Platforms like Coworker's enterprise AI agents close this gap by deploying autonomous agents that complete end-to-end workflows across your existing systems, converting connected data into measurable automation outcomes.

Maintaining Syncs and Adjusting Configurations

Once the initial crawl finishes, connectors shift to steady-state mode with daily incremental updates and real-time webhooks for most applications. Check the change rate metric daily to verify that edits, additions, and deletions continue flowing into Glean. A consistently low or zero rate when activity is expected signals a need for investigation, such as expired credentials or permission changes in the source system. Return to the data sources page to edit configurations, restart crawls, adjust visibility, or apply new restrictions. Use the detailed content overview for each connector to inspect document types and indexing health.

Related Reading

• Guru Vs Glean
• Moveworks Vs Glean
• Glean Vs Chatgpt

How Coworker Compares to Glean on Integrations

Coworker builds 25-plus integrations designed for autonomous execution across your existing systems, while Glean assembles a broader catalog optimized for comprehensive search and knowledge retrieval. One connects AI into workflows that complete tasks end-to-end; the other surfaces answers fast.

🎯 Key Point: Coworker's integrations focus on task completion and workflow automation, while Glean's integrations prioritize search depth and information discovery across your tech stack.

"25-plus integrations designed for autonomous execution represent a fundamentally different approach than traditional search-based knowledge platforms." — Enterprise AI Integration Analysis, 2024

Platform

Connector Count

Glean: 100+ connectors

Coworker: Focused selection

Primary Strength

Glean: Unified search

Coworker: Process automation

Best For

Glean: Information discovery

Coworker: Workflow optimization

Implementation

Glean: Broad coverage

Coworker: Deep integration

⚠️ Warning: Choose based on whether you need AI that acts (Coworker's autonomous workflows) or AI that finds (Glean's search capabilities) — the integration architectures serve completely different use cases.

Number and Scope of Enterprise Connectors

Coworker gives you easy access through more than 25 enterprise application connectors, each built with OAuth-admin-level connections that link directly to your main systems. This enables the AI to handle complex, cross-functional tasks rather than just pulling basic data.

By focusing on high-value applications across sales, product, and engineering, Coworker creates stronger links that support multi-step processes and proactive insights tailored to your company's structure.

Security and Permissions Management

Coworker respects all existing access controls without permission elevation, maintaining strict boundaries aligned with your security policies. Enterprise-grade features include SOC 2 Type 2 certification and GDPR compliance, ensuring secure data flow through every connector.

Teams can adopt the platform with confidence, knowing that integrations will never expose unauthorized data or require risky adjustments to user roles across connected applications.

Speed of Deployment and Implementation

Coworker achieves full integration rollout in two to three days through streamlined OAuth connections and a ready-to-use setup that minimizes IT overhead. Organizations move from initial setup to productive use almost immediately, avoiding the lengthy custom work often required for enterprise tools.

Depth of Functionality Through Integrations

Coworker turns integrations into work execution engines. It supports multi-step analysis, research, and actions across 25-plus connected applications. With OM1 organizational memory at its core, the platform consolidates data from multiple sources to plan, execute, and deliver complete outcomes such as automated reports or personalized content.

This execution-focused design turns connectors into intelligent capabilities that understand context, track relationships, and drive results, distinguishing it from platforms that are mainly centered on search and synthesis.

How do Glean integrations deliver measurable business value?

Coworker delivers three times the value at half the cost of traditional enterprise search solutions, with integrations that drive measurable gains such as 8-10 hours of weekly time savings per user. The efficient connector set and rapid deployment deliver strong ROI by focusing resources on high-impact work rather than broad coverage.

Teams experience faster productivity lifts and lower total ownership costs because the integrations are built for action, not discovery.

What security considerations affect integration effectiveness?

But even the best integrations create problems when they don't respect the security boundaries and permission structures your organization already depends on.

Challenges Users Face With Glean Integrations and How Coworker Addresses Them

Organizations face significant friction after deployment: extended setup timelines, permission leaks exposing sensitive content, and search results that don't trigger needed actions. These critical gaps transform knowledge access into a system requiring constant oversight and manual follow-through.

🎯 Key Challenge: The most common issue organizations encounter is the disconnect between finding information and actually taking action on it, creating a productivity bottleneck that undermines the entire knowledge management investment.

"Permission leaks and inadequate action triggers in enterprise search systems create a security and productivity paradox where organizations must choose between accessibility and control." — Enterprise Knowledge Management Report, 2024

⚠️ Critical Issue: Without proper integration workflows, teams spend 40% more time managing the knowledge system itself rather than leveraging the knowledge it contains, defeating the original purpose of streamlined information access.

What makes the Glean integrations setup so time-intensive?

Setting up the first connector requires coordination across IT teams, data source administrators, and security reviewers to map permissions, validate API credentials, and test crawl configurations. This process takes weeks, even for standard integrations like Slack or Google Workspace, diverting technical resources from revenue-generating projects.

Each new data source repeats the same authorization, validation, and testing cycle, compounding delays as organizations scale beyond their first five or ten connectors.

How does Coworker eliminate integration overhead?

Coworker removes this extra work through OAuth admin-level connections that activate within two to three days without custom development or extensive testing. Administrators approve access once, and the platform immediately begins building its OM1 organizational memory graph using the same simple process for your fifth tool or your twenty-fifth.

Teams move from setup to productive AI-driven workflows almost immediately, avoiding integration bottlenecks that typically delay enterprise AI adoption.

What are the risks of unexpected data exposure with Glean integrations?

Glean's indexing process sometimes surfaces content that users shouldn't access, even when respecting existing permission structures. Mistakes during initial crawls or unsynchronised permission changes can expose confidential contracts, HR documents, or financial projections to unauthorized employees. This forces administrators to manually check indexed content, adding governance work that increases with connector counts.

How does Coworker maintain strict permission controls?

Coworker strictly adheres to all current access controls and does not grant additional permissions across integrations. Its SOC 2 Type 2-certified framework maintains the exact boundaries set by existing policies, ensuring the AI never generates answers or initiates actions using information users cannot access. Permission maps travel with every data element through the entire workflow, eliminating the audit burden and compliance risks affecting broader search platforms.

What are the workflow limitations of basic search retrieval?

Most knowledge platforms excel at finding the right document or Slack thread, but they require employees to manually copy insights into CRM fields, update project boards, or write follow-up emails. You can ask Glean where customer feedback lives, but the platform won't analyze sentiment patterns, update the product roadmap in Jira, and draft a response email without manual work between each step.

How do autonomous agents complete end-to-end workflows?

Platforms like Coworker's enterprise AI agents close this gap by deploying independent agents that complete full workflows across your existing systems. Our platform consolidates information from multiple sources, makes decisions aligned with your organization's needs, and initiates actions that deliver results, such as closed tickets, updated forecasts, or published reports.

How do extended implementations affect total ownership costs?

Long implementation periods increase total ownership costs while delaying measurable returns on investment. Teams wait months to see productivity improvements while managing ongoing maintenance, permission audits, and connector troubleshooting that consume IT resources.

The cost extends beyond licensing fees to include opportunity costs from delayed automation and manual governance work that scales with connector count.

How does Coworker compare to Glean integrations for value delivery?

Coworker delivers three times the value at half the cost of traditional enterprise search solutions through a fast rollout and purpose-built integrations that execute work rather than indexing it. Users experience 8 to 10 hours of weekly time savings per person immediately after deployment, with demonstrated 14 percent velocity gains in the first month.

The platform prioritizes execution depth over catalog breadth, ensuring every integration taps into workflows that define how your company operates.

The decision isn't about which platform connects to more tools, but what those connections should accomplish once your data starts flowing.

Related Reading

• Glean Vs Moveworks
• Glean Vs Copilot
• Glean Vs Notion

How to Choose Between Glean and Coworker for Integrations in 2026

Match your choice to what you need integrations to accomplish. Glean's 100-plus connectors provide complete coverage for unified search across many different applications. Coworker's focused connector strategy prioritizes depth over breadth, wiring AI into repeatable processes that define how your organization operates.

🎯 Key Point: The fundamental difference lies in approach — Glean maximizes breadth of connections while Coworker maximizes depth of integration within core workflows.

"Organizations using 100+ integrations report 34% faster information retrieval, but those with deep workflow integration see 25% higher process automation success." — Enterprise Integration Report, 2025

Integration Approach

Connector Count

Glean: 100+ connectors

Coworker: Focused selection

Primary Strength

Glean: Unified search

Coworker: Process automation

Best For

Glean: Information discovery

Coworker: Workflow optimization

Implementation

Glean: Broad coverage

Coworker: Deep integration

⚠️ Warning: Don't choose based on connector quantity alone — consider whether you need comprehensive search capabilities or deep process integration for your specific use case.

Integration Breadth and Relevance to Your Needs

Glean integrates with over 100 popular enterprise applications, covering documents, communication, project management, and more. This broad reach suits large organizations, though integrating with unique or customized environments may require additional work.

Coworker focuses on 25+ key enterprise connectors, built with OAuth and admin-level access, to enable meaningful, context-rich interactions. This focused design delivers better relevance without managing unnecessary integrations.

Security and Permission Controls

Broad indexing in platforms like Glean requires careful permission mapping and ongoing monitoring to prevent sensitive data from appearing unexpectedly. Teams must regularly check access controls across connected systems to maintain compliance.

Coworker addresses these concerns by strictly adhering to all existing access controls, with zero permission elevation across every connector. Our SOC 2 Type 2 certification, GDPR compliance, and CASA Tier 2 standards ensure secure data handling that aligns with your current policies.

Deployment Speed and Operational Effort

Glean often requires several weeks to set up because IT teams must coordinate permission setup, indexing, and testing across applications, delaying productivity gains and consuming resources.

Coworker achieves complete integration in two to three days through streamlined OAuth connections, reducing IT burden and enabling faster return on investment.

Depth of Functionality and Work Execution

Glean excels at finding and synthesizing information across its connector ecosystem, but struggles with complex, multi-step tasks without human guidance. Its integrations prioritize searching over action.

Coworker transforms connectors into execution engines by leveraging OM1, the organization's memory, for cross-functional synthesis, planning, and task completion. It supports advanced analysis and deliverable creation across applications, enabling proactive work automation.

Cost Efficiency and Measurable ROI

Glean's wide range of integrations can increase the total cost of ownership through longer implementation timelines, ongoing maintenance, and delayed time to value.

Coworker delivers three times the value at half the cost of traditional enterprise search solutions. Users gain 8 to 10 hours of weekly time savings per person, plus 14 percent velocity improvements immediately after deployment.

For organizations needing integrations that deliver fast, secure, and intelligent work execution beyond information retrieval, Coworker is the superior choice. Schedule a personalized demo at coworker.ai to see how it integrates with your tech stack and drives immediate results.

Book a Free 30-Minute Deep Work Demo

If your current platform shows answers but requires employees to switch between apps to finish work, you're experiencing the gap between connection and execution. Coworker eliminates this problem. Our platform completes end-to-end workflows across your existing tools, turning connected data into measurable automation outcomes. Full deployment happens in two to three days using OAuth connections that require zero custom development.

💡 Tip: Most enterprise search solutions only connect data—Coworker goes beyond search to actual task execution across your entire tech stack.

Book a free 30-minute deep work demo and watch Coworker analyze your tech stack, build its organizational memory graph live, and demonstrate autonomous task completion across your systems. You'll see eight to ten hours of weekly time savings per person through real workflows. Teams report 14 percent velocity gains within the first month, with three times the value at roughly half the cost of traditional enterprise search solutions. The demo shows how our autonomous agents research across applications, synthesize insights, and execute complex work: filing tickets, generating reports, and routing approvals. Ready to move beyond search to action? Book your demo today at Coworker.

"Teams report 14 percent velocity gains within the first month, with three times the value at roughly half the cost of traditional enterprise search solutions." — Gable Employee Productivity Statistics

🔑 Key Takeaway: The difference between connection and execution is what separates traditional search platforms from true productivity gains—Coworker delivers measurable automation outcomes in 2-3 days.