Coworker vs Glean (2026)

About thirty five connectors are named on the platform and agents pages, out of a stated 50+ OAuth connectors listed in a directory at /connectors.

On the platform page they cover CRM (Salesforce, HubSpot), communications and meetings (Slack, Gmail, Zoom, Google Meet, Google Calendar, Microsoft 365), docs and project work (Google Drive, Google Sheets, Notion, Confluence, Jira, Linear, Asana, Figma), engineering (GitHub, Datadog, PagerDuty, VS Code), data (Snowflake, BigQuery, Amplitude), payments (Stripe), the browser (Chrome) and the systems of record for IT service management, HR and finance (ServiceNow, Workday, ADP, SAP, NetSuite).

The agents page adds Gong for sales, Zendesk and Intercom for support, and Microsoft Teams. Every connector reads and writes, so agents pull data and push updates across CRM, comms, support, docs, code and data, updating CRM records, creating tickets, sending follow-ups and drafting reports, and the published run drafts into Gmail, updates Salesforce and posts to Slack.

Agents inherit the permissions already in place, with no new logins and no new SSO maps, so there is no parallel access model to drift. Chrome and VS Code appear in the OAuth connector list as ingestion paths feeding the graph, not as interface control.

Sourcecoworker.ai/platform integrations section and /agents connector listread 2026-09-12

Agents act in outside systems as well as reading from them, through Connectors & Actions, and Glean enforces source-system permissions on every read and write. The 275+ app connectors each have their own page under glean.com/connectors, spanning documents, tickets, chat and code, and the same connectors feed Glean's index. The Indexing SDK lets teams add custom, permission-aware data alongside Glean's existing connectors, and custom actions are available through the APIs.

Sourceglean.com/ai-agents connector index and glean.com/platform/apiread 2026-09-12

The Agent Builder is the authoring surface, where customers create custom agents in minutes by defining what they do, which tools they use and when they run, with no code required, and set triggers, approval gates and notification preferences through a visual interface. Agent sequences span several steps and systems, and they branch.

In the account agent's published run, it drafted outreach for six accounts through Salesforce and Gmail, escalated one strategic account to an AE through Slack, and posted an expansion summary to Slack, so one of the six accounts went to a person based on the state of the case. The Incident Orchestrator routes incidents, enforces escalation timers and tracks resolution, which means making a routing decision, holding a timer across a gap the agent does not control, and following an incident through to resolution.

State persists across runs, agents run 24/7 in the background without anyone stepping in, and Coworker describes orchestrating several agents from a single control plane. A workflow involves the agent, the approver at a gate, the AE an account escalates to, and the connected systems each step reads and writes. Agents carry work through to the end, updating the CRM, creating tickets, sending follow-ups and drafting reports. Coworker does not describe retry, failure handling or what an agent does when a step fails.

Sourcecoworker.ai/agents capabilities, agent examples and FAQ, with /platformread 2026-09-12

Glean's agentic engine lets agents reason through tasks, plan next steps and take action using enterprise context, in multi step and multi agent runs. Agent orchestration, which Glean describes as automating work across systems, routes tasks between agents and connects to external systems so automations run when and where they are needed, inside a governed runtime. An agent builder supports reasoning-based agents and complex workflows, and a deployment surface lets teams roll out, share and certify agents.

Sourceglean.com/ai-agentsread 2026-09-12

Agents start on a schedule, on real time events or manually. Scheduled triggers run agents for daily briefings, weekly reports and hourly monitoring. Custom triggers start agents on new Slack messages and Jira updates, CRM changes and calendar events, four event sources in four systems. Agents work where the team already works, running in Slack, joining meetings and updating boards instead of living in another tab.

The Coworker Native Apps (Work, Chat, Build, Meetings, Agents, Artifacts) are Coworker's own surfaces, and Coworker MCP puts the same agents inside Claude, Cursor, ChatGPT and Windsurf. Email appears in the agent examples, which draft outreach through Gmail. Agents run 24/7 in the background without anyone stepping in and send a notice when done, and none of this is held to one tier. Coworker does not say whether a customer can define a compound or conditional trigger beyond the four named event types.

Sourcecoworker.ai/agents capabilities and FAQread 2026-09-12

Key events start agent runs, and agent orchestration exists to trigger agents from key events, route tasks between agents and connect to external systems so automations run when and where they are needed. People reach Glean from its own web app, from 275+ connected applications, and through Glean MCP inside Claude Code, Codex, Gemini, Cursor and Copilot. Proactive AI, which anticipates next steps like meeting prep or first drafts before anyone asks, is marked coming soon, while the event triggers carry no such marker.

Sourceglean.com/ai-agents, against glean.com/platform/enterprise-contextread 2026-09-12

OM2 reads every connected tool continuously, with no uploads or re-syncing, learns backwards over historical data at setup and keeps evolving as it sees more each day, whereas most assistants, Coworker says, fetch document chunks at query time and forget afterward. Knowledge is stored as connected facts about people, projects, customers and decisions, with customers, projects and deals, as well as people, as first class nodes rather than raw text. Recall is synthesized ahead of time rather than found at query time, relevancy-ranked by proximity, recency and centrality, with sub-second graph traversal.

Retrieval is scoped by permission-aware traversal built into the graph, with access policies on every fact and connection. Every answer traces back to its source, and agents get permissioned context across Slack, CRM, docs, Jira and 50+ apps. The corpus covers messages, tickets, deals, docs, sheets, calendars, CRM, emails, meetings, transcripts, code, wikis, boards, PRs, recordings and contacts. Coworker's comparative figures (84% preference, 20% faster, 66% cheaper) are its own unaudited benchmarks.

Sourcecoworker.ai/platform OM2 section with /blog/introducing-om2 and /agentsread 2026-09-12

A persistent index and graph sit over the customer's corpus. Glean has 275+ connectors across apps, documents, tickets, chat and code and 1000+ signals in the Enterprise Graph mapping people, content and relationships, on the principle of indexing data once and using it everywhere. The Enterprise Graph captures not just content but the relationships between people, data and activity across the organization, and it persists between runs and stays queryable. Retrieval respects permissions, enforcing source system permissions on every read, so the graph carries access state as well as content.

Sourceglean.com/platform/enterprise-contextread 2026-09-12

OM2, which replaced OM1 as the headline layer, is built by reading the customer's connected tools continuously, with no uploads or re-syncing, and learns backwards over historical data at setup. Agents use the graph to track progress, learn from corrections and continuously improve, and memory compounds with every interaction, so learning from corrections is written by the agent as well as absorbed into the product.

Scoping rests on isolated single tenant infrastructure, access policies on every fact and connection, and permission aware traversal, with permissions per user in the native apps. Coworker states no retention period, expiry, purge or deletion path for the memory. The only published retention figure is 90 days for recorded meetings on the Enterprise tier.

Coworker MCP is one connection, read-only by default, so the graph can be read and inspected there and in the native apps, with permissions on each fact, but nothing lets a customer or an outside caller edit, correct or delete a fact in it.

Sourcecoworker.ai/platform, /agents and /blog/introducing-om2read 2026-09-12

Enterprise Memory, which learns continuously, is one of four Enterprise Context components, and what Glean publishes under that heading is the Enterprise Graph, a knowledge structure. A per user layer sits beside it. Personal Graph learns each person's goals, commitments, priorities, writing style and ways of working from their edits, replies, messages and other work signals, and Glean uses it to tailor answers and write in that person's voice.

Glean does not describe a lifetime, expiry or purge path for either, or a way for a person or an admin to read or edit what was learned. Skill reflection, launched in October 2026, updates a skill from how it is used only after a person confirms the change. Proactive AI, which builds a live view of teams and projects and anticipates next steps, is marked coming soon.

Sourceglean.com/platform/enterprise-context, glean.com/enterprise-context/personal-graph and glean.com/blog/skill-reflection-2026read 2026-10-24

Customers can add approval steps to any agent workflow, where a reviewer can review, edit or reject the agent's proposed action before it executes, so the hold sits on the agent's own action and the reviewer can amend it as well as approve or deny it. Both modes are supported, with agents running fully autonomously for routine tasks or with approval gates on any workflow so a person reviews and approves actions before they execute. Background runs work the same way, notifying the team when done so they can review the output and approve actions before they go live.

Permissions, approvals, credit limits and escalation logic are named together as controls, and a credit limit is a hard spending stop on an autonomous agent that does not depend on anyone noticing. Escalation logic appears in the products too, with the Incident Orchestrator enforcing escalation timers and the account agent escalating one strategic account to an AE. Agents inherit the permissions already in place, with no new logins and no new SSO maps, so an agent cannot go beyond the authority of the person it acts for.

Sourcecoworker.ai/agents capabilities and FAQ, with /platformread 2026-09-12

Glean Protect checks agent actions before they run. Action Alignment checks agent actions against the user's intent and authority before execution, and write actions are checked before they execute to keep agents within their intended scope, so Glean, not the downstream system, stops a write that fails the check.

Topic Restrictions check requests against acceptable use and industry-specific policies before the model responds. Agent governance policies and different policies for select agents or users are marked coming soon, and the control on agentic browser use is in beta, while the checks above carry no such marker. Glean does not describe an approval queue that a person reviews item by item.

Sourceglean.com/platform/securityread 2026-09-12

Coworker holds SOC 2 Type II, GDPR compliance and CASA Tier 2, shown as three badges on the platform page that each link to a Secureframe trust portal at village-labs.secureframetrust.com. Identity and access controls include SSO, RBAC, and encryption at rest and in transit, and SSO is part of the Enterprise entitlements.

Permissions reach down to each fact, since Coworker is permission-aware by construction, with access policies on every fact and connection, so everyone sees only what they are allowed to see through traversal of the graph that respects permissions. Because the graph pulls Slack, CRM, email and HR systems together, that authorization on each fact governs what every user can reach. Agents inherit the permissions already in place, with no new logins and no new SSO maps, so there is no privilege elevation and no parallel access model to drift.

Isolated single tenant infrastructure and complete audit trails across the platform add to this, along with a commitment never to train models on customer data and published legal agreements, namely a privacy policy, terms and a Master Services Agreement.

The agents page says agents tap into 100k+ deployed agents' learnings, which reads as learning across customers and sits against the statement that customer data is never used to train models, and Coworker does not say whether the shared learnings are behavioral patterns rather than customer content.

Sourcecoworker.ai/platform enterprise-grade section and FAQ, with /pricingread 2026-09-12

Glean holds SOC 2 Type II, ISO 27001, ISO 42001, HIPAA, TX-RAMP Level 2 and GDPR, with a trust center at trust.glean.com.

Identity & Access verifies who is making a request through the customer's SSO provider before AI runs, covering both user and agent identity, and Data Permissions enforces source-system permissions on every read and write, so an agent does not automatically access everything the user can. An always on audit trail records what happened.

Four items are marked coming soon or beta, agent governance policies, per agent and per user policies, Enterprise Graph enriched threat detection, and security scans of memory.

Sourceglean.com/platform/securityread 2026-09-12

Every action is logged and every decision auditable, with guardrails the customer sets and audit trails the customer owns, and the agents FAQ says every action in autonomous runs is logged for full auditability. Complete audit trails across the platform are listed among the enterprise controls beside permissions and identity, and logging every action records what the agent did, not only what it produced.

Answers are attributed separately in OM2, where every answer traces back to its source, so a conclusion can be walked back to the fact and the connected tool it came from. Coworker gives no detail on the audit trail itself, with no stated retention period and no word on whether it can be exported or filtered, whether it captures reasoning as well as actions, or whether it exists below the Enterprise tier.

Sourcecoworker.ai/agents and /platform enterprise-grade section, with /blog/introducing-om2read 2026-09-12

Every control point is logged to an end-to-end audit trail as it happens, with events available to stream into a SIEM.

Six control points are logged, identity and access, data permissions, sensitive content, topic restrictions, runtime threat protection and action alignment, so the trail shows who asked, under what identity, what was permitted, what was screened and what the agent was allowed to do.

It is Glean's own record of what its agents did, separate from the logs the customer's Slack, Jira or Salesforce already keep. Agent observability, a separate surface, reports adoption, error rates, upvotes, downvotes and ROI as operational metrics.

Sourceglean.com/platform/security and glean.com/ai-agentsread 2026-09-12

Isolated single tenant infrastructure is offered in four forms, cloud, private cloud, on premises or air gapped, and on premises and air gapped installs sit in the customer's own environment, so the customer decides where data rests. Coworker is SOC 2 Type II, GDPR and CASA Tier 2 verified, with SSO, RBAC, encryption, audit trails and air-gapped deployment support.

Single tenancy is the baseline, and the OM2 memory runs on isolated single-tenant infrastructure in Coworker's cloud or via VPC. VPC peering and bring your own model on the customer's own infrastructure are further options, so a customer who cannot send data to a shared service has three published routes.

The homepage says routing is all hosted in the US and the OM2 announcement leads with cloud and VPC, while the platform page states the full range. There is no named region list for the hosted option, no residency selection for cloud customers, and no page on what an air gapped deployment costs, excludes or requires.

Routing across twelve providers is hard to square with an air gapped install, and bringing your own model on the customer's infrastructure may resolve that, though Coworker does not say so.

Sourcecoworker.ai/platform OM2 security line and FAQread 2026-09-12

Customers can host Glean in their own cloud tenant, and Glean says SafetyCulture chose it in part for its security-first approach to enterprise data and the ability to host Glean within its own cloud tenant. TX-RAMP Level 2 points to a deployment posture US state governments can procure, and a trust center sits at trust.glean.com. Glean publishes no deployment guide for the cloud tenant option, and no single tenant, customer managed, on premises or air gapped deployment.

Sourceglean.com/platform/securityread 2026-09-12

A catalog of agents is published, each described and tagged by role. Expansion Pipeline, for Account Management, finds accounts hitting usage ceilings and generates upgrade outreach, and Revenue Recovery, for Finance, processes payment failures with segment-specific recovery playbooks. Pipeline Cleanup, for Sales Ops, enforces CRM discipline on stale deals, past due dates and missing data.

Incident Orchestrator, for Engineering, routes incidents, enforces escalation timers and tracks resolution, and Data Analyst, for BI and Analytics, queries data, builds reports and surfaces insights automatically. Three more are named in the deployment section, Post-Meeting Actions for Sales, Contract Review for Legal and Bug Triage for Engineering, and the agent picker offers Account, MCP, Engineering, BI, Legal, Meetings, Finance and Sales as classes. Each agent works on its own and serves a different function on different objects for different teams in the same company.

Once a tool is connected, the product learns in minutes and suggests agents suited to the user's role, so the catalog proposes agents from what a customer connects. OM2 carries shared skills and artifact templates that travel across models and do work when selected, and use case pages by function, one each for Sales, Engineering, Customer Success, Support, Product, Marketing, People, Operations and Industries, make the catalog browsable. The named agents each appear as a card with no page of their own, and no count of the full library is given.

Sourcecoworker.ai/agents agent set and role suggestions, with /platform OM2 skillsread 2026-09-12

The Agent Library lets teams discover trusted, reusable agents, so every team can build, deploy and discover new agents on one platform, and a deployment surface lets them roll out, share and certify agents. The library holds independent agents built for different jobs that customers can adopt from the catalog. Glean does not publish a count of prebuilt agents.

Sourceglean.com/ai-agents and its Agent Library sectionread 2026-09-12

Coworker routes each task to the optimal model across closed, open-source and self-hosted providers, balancing cost, latency and accuracy, with every task routed to the cheapest model that meets the quality bar. It names 12+ model providers, among them OpenAI, Anthropic and Google, plus open source Llama, Mistral and MiniMax. With BYOM, a customer can bring its own models and run them on its own infrastructure.

As better models ship, teams get them automatically with no migration and no vendor lock-in, and OM2's memory and skills travel with the customer whatever model it chooses. Coworker MCP, on the same page, lets the customer's own assistant reach Coworker's memory. Coworker does not say whether an administrator can pin a specific model per agent or can only rely on automatic routing.

Sourcecoworker.ai/platform routing section and FAQread 2026-09-12

Glean Intelligence optimizes AI for price-performance, matching each task to the right model across 40+ open and frontier models, with Auto routing. Customers and admins get a Model Hub for access to the latest models, flexible model choice as part of the Open Platform, an AI Gateway that governs every AI interaction and which models may be used, and Usage Controls for AI usage and spend. Multi cloud support and the Bedrock, Vertex and Azure OpenAI hosting relationships are infrastructure, not separate model providers. Glean does not show how a model is selected for each step.

Sourceglean.com/platformread 2026-09-12

Coworker MCP, a product with its own page, puts org memory, 50+ tools and dedicated agents inside any MCP client through one connection that is read-only by default and uses the same SSO and permissions, with Claude, Cursor, ChatGPT and Windsurf named as clients. OM2 also connects through MCP or an API, so Coworker's memory can be used outside Coworker in any MCP-compatible client.

Through it the customer's assistant calls Coworker, and because dedicated agents sit inside any MCP client, an outside assistant can invoke a Coworker agent that updates CRM records, creates tickets and sends follow ups. The agent picker lists MCP as one of its surfaces alongside Account, Engineering, BI, Legal, Meetings, Finance and Sales.

The connection reads by default, and the wording implies write access can be configured, but Coworker does not say how or what a write scope covers. Permissions and SSO come from the same identity, so the surface does not widen a customer's exposure. The memory is sold as one memory for every surface, with skills traveling too. Coworker publishes no tool list, endpoint reference, SDK or OpenAPI document, and the API named in the OM2 post has no published reference.

Sourcecoworker.ai/platform portability section and FAQ, with /blog/introducing-om2read 2026-09-12

Outside callers reach Glean through its Search API, Chat API and Agents API, an Indexing SDK that lets teams add custom, permission-aware data alongside Glean's existing connectors, and a Web SDK to embed Glean UI and context-aware chat or agent experiences.

The Agents API follows the LangChain Agent Protocol, with client libraries in TypeScript, Go, Java and Python, and an ungated developer portal sits at developers.glean.com.

Glean MCP feeds governed enterprise context into Claude Code, Codex, Gemini, Cursor and Copilot, letting those tools drive Glean, while the 275+ connectors run the other way, letting Glean drive other systems.

Sourceglean.com/platform/api and glean.com/blog/go-agents-launchread 2026-09-12

There is no sandbox, dry run, simulation or staging workspace, no holdout, A/B comparison or versioning and rollback of an agent configuration, and no evaluator, scored result or regression surface. In the deployment lifecycle the agents FAQ walks through, a customer builds an agent in the Agent Builder and it runs, with no test step. The platform is organized around five layers, OM2, Routing, Portability, Integrations and Enterprise Grade, and none of them covers evaluation.

The Optimize and scale step says memory compounds with every interaction, which describes the memory layer growing. Agents are said to get smarter with use, observe the team's patterns and suggest new automations, and get smarter every week as they learn how the team works. Approval gates let a person review, edit or reject each action before it executes.

Sourcecoworker.ai/agents and /platformread 2026-09-12

Builders can test agents before they publish them, and Glean does not describe how a test is scored. The agent builder versions every change automatically, keeps drafts and offers rollback, and lets builders test outputs and adjust instructions.

Headless agent building, generally available since October 2026, lets developers define an agent in files from Claude Code, Codex or Cursor, run it with representative inputs, "run evaluations" and refine it before publishing, with changes reviewed and rolled back through Git. Debug and trace views became generally available in May 2026. Glean does not describe what an evaluation measures, a pass criterion, scored test cases, a quality gate or a controlled experiment. Agent observability reports adoption, error rates, upvotes, downvotes and ROI as live operational metrics.

Sourceglean.com/ai-agents/agent-builder, glean.com/blog/glean-headless-agent-builder and glean.com/press/glean-introduces-the-enterprise-agent-development-lifecycle-codifying-how-enterprises-build-govern-and-measure-ai-agentsread 2026-10-24

Data comes in through OAuth connectors feeding the graph, actions go out as connector writes that update CRM, create tickets and send follow-ups, and the outside surface is an MCP server. Coworker presents OM2 as replacing work at the interface, using sub-second graph traversal in place of brute force tool calling. Nothing operates a screen, and all fifty connectors are OAuth APIs.

Chrome and VS Code appear among the OAuth connectors on the platform page, in the list of connectors feeding the graph alongside Slack, Snowflake and Workday, and what is read from them includes code, PRs and recordings, all ingested into the knowledge graph. Coworker has no hosted or local browser, desktop session or remote computer control, and no RPA, recorder or extension that acts on a page.

Sourcecoworker.ai/platform integrations list and /agents context listread 2026-09-12

Agents reach other systems through 275+ API connectors and custom actions, and Glean offers no hosted browser, desktop session or remote or local computer control. Glean Protect lists keeping agentic browser use in check as a guardrail in beta. Nothing shows Glean's own agent driving a browser.

Sourceglean.com/platform/security and glean.com/platformread 2026-09-12