Glean vs. ChatGPT Enterprise

Two incredibly popular AI search platforms for teams are Glean and ChatGPT Enterprise. These products are often compared due to overlapping data integrations and "chat with your data with AI" offerings, but they are vastly different tools with different focuses. Glean is primarily a platform that queries data from the entire company’s knowledge and surfaces relevant information with AI; it’s designed for teams with a sprawling SaaS tooling stack that’s difficult to manage and context switch between. ChatGPT Enterprise, meanwhile, is a “beefed-up” AI chat interface with unlimited access to OpenAI’s latest model, massive context windows, and enterprise data integrations. It features an unopinionated design for teams looking to answer open-ended questions and solve diverse problems from their data.

The origins of Glean and ChatGPT Enterprise reveal their distinct priorities.

Glean started as a search platform with enterprise data integrations. With Glean, any employee could search their company’s data sources, including Google Drive, Salesforce, Box, HR Tooling, and other SaaS tools. As AI emerged, Glean evolved from simply querying to actioning on queried data. Today, with Glean, you can search, synthesize, and action upon documents with managed AI agents (however, with only limited agentic functionality). For example, an employee could use modern-day Glean to surface where a specific customer’s custom pricing plan was documented and delegate an AI agent to send that customer an email concerning it. In short, Glean’s story is a Spotlight-like search bar for a SaaS stack that grew into an AI-branded knowledge management tool.

As the name implies, ChatGPT Enterprise’s foundations are quite straightforward: ChatGPT Enterprise is a powerful tool and the most advanced version of OpenAI’s successful AI chat product. On the tier chart, ChatGPT Enterprise surpasses other ChatGPT team tiers, such as ChatGPT Pro and ChatGPT Team, in available features. ChatGPT Enterprise is designed for larger companies that want to integrate AI chat into their various day-to-day operations, such as conducting sales research, processing invoice data, writing Python scripts, or answering questions about the company’s payroll. ChatGPT Enterprise features native RAG (retrieval-augmented generation), persistent memory, the largest possible context windows for OpenAI models, and OpenAI’s latest models. ChatGPT Enterprise also includes integration features that make it partially competitive with Glean, but it is not designed to be a knowledge management tool.

Despite their varying focuses, comparing Glean and ChatGPT Enterprise is a worthy conversation. While some enterprises might opt to purchase both for their distinct strengths, other businesses would likely pair ChatGPT Team or ChatGPT Pro with Glean. Today, we’ll compare the two products. Additionally, we’ll discuss why neither may be the right fit for an AI-heavy enterprise, and when a solution like Credal.ai may be a better option.

A Quick Comparison: What Types of Organizations Should Prioritize What Product?

Glean and ChatGPT Enterprise are designed for different types of organizations. These organizations don’t have exclusively different problems—just like Glean and ChatGPT don’t have exclusively different functionality—but they do have distinct core problems.

Who Is Glean Designed For?

Glean is designed for organizations that have a disjointed or sprawling SaaS tooling stack. When organizations have a large SaaS stack with data spread across it, day-to-day operations suffer. For example, these organizations have burdened employees by forcing constant context switching between products, causing delays and fatigue. Employees might also struggle to find data, knowing it exists but not knowing where it’s stored. This is particularly tricky if interlinked data (such as customer notes) are spread across multiple platforms.

Glean addresses this problem with a two-pronged approach. First, it has native connectors that integrate with copious SaaS tools. Second, it exposes AI features that can summarize and answer questions for employees or take limited actions via agents.

However, Glean’s agentic features are limited. The platform excels at synthesis tasks—for example, an employee could create an agent that consolidates recent customer data for an account manager and sends an email. However, Glean only supports single agents and can pose a problem for customers with data stored in disparate locations. This is a problem that more advanced AI tools, like Credal, are designed to address: with Credal, multiple agents can work together to solve a problem. For instance, a sales-focused agent might identify potential customer feedback in Salesforce and relay it to an engineering-focused agent, which ensures issues are up to date in Confluence.

Who Is ChatGPT Enterprise Designed For?

Holistically, ChatGPT Enterprise is very unopinionated. ChatGPT Enterprise’s design enables users to utilize it for anything, including tasks that don’t involve data integrations. For example, an engineer might use ChatGPT Enterprise to write a one-off Python script used by a bash process, all without having to connect ChatGPT Enterprise to any tooling. Meanwhile, a sales rep might use ChatGPT to write a bespoke email to a customer they’re struggling to close.

ChatGPT Enterprise—similar to Glean—also features some native integrations to third-party drives (Box, Dropbox, Google Drive, and OneDrive), but it otherwise requires custom MCP connectors to other software. Accordingly, it has limited integration features.

However, these features aren’t unique to ChatGPT Enterprise. They are also available on ChatGPT’s Business and Pro tiers. Instead, the reason to purchase ChatGPT Enterprise is to either unlock ChatGPT’s pre-built agents (like Codex, for complex programming tasks), gain unlimited access to OpenAI’s latest model (currently, GPT-4o), or access bigger context windows. Accordingly, the reason that an organization would want ChatGPT Enterprise is to access state-of-the-art AI models at scale. This makes sense for organizations that constantly analyze complex questions (e.g., synthesizing a history of network products to aid in an investment decision) or solve complex problems (e.g., understanding the biggest objection that sales reps get). While Glean is focused on companies trying to solve “death by a thousand cuts” inefficiencies, ChatGPT Enterprise is for organizations working to solve problems that might have been impractical without AI.

Another reason organizations might choose ChatGPT Enterprise is due to a casual reliance on ChatGPT by employees, alongside a fear of data privacy issues. ChatGPT Enterprise is committed to zero data retention—a requirement for GDPR data custody rules, SOC 2 data exposure tenets, and other customer data contracts. In some cases, organizations may choose ChatGPT Enterprise due to a shadow IT problem, where employees have used ChatGPT on their own volition without IT oversight, creating a legal risk because of the potential for sensitive data to be leaked to OpenAI’s servers.

Costs: How Do Glean and ChatGPT Enterprise Compare?

Glean and ChatGPT Enterprise are both enterprise tools and, therefore, are subject to custom pricing based on a customer’s specific needs. However, we can still make some comparisons based on online user reviews.

Glean has a wide base of users. Because some customers may be at a startup or growth stage, their contracts may be as low as $28.8K per year. However, most enterprises should expect to pay high six-figure to low seven-figure contracts. We’ve interacted with plenty of companies that have gone through Glean’s quoting process, some receiving quotes of nearly $5M. It’s significantly more expensive than products like Credal despite being significantly limited in AI features (discussed later below).

ChatGPT Enterprise has a much smaller user base and therefore has fewer publicly available data points. However, it does feature a minimum contract value of $108K per year, with an expectation of 150 minimum seats retailing at $60 per seat per year.

With all enterprise deals, there is wiggle room. For example, it’s possible that an enterprise may manage to secure a discount below the $108K per year benchmark for ChatGPT Enterprise by compromising on certain features.

Knowledge Graph vs. Language Model

Glean and ChatGPT Enterprise feature different base models. Glean is a knowledge management system: a platform designed to capture, organize, analyze, and share an organization’s knowledge, which is spread across various tools. ChatGPT Enterprise is primarily a chat interface for interacting with an in-house, foundational large-language model (LLM). Let’s discuss the differences.

Glean Features a Multilayered Knowledge Management System With Hundreds of Connectors

With over 100 pre-built zero-code connectors, Glean makes it easy to connect to popular tools, including Google Workspace, Microsoft 365, Slack, Salesforce, Jira, Confluence, etc. For enterprises needing to integrate other data, custom data connectors are also possible.

Glean also features real-time permissions, where access is reflected in Glean when changes are made in the underlying SaaS applications. For example, if an employee loses access to a Google Doc at 2:00 pm, they’ll also lose access in Glean at the same time. This is possible because Glean does per-query access checks to ensure access still exists.

Glean features an enterprise knowledge graph that maps three critical relationships. It delineates who knows what (expertise mapping), who works with whom (collaboration patterns), and what content relates to what (topic clustering).

ChatGPT Enterprise Is Built on Its Own Foundational Model

ChatGPT Enterprise is primarily a chat application built atop OpenAI’s flagship languages models like GPT-4o and o3. Because OpenAI, the flagship leader of the modern wave of AI models, is the developer of both the UI and the underlying model, it will always feature the most cutting-edge language model (which may, occasionally, not yet be available to external vendors like Glean).

As an AI chat application, ChatGPT Enterprise is un-opinionated in design and can be used for various tasks across different departments. Operation team members might use the AI chat to create, summarize, or alter documents used in day-to-day work; engineers could utilize the chat (and the built-in Codex AI agent) to write code snippets and debug problems; and revenue teams could use it to conduct deep research on sales trends.

This is possible because ChatGPT Enterprise features native connectors to a company’s underlying data sources, such as Google Drive, Salesforce, Linear, or other internal documents or SaaS apps. However, these features are not nearly as robust as Glean’s connectors, which have permission mirroring features and a significantly larger library of connectors. Accordingly, ChatGPT Enterprise is rarely considered a true knowledge management system. Instead, it is an AI chat application with some select data integrations.

Still, ChatGPT Enterprise does not skimp on its ability to process massive context windows of data. The product is capable of supporting up to 128,000 tokens (roughly 300 pages of text) and can also upload up to 20 files per query. Custom GPTs are also possible, where a model is refined to a specific task or knowledge base, making it more accurate at answering questions or doing tasks. As an AI chat application, ChatGPT Enterprise is incredibly robust.

Security Comparison: How Do Glean and ChatGPT Enterprise Handle Security?

How Does Glean Handle Security?

Glean’s permissions system is built on an inheritance model, where Glean mirrors the access permissions of the underlying sources, like Google Drive or Salesforce. This prevents LLM queries from sidestepping stringent authorization models and revealing unauthorized information.

Glean also ensures that an LLM does not retain any customer data due to its zero data retention guarantee. This matters to organizations that need to maintain compliance standards, such as HIPAA and GDPR, where third-party data custody poses risks.

Glean, as a platform, is also compliant with those same standards and offers single-tenant deployment options. Additionally, Glean includes features like Glean Protect, which scans for overshared sensitive data and provides audit trails for all user activities, ensuring decent security and accountability.

How Does ChatGPT Enterprise Handle Security?

ChatGPT Enterprise takes a similar approach, inheriting permissions from some underlying SaaS applications, such as Google Drive and Microsoft Outlook. For other integrations, teams would have to build custom connectors to get more granular permissions; however, this defeats the benefit of ChatGPT Enterprise’s native connector feature.

To partially compensate for this, ChatGPT Enterprise uses a secure sandbox model. This means that no customer data touches OpenAI’s training pipeline; instead, it runs in an isolated environment. Any deleted information in a customer account will be purged from OpenAI’s system within 30 days. Otherwise, ChatGPT stores data with AES-256 encryption at rest and uses TLS 1.2+ in transit.

However, because ChatGPT Enterprise is primarily a chat application, there is a risk of human error where an employee pastes customer PII or other sensitive data as a prompt. In this scenario, despite the data being held in secure custody by OpenAI, it has left the controlled environment. Accordingly, the security of ChatGPT Enterprise is mostly a function of trusting employees to use judgment about what data to share and trusting OpenAI’s isolation promises.

What Are Some of the Disadvantages of Both ChatGPT Enterprise and Glean?

Glean and ChatGPT Enterprise have some significant shortcomings. Because of their varying focuses, we’ll discuss them separately.

What Are Glean’s Shortcomings?

As Glean was not originally an AI company and instead pivoted into the space, its general UI is far more mature than its AI features. For example, while Glean has native agents, they aren’t too fleshed out. They feature limited pre-built actions, only support single agents, and limit memory to a single agent.

During one conversation, a customer voiced their negative experience with Glean, citing the limited nature of its agent features.

“I have started playing around with the Glean agent stuff. I think it’s weak. Frankly, the connectivity that they have from an ecosystem perspective is really soft, [it] basically can do like four or five things. They’re like send a Slack post, send an email … read a Confluence article. It’s super rudimentary. They push off a lot of the development to their customers.”

Compared to a solution like Credal, Glean has very young AI features. Credal, an AI-first company, has prioritized the agentic aspects of its product. Credal has more abundant pre-built actions for agents to leverage. Even more notable, Credal enables companies to build agentic workflows that involve multiple agents. This matters to enterprises that want to see a massive portion of their day-to-day work automated with AI. Multi-agent systems are capable of accomplishing more than single-agent systems; each agent specializes in a specific job role and is more likely to succeed without supervision, since the context window isn’t spread thin. With Credal, companies can launch agents that focus on specific subproblems (e.g., maintaining Confluence records) that can communicate with each other. This makes a significant difference for enterprises that have abundant data sources and subproblems, allowing agents to focus on specific actions and work together toward a common goal.

What Are ChatGPT Enterprise’s Shortcomings?

Because ChatGPT Enterprise is focused on integrations and Glean-like features, its shortcomings are best framed in comparison with platforms like Glean and Credal.

ChatGPT Enterprise’s integrations are significantly more limited than Glean’s. It’s primarily a chat application and is not designed for SaaS search. It also does not support truly customizable agents, limiting organizations from deploying bespoke agents designed around day-to-day tasks that employees otherwise need to handle. Instead, ChatGPT Enterprise ships a limited set of pre-built agents, like the dedicated code assistant called Codex. It also offers customGPTs that are configurable, but can only take limited actions, such as web search.

Additionally, ChatGPT Enterprise is constrained to only OpenAI’s models. This can be limiting for businesses that prefer alternative models, such as Anthropic’s Claude, which is fantastic at handling data stored in graphs. In other words, an organization’s data format and analysis needs may be better suited for models beyond OpenAI’s product line.

ChatGPT Enterprise is ideal for organizations that already depend on ChatGPT Business and require more native integrations. For organizations trying to solve more open-ended problems (like IT manager issues or Salesforce maintenance tasks), a solution like Credal or Glean is more apt.

How to Choose: Decide What Problem You’re Trying to Solve

If you are choosing between Glean and ChatGPT Enterprise, there are a few questions to consider that can help you decide. A quick comparison between the tools:

Glean:

• 100+ pre-built integrations
• Fully-customizable agents
• Access to various models, including models from Anthropic and Google

ChatGPT

• Few bespoke connections to file storage solutions like Google Drive and Box
• Limited pre-built agents and custom GPTs
• Unlimited access to OpenAI’s latest model

Additionally, if considering Credal:

Credal

• Pre-built integrations to major tools (Box, Confluence, Salesforce, Google Drive, Dropbox, OneDrive etc)
• Fully-customizable agents with access to bespoke pre-built actions
• Support to multi-agent workflows for truly agentic autonomy
• Access to various models, including models from Anthropic and Google

When You should Choose Glean

If you are dealing with any of the following subproblems, Glean might be the right solution:

• If employees are spending at least two hours per day searching across systems, Glean helps save money on lost productivity.
• If new hires take significant time to learn about a company’s processes and data, Glean helps cut down these onboarding lag costs.
• If sales and marketing (as well as engineering and customer success) are having trouble communicating with each other, Glean can provide an easy way to share information without forcing teams to adopt the same underlying tools.
• If a company is in a highly regulated industry where sharing sensitive data with external programs is a concern, Glean provides a more bulletproof permissions system.

Glean is a single pane where employees can ask questions, create workflows, and operate without context switching.

When You Should Choose ChatGPT Enterprise

You should choose ChatGPT Enterprise when the following subproblems resonate:

• Teams often need help drafting, writing, coding, and analyzing.
• Developers need help creating mundane coding tasks, such as unit test generation, that waste precious engineering hours.
• Documents are constantly being scrutinized for analysis or summarization.

ChatGPT Enterprise gives organizations unlimited access to OpenAI’s most advanced models, making it fantastic for tackling complex problems that less mature models may struggle with.

When You Should Choose Credal

For organizations that care about using agents to their maximum capacity to replace simple and complex day-to-day employee operations, solving similar issues as Glean and beyond, then Credal might be the right choice, as it provides a more robust AI approach. Credal is a native AI company that prioritized AI features from the start. Credal’s support for multi-agents and copious integration-specific actions makes it ideal for organizations looking to heavily invest in AI and automate workflows without constant human-in-the-loop or manual orchestration.

Credal stands out for its flexible agent-based architecture, enabling teams to rapidly spin up specialized AI agents tailored to their specific business logic. These agents might deal with tasks like call scoring, categorization, or customer prioritization. Agents can also be orchestrated using a centralized agent (i.e., an “orchestrator”), which coordinates domain-specific agents and handles complex workflows, including call coaching or sales conversation prep.

Credal, like Glean, also makes integration seamless, with robust APIs that support both real-time and batch processing. Credal, like ChatGPT Enterprise, also supports custom assistants that are tailored to a specific knowledge base or task. All of this is possible with a more friendly pricing model: Companies can opt into a 30-day evaluation window with no upfront billing, allowing them to validate the platform’s value before committing. Pricing is based on seat usage, data volume, and AI consumption, making it well-suited for both high-touch agents and orchestrator-driven automations.

A Closing Thought: Don’t Underestimate Your Agentic Foundation

While ChatGPT Enterprise and Glean are leading AI products, choosing either will result in larger contracts with limited agentic features. For enterprises that are serious about embracing AI, picking a product that focuses on giving agents the foundation to work together and integrate with SaaS applications is critical.

With Credal, it is easy to orchestrate domain-specific agents tailored to specific tasks, especially for organizations with multiple departments, SaaS tools, and day-to-day tasks. In a nutshell, Credal is the only product focused on enterprise problems at scale. Learn more about Credal by booking a demo with our team today.