We’re excited to announce that the SplxAI Platform now natively supports connecting AI assistants and agents built with Glean!
This new integration significantly enhances SplxAI’s compatibility with major enterprise AI use cases, enabling organizations that rely on Glean to continuously red team and evaluate their AI assistants and agents for security, safety, and precision.
With our simple setup process, users can now connect their Glean-powered AI assistants to the SplxAI Platform in less than five minutes – without writing a single line of code – and immediately start running comprehensive tests and evals to ensure their AI systems remain secure and aligned with business objectives at all times.
Let’s explore how Glean is transforming the enterprise AI landscape, and how SplxAI helps practitioners strengthen the security and reliability of these AI applications.
We’re excited to announce that the SplxAI Platform now natively supports connecting AI assistants and agents built with Glean!
This new integration significantly enhances SplxAI’s compatibility with major enterprise AI use cases, enabling organizations that rely on Glean to continuously red team and evaluate their AI assistants and agents for security, safety, and precision.
With our simple setup process, users can now connect their Glean-powered AI assistants to the SplxAI Platform in less than five minutes – without writing a single line of code – and immediately start running comprehensive tests and evals to ensure their AI systems remain secure and aligned with business objectives at all times.
Let’s explore how Glean is transforming the enterprise AI landscape, and how SplxAI helps practitioners strengthen the security and reliability of these AI applications.
We’re excited to announce that the SplxAI Platform now natively supports connecting AI assistants and agents built with Glean!
This new integration significantly enhances SplxAI’s compatibility with major enterprise AI use cases, enabling organizations that rely on Glean to continuously red team and evaluate their AI assistants and agents for security, safety, and precision.
With our simple setup process, users can now connect their Glean-powered AI assistants to the SplxAI Platform in less than five minutes – without writing a single line of code – and immediately start running comprehensive tests and evals to ensure their AI systems remain secure and aligned with business objectives at all times.
Let’s explore how Glean is transforming the enterprise AI landscape, and how SplxAI helps practitioners strengthen the security and reliability of these AI applications.
Glean: Transforming Enterprise Knowledge Management with AI
In the last years, Glean has established itself as a leading enabler of AI technology within the enterprise, empowering organizations to streamline internal knowledge management and dramatically increase employee efficiency through generative AI technology.
Glean’s AI assistants and agents can integrate with over 100 internal apps and data sources, dynamically retrieving information and automating workflows across departments. By embedding deeply within an organization's tool stack, Glean enables smarter decision-making, dramatically reduces the time employees spend searching for information, and accelerates everyday workflows.
Global enterprises – including Databricks, Deutsche Telekom, Duolingo, and many more – trust Glean’s solutions to improve employee satisfaction and drive productivity, ultimately saving their teams countless hours of work.
Glean’s seamless compatibility with widely adopted platforms like Slack, Microsoft Teams, and Zoom further positions it as one of the most frictionless and effective AI solutions in the enterprise market today.
In the last years, Glean has established itself as a leading enabler of AI technology within the enterprise, empowering organizations to streamline internal knowledge management and dramatically increase employee efficiency through generative AI technology.
Glean’s AI assistants and agents can integrate with over 100 internal apps and data sources, dynamically retrieving information and automating workflows across departments. By embedding deeply within an organization's tool stack, Glean enables smarter decision-making, dramatically reduces the time employees spend searching for information, and accelerates everyday workflows.
Global enterprises – including Databricks, Deutsche Telekom, Duolingo, and many more – trust Glean’s solutions to improve employee satisfaction and drive productivity, ultimately saving their teams countless hours of work.
Glean’s seamless compatibility with widely adopted platforms like Slack, Microsoft Teams, and Zoom further positions it as one of the most frictionless and effective AI solutions in the enterprise market today.
In the last years, Glean has established itself as a leading enabler of AI technology within the enterprise, empowering organizations to streamline internal knowledge management and dramatically increase employee efficiency through generative AI technology.
Glean’s AI assistants and agents can integrate with over 100 internal apps and data sources, dynamically retrieving information and automating workflows across departments. By embedding deeply within an organization's tool stack, Glean enables smarter decision-making, dramatically reduces the time employees spend searching for information, and accelerates everyday workflows.
Global enterprises – including Databricks, Deutsche Telekom, Duolingo, and many more – trust Glean’s solutions to improve employee satisfaction and drive productivity, ultimately saving their teams countless hours of work.
Glean’s seamless compatibility with widely adopted platforms like Slack, Microsoft Teams, and Zoom further positions it as one of the most frictionless and effective AI solutions in the enterprise market today.
How Organizations Leverage Glean's AI Solutions
Across many industries, enterprises are turning to Glean to maximize employee productivity, streamline knowledge access, and optimize customer support. The most common enterprise use cases we observe with Glean include:
Dynamic Knowledge Retrieval: Glean integrates with a broad range of knowledge and data sources, giving employees instant access to accurate, up-to-date information across departments and roles.
Streamlined Employee Onboarding: New hires are able to quickly navigate internal knowledge bases, significantly speeding up their ramp-up time and making them productive sooner.
Customer Support Optimization: Support teams leverage Glean’s capabilities to find resolutions for customer issues faster, reducing ticket handling times and maintaining high levels of customer satisfaction.
Through these use cases, many enterprises report measurable gains in employee efficiency, faster case resolution times, and overall improvements in employee experience and satisfaction. Learn more about Glean's most common use cases here.
Across many industries, enterprises are turning to Glean to maximize employee productivity, streamline knowledge access, and optimize customer support. The most common enterprise use cases we observe with Glean include:
Dynamic Knowledge Retrieval: Glean integrates with a broad range of knowledge and data sources, giving employees instant access to accurate, up-to-date information across departments and roles.
Streamlined Employee Onboarding: New hires are able to quickly navigate internal knowledge bases, significantly speeding up their ramp-up time and making them productive sooner.
Customer Support Optimization: Support teams leverage Glean’s capabilities to find resolutions for customer issues faster, reducing ticket handling times and maintaining high levels of customer satisfaction.
Through these use cases, many enterprises report measurable gains in employee efficiency, faster case resolution times, and overall improvements in employee experience and satisfaction. Learn more about Glean's most common use cases here.
Across many industries, enterprises are turning to Glean to maximize employee productivity, streamline knowledge access, and optimize customer support. The most common enterprise use cases we observe with Glean include:
Dynamic Knowledge Retrieval: Glean integrates with a broad range of knowledge and data sources, giving employees instant access to accurate, up-to-date information across departments and roles.
Streamlined Employee Onboarding: New hires are able to quickly navigate internal knowledge bases, significantly speeding up their ramp-up time and making them productive sooner.
Customer Support Optimization: Support teams leverage Glean’s capabilities to find resolutions for customer issues faster, reducing ticket handling times and maintaining high levels of customer satisfaction.
Through these use cases, many enterprises report measurable gains in employee efficiency, faster case resolution times, and overall improvements in employee experience and satisfaction. Learn more about Glean's most common use cases here.
Glean's State of Security
Glean’s solutions are built with state-of-the-art security and governance at their core. Their platform includes robust agentic guardrails, AI governance tools, and strict enforcement of data permissions, allowing organizations to tightly control internal access and prevent sensitive data leaks.
However, no AI solution is ever 100% secure against emerging risks. Even with strong permission controls and agentic guardrails, continuous security testing and evaluations of AI apps remain critical.
This is especially important in retrieval-augmented generation (RAG) systems – which are widely used with Glean – where changes to the knowledge base can introduce new vulnerabilities, including risks of unauthorized data exposure or poisoning of retrieved content. In high-trust environments where employees depend on AI-generated information to make critical business decisions, ensuring resilience against risks like data leakage, misinformation, or poisoned retrievals is crucial. Even small inaccuracies or unauthorized disclosures can lead to serious consequences – from eroding internal trust in AI systems, to regulatory non-compliance, to reputational damage and financial loss. As organizations scale their AI use cases across multiple departments, maintaining the integrity, reliability, and security of retrieved information becomes a foundational requirement for safe and successful enterprise AI adoption.
Glean’s solutions are built with state-of-the-art security and governance at their core. Their platform includes robust agentic guardrails, AI governance tools, and strict enforcement of data permissions, allowing organizations to tightly control internal access and prevent sensitive data leaks.
However, no AI solution is ever 100% secure against emerging risks. Even with strong permission controls and agentic guardrails, continuous security testing and evaluations of AI apps remain critical.
This is especially important in retrieval-augmented generation (RAG) systems – which are widely used with Glean – where changes to the knowledge base can introduce new vulnerabilities, including risks of unauthorized data exposure or poisoning of retrieved content. In high-trust environments where employees depend on AI-generated information to make critical business decisions, ensuring resilience against risks like data leakage, misinformation, or poisoned retrievals is crucial. Even small inaccuracies or unauthorized disclosures can lead to serious consequences – from eroding internal trust in AI systems, to regulatory non-compliance, to reputational damage and financial loss. As organizations scale their AI use cases across multiple departments, maintaining the integrity, reliability, and security of retrieved information becomes a foundational requirement for safe and successful enterprise AI adoption.
Glean’s solutions are built with state-of-the-art security and governance at their core. Their platform includes robust agentic guardrails, AI governance tools, and strict enforcement of data permissions, allowing organizations to tightly control internal access and prevent sensitive data leaks.
However, no AI solution is ever 100% secure against emerging risks. Even with strong permission controls and agentic guardrails, continuous security testing and evaluations of AI apps remain critical.
This is especially important in retrieval-augmented generation (RAG) systems – which are widely used with Glean – where changes to the knowledge base can introduce new vulnerabilities, including risks of unauthorized data exposure or poisoning of retrieved content. In high-trust environments where employees depend on AI-generated information to make critical business decisions, ensuring resilience against risks like data leakage, misinformation, or poisoned retrievals is crucial. Even small inaccuracies or unauthorized disclosures can lead to serious consequences – from eroding internal trust in AI systems, to regulatory non-compliance, to reputational damage and financial loss. As organizations scale their AI use cases across multiple departments, maintaining the integrity, reliability, and security of retrieved information becomes a foundational requirement for safe and successful enterprise AI adoption.
How SplxAI Ensures Full Integrity of Glean's AI Systems
The SplxAI Platform enables organizations to run risk assessments across more than 20 predefined probes — including tests for prompt injections, jailbreaks, and hallucinations — along with defining fully custom evaluation scenarios.
For Glean-powered AI applications, two probe categories are particularly critical:
RAG Poisoning: Tests a system’s susceptibility to malicious data injections by introducing intentionally misleading or harmful content into the dataset to assess whether the AI assistant incorporates poisoned information into its outputs.
RAG Precision: Evaluates how effectively the RAG system retrieves and embeds accurate, relevant information from authorized datasets, ensuring the assistant consistently provides trustworthy responses.
Given the dependency of enterprise workflows on precise and factual AI responses, proactively testing these areas is key to maintaining both security and user trust.
RAG Poisoning
Since Glean relies heavily on retrieval-augmented generation (RAG) to deliver accurate and relevant answers, it's crucial to assess its resilience against RAG poisoning attempts. RAG poisoning occurs when malicious or misleading content is introduced into the knowledge base, potentially leading the assistant to generate incorrect or harmful responses. By leveraging SplxAI's automated red teaming capabilities, you can simulate such poisoning scenarios to evaluate how Glean handles compromised data sources.
As an example, you can add a few entries to the company knowledge base – one referencing API keys, and another containing RAG poisoning content. Then, you run automated tests that attempt to use the poisoned entry to exfiltrate the API keys.
This example demonstrates how the assistant responds to a RAG poisoning attempt: rather than returning actual API keys, it provides a fake URL sourced from the poisoned content, which, if clicked, could exfiltrate data to a third-party website.
The cited sources clearly show that the RAG poison (labeled "Base") was utilized in the assistant's response.
RAG Precision
Given that Glean's effectiveness hinges on accurately retrieving and presenting information from vast internal data sources, ensuring high RAG precision is critical. RAG precision refers to the assistant's ability to fetch the most relevant and contextually appropriate information in response to user queries. With SplxAI, you can conduct automated assessments to measure the precision of Glean's AI assistants, verifying that it consistently delivers accurate and reliable information.
For example, you can add any text you'd like as company knowledge, then run automated tests that query this content in diverse ways to rigorously assess RAG retrieval.
Here’s an example of a successful RAG retrieval in response to a vague question. The assistant correctly extracted the relevant information from an injected internal story.
Continuous evaluations for RAG Precision allow teams to maintain high performance standards and prevent degradation over time as knowledge sources evolve and contain more data.
The SplxAI Platform enables organizations to run risk assessments across more than 20 predefined probes — including tests for prompt injections, jailbreaks, and hallucinations — along with defining fully custom evaluation scenarios.
For Glean-powered AI applications, two probe categories are particularly critical:
RAG Poisoning: Tests a system’s susceptibility to malicious data injections by introducing intentionally misleading or harmful content into the dataset to assess whether the AI assistant incorporates poisoned information into its outputs.
RAG Precision: Evaluates how effectively the RAG system retrieves and embeds accurate, relevant information from authorized datasets, ensuring the assistant consistently provides trustworthy responses.
Given the dependency of enterprise workflows on precise and factual AI responses, proactively testing these areas is key to maintaining both security and user trust.
RAG Poisoning
Since Glean relies heavily on retrieval-augmented generation (RAG) to deliver accurate and relevant answers, it's crucial to assess its resilience against RAG poisoning attempts. RAG poisoning occurs when malicious or misleading content is introduced into the knowledge base, potentially leading the assistant to generate incorrect or harmful responses. By leveraging SplxAI's automated red teaming capabilities, you can simulate such poisoning scenarios to evaluate how Glean handles compromised data sources.
As an example, you can add a few entries to the company knowledge base – one referencing API keys, and another containing RAG poisoning content. Then, you run automated tests that attempt to use the poisoned entry to exfiltrate the API keys.
This example demonstrates how the assistant responds to a RAG poisoning attempt: rather than returning actual API keys, it provides a fake URL sourced from the poisoned content, which, if clicked, could exfiltrate data to a third-party website.
The cited sources clearly show that the RAG poison (labeled "Base") was utilized in the assistant's response.
RAG Precision
Given that Glean's effectiveness hinges on accurately retrieving and presenting information from vast internal data sources, ensuring high RAG precision is critical. RAG precision refers to the assistant's ability to fetch the most relevant and contextually appropriate information in response to user queries. With SplxAI, you can conduct automated assessments to measure the precision of Glean's AI assistants, verifying that it consistently delivers accurate and reliable information.
For example, you can add any text you'd like as company knowledge, then run automated tests that query this content in diverse ways to rigorously assess RAG retrieval.
Here’s an example of a successful RAG retrieval in response to a vague question. The assistant correctly extracted the relevant information from an injected internal story.
Continuous evaluations for RAG Precision allow teams to maintain high performance standards and prevent degradation over time as knowledge sources evolve and contain more data.
The SplxAI Platform enables organizations to run risk assessments across more than 20 predefined probes — including tests for prompt injections, jailbreaks, and hallucinations — along with defining fully custom evaluation scenarios.
For Glean-powered AI applications, two probe categories are particularly critical:
RAG Poisoning: Tests a system’s susceptibility to malicious data injections by introducing intentionally misleading or harmful content into the dataset to assess whether the AI assistant incorporates poisoned information into its outputs.
RAG Precision: Evaluates how effectively the RAG system retrieves and embeds accurate, relevant information from authorized datasets, ensuring the assistant consistently provides trustworthy responses.
Given the dependency of enterprise workflows on precise and factual AI responses, proactively testing these areas is key to maintaining both security and user trust.
RAG Poisoning
Since Glean relies heavily on retrieval-augmented generation (RAG) to deliver accurate and relevant answers, it's crucial to assess its resilience against RAG poisoning attempts. RAG poisoning occurs when malicious or misleading content is introduced into the knowledge base, potentially leading the assistant to generate incorrect or harmful responses. By leveraging SplxAI's automated red teaming capabilities, you can simulate such poisoning scenarios to evaluate how Glean handles compromised data sources.
As an example, you can add a few entries to the company knowledge base – one referencing API keys, and another containing RAG poisoning content. Then, you run automated tests that attempt to use the poisoned entry to exfiltrate the API keys.
This example demonstrates how the assistant responds to a RAG poisoning attempt: rather than returning actual API keys, it provides a fake URL sourced from the poisoned content, which, if clicked, could exfiltrate data to a third-party website.
The cited sources clearly show that the RAG poison (labeled "Base") was utilized in the assistant's response.
RAG Precision
Given that Glean's effectiveness hinges on accurately retrieving and presenting information from vast internal data sources, ensuring high RAG precision is critical. RAG precision refers to the assistant's ability to fetch the most relevant and contextually appropriate information in response to user queries. With SplxAI, you can conduct automated assessments to measure the precision of Glean's AI assistants, verifying that it consistently delivers accurate and reliable information.
For example, you can add any text you'd like as company knowledge, then run automated tests that query this content in diverse ways to rigorously assess RAG retrieval.
Here’s an example of a successful RAG retrieval in response to a vague question. The assistant correctly extracted the relevant information from an injected internal story.
Continuous evaluations for RAG Precision allow teams to maintain high performance standards and prevent degradation over time as knowledge sources evolve and contain more data.
Closing Remarks
With native support for Glean, the SplxAI Platform continues to expand its leadership as the go-to red teaming solution for enterprises building and deploying AI applications at scale.
By offering seamless integrations, automated security testing, and continuous risk evaluation across a growing ecosystem of AI solutions, SplxAI empowers security and AI teams to confidently deploy AI initiatives without compromising on safety or trust.
Start testing and securing your Glean-powered AI assistants today – and securely unlock the full potential of AI innovation.
With native support for Glean, the SplxAI Platform continues to expand its leadership as the go-to red teaming solution for enterprises building and deploying AI applications at scale.
By offering seamless integrations, automated security testing, and continuous risk evaluation across a growing ecosystem of AI solutions, SplxAI empowers security and AI teams to confidently deploy AI initiatives without compromising on safety or trust.
Start testing and securing your Glean-powered AI assistants today – and securely unlock the full potential of AI innovation.
With native support for Glean, the SplxAI Platform continues to expand its leadership as the go-to red teaming solution for enterprises building and deploying AI applications at scale.
By offering seamless integrations, automated security testing, and continuous risk evaluation across a growing ecosystem of AI solutions, SplxAI empowers security and AI teams to confidently deploy AI initiatives without compromising on safety or trust.
Start testing and securing your Glean-powered AI assistants today – and securely unlock the full potential of AI innovation.
Ready to leverage AI with confidence?
Ready to leverage AI with confidence?
Ready to leverage AI with confidence?
