CrowdStrike Charlotte AI: Solution Overview, Pros and Cons 

What Is CrowdStrike Charlotte AI? 

CrowdStrike Charlotte AI is a generative AI assistant for cybersecurity teams using the CrowdStrike Falcon platform. Leveraging AI models and the telemetry of the Falcon platform, Charlotte AI aims to simplify security operations and reduce investigation times.

Charlotte AI allows users to direct workflows, triage detections, and receive answers to complex queries in plain language. The tool integrates threat intelligence with anonymized usage data and additional context.

Key Features of CrowdStrike Charlotte AI 

CrowdStrike Charlotte AI provides the following key features:

• Generative AI-powered workflows: Uses a multi-model AI architecture integrated with threat intelligence to provide insights for security teams to triage incidents, analyze adversary activity, and automate responses.
• Simplified user interaction: Through natural-language processing, allows analysts to generate scripts, explain command lines, and extract telemetry without the need to master complex scripting languages or sift through documentation.
• Accelerated investigation and response: Reduces investigation times by allowing users to drill deeper into emerging threats and indicators of adversary presence. It enables real-time querying of the IT environment across endpoints, servers, and cloud workloads. Analysts can also create and share promptbooks to simplify team workflows.
• Enhanced analyst productivity: Automates routine tasks such as incident creation, analysis, and reporting to help security teams save time.
• Safe and transparent AI adoption: Operates with safeguards, including traceable and auditable insights. Role-based access controls and built-in protections minimize risks such as AI hallucinations while ensuring secure usage across teams.
• Democratization of expertise: Closes the skills gap and compresses onboarding cycles, allowing teams to operate with varying levels of experience.

Understanding How CrowdStrike Charlotte AI Works 

CrowdStrike Charlotte AI operates through an architecture that emphasizes speed and safety across security workflows. This approach leverages a multi-AI system that integrates task-specific AI agents, CrowdStrike’s telemetry, and generative AI technologies. Here’s a breakdown of how Charlotte AI functions:

Multi-AI Architecture

Charlotte AI employs a multi-AI architecture, where workflows are partitioned into discrete sub-tasks, and specialized AI agents handle each task. These agents are tailored for particular roles, such as retrieving data, generating scripts, or analyzing threat intelligence. 

The architecture allows the system to select the best foundational model for each sub-task, ensuring accuracy without compromising security or burdening analysts with complexity.

By leveraging diverse AI models and isolating their use, Charlotte AI minimizes trade-offs inherent to relying on a single model. 

Task-Oriented AI Agents

Charlotte AI uses over a dozen AI agents that are fine-tuned for different tasks. These agents work together to handle user prompts, retrieve relevant data, validate outputs, and structure complete answers. The process includes the following steps:

1. Understanding the question: AI agents first interpret the user’s input, extracting key entities such as threat actors, vulnerabilities, or indicators of compromise.
2. Routing subtasks: A router agent determines which specialized AI agents should handle each aspect of the request.
3. Data retrieval or task execution: For requests requiring API calls (e.g., scanning for indicators), dedicated agents retrieve the necessary data. For other tasks, such as generating a CrowdStrike Query Language (CQL) script, other agents handle the execution.
4. Validation: A validation agent reviews outputs to ensure completeness and accuracy, flagging any inconsistencies or missing information.
5. Response generation: A final agent structures the response in a human-readable format.

Safeguards Against Hallucinations

To mitigate the risks of generative AI hallucinations (inaccurate or unsupported outputs), Charlotte AI includes multiple safeguards. These include validation agents that verify outputs against Falcon platform data and task-specific performance monitoring. By isolating tasks across multiple AI agents and models, Charlotte AI can reduce the impact of any single model’s failure, ensuring a consistent and secure user experience.

Workflow Acceleration Through Generative AI

Charlotte AI accelerates investigation and response by enabling users to interact with the Falcon platform through natural language. Analysts can query their entire IT environment, generate detection rules, or analyze threat intelligence in real time. For example, Charlotte AI can assist in creating and running CQL queries, investigating zero-day vulnerabilities, or analyzing indicators of compromise.

This design allows teams of all skill levels to operate efficiently. Novice analysts can perform advanced tasks like querying large datasets or generating mitigation scripts, while experienced users benefit from significant time savings.

Related content: Read our guide to security analytics

CrowdStrike Charlotte AI Limitations 

While Charlotte AI offers significant advantages in security operations, it has some limitations that teams should consider:

• Dependence on Falcon Platform: Charlotte AI is deeply integrated with the CrowdStrike Falcon platform. While this ensures seamless functionality for Falcon users, organizations using other security tools may find limited interoperability.
• Accuracy constraints and AI hallucinations: Like all generative AI models, Charlotte AI can sometimes produce inaccurate or misleading responses. CrowdStrike has implemented safeguards, such as validation agents and role-based access controls, but users must still verify outputs before acting on them.
• Limited customization for non-standard use cases: Charlotte AI is optimized for common security workflows, but its ability to handle highly customized or unconventional use cases is limited. Security teams with unique operational needs may need to supplement AI-driven insights with manual analysis.
• Resource requirements for full optimization: Organizations looking to maximize Charlotte AI’s capabilities may need to invest time in training analysts to use the system effectively. While the tool reduces onboarding time, teams unfamiliar with Falcon’s modules may still require some ramp-up.

Exabeam: Ultimate Alternative to Crowdstrike Charlotte AI 

Agentic AI is redefining security operations by shifting from passive detection to proactive defense, enabling AI-driven systems to investigate threats, correlate data, and execute response actions autonomously. As cyber threats continue to evolve, security teams need solutions that go beyond static AI assistants and deliver real-time, adaptive intelligence.

Exabeam Nova is purpose-built to meet these demands, acting as a force multiplier within the SOC. By automating investigations, reducing alert fatigue, and accelerating response times, it empowers analysts to operate more efficiently and effectively. With seamless integration into the New-Scale Platform, Exabeam Nova eliminates the need for separate tools, ensuring AI-driven insights are embedded directly into existing security workflows.

Unlike traditional AI assistants, Exabeam Nova dynamically adjusts its investigative approach based on the severity and context of each threat. It delivers precise, actionable insights tailored to both frontline analysts and security leaders, ensuring that every stakeholder has the intelligence needed to make informed decisions. Exabeam Nova develops rich case summary notes within Threat Center that compile key threat indicators, related detections, and recommended actions thereby reducing the time analysts spend piecing together fragmented data. 

Built on the Exabeam proprietary Threat Classification Framework and leveraging ten times more training data than its predecessor, it provides deeper investigative knowledge and more accurate threat prioritization.

Security and compliance remain at the core of Exabeam Nova. Unlike other AI solutions that rely on external cloud training, Exabeam Nova ensures that customer data remains private and secure. No investigation details are used for model training, and all data is processed within the Exabeam trusted environment, maintaining compliance with industry regulations and safeguarding sensitive information.

Beyond investigations, Exabeam Nova enhances security posture evaluations through Outcomes Navigator, where it helps teams assess use case coverage, pinpoint gaps, and provide targeted recommendations to strengthen defenses. By analyzing log sources, behavioral models, and rule utilization, it enables organizations to continuously refine and optimize their security strategy.

As AI-driven cyber threats grow in sophistication, organizations can no longer afford to rely on outdated security models. Exabeam Nova delivers a proactive, AI-powered security strategy that enables teams to detect threats faster, respond with greater confidence, and continuously strengthen their security posture. The future of security operations is here—and it’s powered by Exabeam Nova. For more information visit Exabeam.com