Skip to main content
Paid
Cortex XSIAM logo
Data & Analytics paid

Cortex XSIAM

Verified 1 day ago
Compare Alternatives Claim this listing
About Cortex XSIAM 18s read
1 min read

Palo Alto Networks' AI-driven security operations platform that consolidates SIEM, SOAR, and endpoint detection into one AI SOC platform. XSIAM uses AI to automatically investigate and close up to 99% of alerts without analyst involvement, dramatically reducing mean time to respond. The platform integrates threat intelligence from Unit 42 and enforces consistent security policies across the environment.

Best for: Large enterprises looking to modernise their SOC with a unified AI-driven platform
Global availability
Screenshot
Key Features
  • AI-driven alert triage and auto-closure
  • Unified SIEM, SOAR, and EDR platform
  • Unit 42 threat intelligence integration
  • Automated incident response workflows
  • Behavioural analytics and UEBA
Pros & Cons
What we like
Dramatically reduces alert fatigue through AI automation
Single platform eliminates tool sprawl in SOC
Strong threat intelligence from Unit 42 research team
What to consider
Premium enterprise pricing with complex licensing
Migration from existing SIEM can be resource-intensive
Questions and Answers

No questions yet. Be the first to ask!

Log in to ask a question.

User Reviews

No reviews yet. Be the first to review Cortex XSIAM!

Log in to leave a review.

You might also like
John Snow Labs J
John Snow Labs
paid
H2O.ai H
H2O.ai
freemium
Talend AI T
Talend AI
paid
User Reviews

No reviews yet. Be the first to leave a review!

Log in to leave a review.

Was this page helpful?

AI Glossary

The simulation of human intelligence in machines programmed to think, learn, and problem-solve. AI encompasses machine learning, natural language processing, computer vision, and more.

A deep learning model trained on vast text datasets to understand and generate human-like language. Examples include GPT-4, Claude, and Gemini.

AI systems that create new content - text, images, audio, video, or code - based on patterns learned during training rather than retrieving existing data.

The practice of designing and refining input text (prompts) to guide an AI model toward producing more accurate, relevant, or creative outputs.

A computing architecture inspired by the human brain, consisting of interconnected layers of nodes that learn to recognise patterns in data.

A branch of AI where algorithms improve automatically through experience and exposure to data, without being explicitly programmed for each task.

AI technology that enables computers to understand, interpret, and generate human language - the foundation of chatbots, translation tools, and voice assistants.

The process of further training a pre-trained AI model on a specific, smaller dataset to specialise it for a particular task or domain.

When an AI model generates plausible-sounding but factually incorrect or entirely fabricated information, often presenting it with false confidence.

The units of text (roughly 4 characters or ¾ of a word in English) that LLMs process. Model costs and context limits are measured in tokens.

The maximum amount of text (measured in tokens) an LLM can process in a single interaction - both input and output combined.

A technique that enhances LLM outputs by fetching relevant external documents at query time, grounding responses in up-to-date or proprietary data.

Numerical vector representations of text, images, or other data that capture semantic meaning, enabling AI to measure similarity and retrieve relevant content.

The process of running a trained AI model to produce predictions or outputs from new input data - distinct from the training phase.

An AI system that autonomously plans and executes multi-step tasks by combining reasoning, tool use (web search, code execution, APIs), and memory.

AI models that can process and generate multiple types of data - such as text, images, audio, and video - within a single unified system.

A large-scale AI model trained on broad data that serves as a base for many downstream applications via fine-tuning or prompting.

A pricing model where core features are available for free, with premium features, higher usage limits, or advanced capabilities offered via paid plans.

A set of protocols that allows developers to integrate an AI tool's capabilities directly into their own applications and workflows.

Zero-shot means the model handles a task without any examples; few-shot means it is given a small number of examples in the prompt to guide its response.
Trending Now
Claude AI Learning Brain OpenAI Operator
Tool Info
Verified 1 day ago
Pricing paid
Category Data & Analytics
Added Jun 02, 2026
Source Manual Entry
Visit Website Back to Tools See Alternatives
Share:
Pricing Notes

AI tool pricing changes frequently. The pricing shown was accurate at our last editorial review. We recommend checking the tool's website directly for current plans.

Last reviewed: Oct 26, 2026
Check Current Pricing
Related Tools
John Snow Labs paid H2O.ai freemium Talend AI paid Anomalo AI paid
Compare

See how Cortex XSIAM stacks up against alternatives.

vs John Snow Labs vs H2O.ai vs Talend AI
Pricing
Paid
Visit Tool
Best For

Large enterprises looking to modernise their SOC with a unified AI-driven platform

Embed this tool

Add a link badge to your website or blog:

People Also Viewed

John Snow Labs
John Snow Labs
Paid
 H2O.ai
H2O.ai
Freemium
 Talend AI
Talend AI
Paid
 Anomalo AI
Anomalo AI
Paid