Fortinet vs Siemens

AI orchestration platform automating security and network operations: alert triage/investigation, network configuration validation, and threat hunting, integrated across Fortinet's management products.

Discovers, controls and governs AI use across enterprise environments: shadow-AI detection (6,500+ AI application URLs), AI-application visibility (FortiView for AI), and AI-workload data-loss prevention.

Cloud-native data-loss-prevention agent combining machine-learning content/context analysis with a GenAI-powered assistant that summarizes and contextualizes incidents for insider-risk and data-egress protection.

Email security gateway combining machine learning, LLM-based content analysis and image recognition to detect phishing, BEC and other threats across the email lifecycle.

Uses AI-based behavioural analysis of network traffic to detect lateral movement, data exfiltration and privilege escalation without endpoint agents, sold as on-premises appliances and VMs or as FortiNDR Cloud.

Sandbox appliance/service for zero-day and advanced-threat detection, using AI-powered analysis (a purpose-built ML engine plus artificial neural networks) alongside static and dynamic analysis to accelerate verdicts.

Applies AI/ML analysis to telemetry from Fortinet network devices to detect pattern anomalies and automate network troubleshooting.

Generative-AI assistant for industrial engineers that answers equipment-troubleshooting questions by chat, generates and debugs automation code, and supports digital-twin simulation, built with Microsoft Azure AI.

Ready-to-use AI visual quality inspection system that trains on roughly 20 good samples to detect anomalies, deviations and missing parts on a production line without machine-vision or AI expertise.

Cloud predictive-maintenance software that applies industrial AI to machine and process data to forecast asset failures, rank risk across sites and prioritise maintenance work.

Generative and agentic AI system for Siemens EDA tools that ingests and vectorises multimodal design data, exposes a natural-language interface across the design workflow and automates debugging, with customer-choice LLM support.

Edge software suite for packaging, deploying, running and monitoring AI models on the factory floor, comprising an AI SDK, AI Inference Server and AI Asset Manager running on Siemens Industrial Edge and NVIDIA-accelerated industrial PCs.

Visual drag-and-drop and notebook-based platform in the Rapidminer portfolio for building, training and explaining machine learning and generative AI models, with AutoML tooling and deployment to cloud, on-premises or edge infrastructure.

Enterprise knowledge-graph platform in the Rapidminer portfolio, built on open W3C standards (RDF, SPARQL, OWL, SHACL), that federates cross-domain data into a governed semantic layer and gives AI agents a queryable, traceable context for grounded answers.