Company Overview
Confidential AI company enabling secure AI deployment in trusted execution environments for privacy-preserving inference.
Headquartered in Paris, France, Mithril Security offers its BlindAI as a solution for organizations navigating the complexities of confidential computing and hardware-enforced isolation for AI systems. The platform is positioned within the broader AI Infrastructure Security category, where AI Security Intelligence tracks 12 companies building specialized capabilities.
Founded in 2021, Mithril Security has been building its platform during the critical period when enterprise AI adoption — and the corresponding security challenges — began their exponential acceleration.
Why Watch This Company
Mithril Security addresses a critical gap in the AI security stack: the infrastructure layer that most AI-specific security tools take for granted. As AI workloads demand specialized compute and networking, confidential computing and hardware-enforced isolation for AI systems becomes essential for organizations running production AI systems at scale.
Key Facts
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Headquarters
Paris, France
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Category
AI Infrastructure Security
Primary Product
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BlindAI
Confidential AI company enabling secure AI deployment in trusted execution environments for privacy-preserving inference.
AI Infrastructure Security Landscape
AI Infrastructure Security →
AI Infrastructure Security focuses on protecting the compute, network, and platform layers that underpin AI/ML workloads. As enterprises shift AI training and inference to cloud and edge environments, the infrastructure stack — GPUs, model serving endpoints, data pipelines, API gateways, and container orchestration — becomes a high-value target. This category covers solutions that secure these components without introducing latency or limiting model performance.
12 companies tracked in this category
Buyer's Evaluation Framework
Key questions to evaluate any AI Infrastructure Security vendor — including Mithril Security:
Does the platform provide security controls specifically designed for GPU clusters, model serving endpoints, and AI pipeline infrastructure?
Can the solution inspect and enforce policies on AI/ML API traffic without adding significant latency to inference calls?
How does the vendor handle multi-cloud and hybrid AI deployments where workloads span different infrastructure providers?
Does the platform integrate with container orchestration and ML pipeline tools (Kubernetes, Kubeflow, MLflow)?
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Category Peers — AI Infrastructure Security
11 other companies in this category
Anjuna
Palo Alto, CA
Cato Networks
Tel Aviv, Israel
★ Featured Profile
Cloudflare
San Francisco, CA
★ Featured Profile
Cylake
Tel Aviv, Israel
Fortanix
Santa Clara, CA
Fortinet
Sunnyvale, CA
Netskope
Santa Clara, CA
★ Featured Profile
Operant AI
San Francisco, CA
Sophos
Abingdon, UK
Trend Micro
Tokyo, Japan
Zscaler
San Jose, CA
★ Featured Profile