Confidential AI

Scale AI Innovation with Security, Trust, and Sovereignty at the Core.

Name: Confidential AI
Brand: Fortanix
Rating: 4 (1 reviews)

Build and run the AI you want. Keep data, models, and agents fully protected with Confidential Computing.

Full Protection for Enterprise Data,
AI Models, and Agents

Fortanix Confidential AI secures sensitive data, proprietary frontier models, and agents across the full AI lifecycle. The joint Fortanix-NVIDIA solution, built on Confidential Computing, keeps both data and model IP inaccessible to the underlying infrastructure, with verifiable trust and cryptographic guarantees. Whether you run AI workloads in confidential VMs or Confidential Containers (CoCo) on Kubernetes, Fortanix attests every workload and releases keys only to verified environments. From scaling enterprise AI and deploying frontier AI on premises to securing multi-tenant AI Factories and building sovereign AI clouds, Fortanix Confidential AI is your proven path to AI innovation, with security, trust, and sovereignty at the core.

Confidential AI Ecosystem

More Ways Fortanix
Confidential AI Helps

Fortanix Confidential Al help eliminate the barrier of Al adoption by protecting both proprietary Al models and sensitive data while in use to accelerate Al innovation without compromising security, trust, and sovereignty.

AI Labs

Deploy frontier models wherever enterprise data lives, with your IP fully protected.

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Multitenant AI Factories

Turn multi-tenancy into a trusted, verifiable architecture.

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Sovereign AI Cloud

Guarantee data residency and in-border AI innovation

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Secure Environment for AI Workloads

Whether your AI runs on premises or in public clouds, Confidential CPUs and GPUs ensure in-memory encryption, keeping sensitive data, model weights, and inference protected, even from privileged insiders. Use the Trusted Execution Environments (TEEs) to

Ensure data, models, and agents security
Run best in class AI on premises
Meet regulatory requirements

*Supported public clouds: Azure and Google

Verifiable Infrastructure Integrity

Composite attestation for CPU and GPU create a single chain of trust. Verify exactly what AI workload is running with hardware-signed proof. The confidential control plane allows you to

Create Confidential VMs and Confidential Containers
Set policy controls

Secure Key Release

Access to datasets and model artifacts is allowed only after verified attestation. Decryption happens only within verified, isolated environments. Drive crypto agility with

FIPS 140-2 Level 3 Certified HSM with built-in KMS
Latest NIST-approved PQC algorithms

Bringing our AI detection models into customer environments requires us to think about both our growth and protecting our IP. Fortanix Confidential AI, with support for Confidential Containers, removes any concern around IP theft or misuse.

We can deploy our models into third-party environments without changing how we work. Now we can meet our customers wherever they need us and bring our technology to new markets, helping more organizations fight AI fraud and deepfakes - CEO and Co-founder, Zohaib Ahmed

Zohaib Ahmed

CEO and Co-founder, Resemble AI

Enterprise AI transformation in the US, India, and globally is hitting a wall that isn't about model quality - it’s about trust and control. That's why we've built Gnani.ai around Resident AI: intelligence that operates inside an enterprise's own environment, under its own controls, rather than asking enterprises to hand that control away.

Partnering with Fortanix lets us back that promise with the confidential computing and data security enterprises actually require before they'll put agentic AI into production.”

AI factories are engines of enterprise transformation, and must be built on a foundation of security and trust,

Together with Fortanix, we’re bringing NVIDIA Confidential Computing into these next-generation environments, enabling organizations to run powerful AI with verified confidentiality, compliance and control in on-premises data centers.

Justin Boitano

Vice President of enterprise AI products at NVIDIA

Fortanix has been an early adopter of Azure Confidential Computing since 2020.

Fortanix’s use of Azure confidential VMs with NVIDIA H100 Tensor Core GPUs in Armet AI is another example of their ability to make Confidential Computing, and now Confidential AI, available to a broader audience.

Mark Russinovich

CTO, Deputy CISO and Technical Fellow

Armet AI satisfies a need in the market for organizations to securely build custom generative AI applications while ensuring data security, privacy, governance and compliance.

The desire for organizations to quickly deploy GenAI that’s tailored to their specific needs is exploding, but in doing so, they need to prioritize the security of their data and large language models to ensure compliance and reduce risk.

Craig Matsumoto

Analyst

Our models represent years of proprietary research and engineering - protecting that IP while expanding access is a core tension in enterprise deployment.

Working with Fortanix on NVIDIA Confidential Computing-backed infrastructure lets us resolve that directly, giving organizations in government, healthcare, and finance the ability to run our Text to Speech models on their own servers, on their own data.

Kuba Abramczyk

Forward Deployed Engineer at ElevenLabs

The challenge with enterprise AI isn’t just getting models running. It’s building an architecture that lets organizations use their most important data securely, wherever AI is running,” said Jeremy Foster, Senior Vice President and General Manager, Cisco Compute.

Cisco believes security has to be designed into the AI infrastructure from the start, across compute, networking, data, applications and the workloads themselves. Confidential computing adds an important layer by protecting data and models while they’re actively being used, helping enterprises move AI into production with greater confidence.

Jeremy Foster

Senior Vice President and General Manager, Cisco

Voice AI gets more useful the more context it can carry through a conversation and beyond. For enterprises, that creates a hard engineering problem: the information that makes the experience work may be the very information you can’t risk exposing, said Kris Efland, VP of Engineering at Deepgram.

Our work with Fortanix gives teams a way to run Deepgram’s real-time voice AI in their own environment while keeping audio and model weights protected during inference. Fortanix’s support for Confidential Containers brings greater protection into the Kubernetes systems enterprises already operate, making private voice AI easier to integrate safely and at scale.