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Cornerstones of Confidential AI and Data Collaboration
Easily create a Trusted Execution Environment (TEE).
Abstract the instantiation of a TEE (secure enclave) to isolate data, code, and secrets. Anjuna Seaglass virtualizes modern CPUs and cloud infrastructure services to offer hardware-enforced isolation that protects from unauthorized access by users or software, regardless of privilege level.
Encrypt data in all three states.
Secure sensitive workloads by ensuring that data is always encrypted. Anjuna Seaglass implements a confidential runtime to enable data-in-use encryption inside the TEE, and control at-rest and in-transit encryption to prevent vulnerabilities as data leaves the confidential computing environment.
Authenticate the identity of your code.
Create a high-trust environment by ensuring both your infrastructure and applications can be trusted before they are allowed to boot. Anjuna Seaglass uses a cryptographic attestation policy manager to orchestrate the secure distribution of secrets to applications inside the enclave.
Secure apps across clouds without rework.
Run and manage all applications, traditional and cloud-native, on all the leading public clouds (AWS, Azure, Google Cloud) without requiring code changes and using a consistent operational model. Learn more about Anjuna Seaglass.
Get Started Free with Anjuna Seaglass
Try free for 30 days on AWS, Azure or Google Cloud, and experience the power of intrinsic cloud security.
Use Cases for Confidential Computing with Anjuna
The Trust Foundation for Agentic AI
AI agents now act with privileged access to data and systems. Without hardware-rooted trust, they are vulnerable to memory poisoning, tool misuse, and identity spoofing. Anjuna eliminates these risks with Confidential Computing.
The Path to Secure AI
Anjuna allows businesses to navigate the complexities of AI adoption with unparalleled security, compliance, and innovation, all while preserving data privacy and integrity.
Anjuna Seaglass: The Universal Confidential Computing Platform
Run any application with intrinsic security and always-on confidentiality—no code changes required. Built on hardware-rooted trust, Seaglass makes cloud and AI workloads provably secure.
Anjuna Northstar: The AI Data Fusion Clean Room
Unlock safe collaboration with AI agents and sensitive data. Northstar enables multi-party data fusion, privacy-preserving workflows, and secure AI-driven insights—all inside a Confidential Clean Room.
FAQ
Confidential Computing uses hardware-rooted Trusted Execution Environments (TEEs), also called secure enclaves, to isolate code, data, and secrets at runtime. This means data is protected not just when stored or in transit, but also while it's actively being processed.
A TEE, sometimes called a secure enclave, is a hardware-isolated region of a processor where code and data can run completely shielded from the rest of the system. Even the host operating system, hypervisor, or a cloud provider's administrators cannot inspect or tamper with what's happening inside. Anjuna abstracts the complexity of creating and managing TEEs so developers don't have to interact with low-level hardware APIs directly.
Most security solutions protect data at rest (stored on disk) and in transit (moving across a network), but leave data exposed while it's being processed in memory. Anjuna adds data-in-use encryption by running workloads inside TEEs, ensuring sensitive information is never exposed in plaintext at any stage of its lifecycle.
Attestation is the process of cryptographically verifying that a piece of code is exactly what it claims to be, running in a genuine hardware enclave, before any secrets are released to it. Anjuna's policy-based attestation manager orchestrates this process, so applications can establish a verified chain of trust before they're allowed to boot or access sensitive data.
Autonomous AI agents present a unique threat surface: they operate with privileged access to data and tools, making them susceptible to memory poisoning, tool misuse, and identity spoofing. Anjuna runs agents inside TEEs and enforces runtime policies that govern what actions an agent is permitted to take, effectively providing a hardware-rooted supervisory layer that the agent itself cannot override.
Anjuna Northstar implements a secure, isolated environment where multiple parties can contribute proprietary data and AI models for collaborative processing without any party being able to see the other's raw inputs. The computation happens inside an enclave, so each side's intellectual property and sensitive data remain protected even during joint AI training or inference.
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