Organizations are rapidly deploying Large Language Models (LLMs) to power copilots, intelligent search, analytics, and decision support. But for regulated industries and sensitive environments, traditional AI deployments introduce significant privacy, security, and governance concerns.
Duality’s LLM Inference solution enables organizations to run AI workloads inside Trusted Execution Environments (TEEs), ensuring sensitive data, prompts, and responses remain protected throughout the inference process.
Trusted Execution Environments create hardware-isolated enclaves where AI applications can securely process sensitive information.
Data, prompts, retrieval results, and model interactions remain protected from cloud infrastructure, administrators, and other unauthorized parties, allowing organizations to leverage modern AI capabilities without sacrificing security or control.
Run LLMs inside hardware-protected Trusted Execution Environments that isolate sensitive workloads from the surrounding infrastructure.
Deploy Retrieval-Augmented Generation solutions that securely retrieve and analyze proprietary documents, records, and knowledge bases.
Support data stored directly within confidential environments or securely accessed from external repositories through Duality’s privacy-preserving technologies.
Run AI applications across public cloud, sovereign cloud, hybrid, and on-premises environments while maintaining consistent security controls.
Verify the integrity of the execution environment before sensitive models, credentials, and datasets are provisioned.
Apply granular policies, access controls, auditing, and logging to ensure AI usage remains secure, compliant, and accountable.
Deploy AI assistants, copilots, and intelligent workflows without exposing sensitive data to cloud providers or third-party services.
Safeguard prompts, documents, retrieval results, proprietary models, and business-critical information throughout the AI inference lifecycle.
Enforce policies, auditing, access controls, and data sovereignty requirements to support regulated and mission-critical AI deployments.
Leverage cloud-scale infrastructure and leading LLMs while maintaining the security, privacy, and control required for enterprise, government, and defense environments.
Enable employees to securely interact with internal documents, policies, and business knowledge through AI-powered assistants.
Analyze patient records, clinical documentation, research data, and operational information while maintaining privacy and regulatory compliance.
Support fraud detection, risk analysis, customer service, compliance investigations, and research workflows involving highly sensitive financial information.
Deploy AI assistants and analytical tools that operate on sensitive, classified, or sovereign data while maintaining strict security requirements.
Securely analyze contracts, policies, regulatory documents, and case materials without exposing confidential information.
Build AI applications that combine LLM reasoning with protected enterprise knowledge repositories.
Traditional AI deployments require organizations to trust the underlying infrastructure with access to sensitive information.
Trusted Execution Environments change this model by creating cryptographically protected execution environments where AI workloads can operate securely, even on infrastructure that would otherwise be considered untrusted.
This enables organizations to leverage state-of-the-art AI models while maintaining privacy, governance, and control over their most valuable data assets.
Organizations should not have to choose between AI innovation and data security.
Duality’s LLM Inference solution combines confidential computing, secure orchestration, governance, and privacy-preserving data access to help organizations deploy AI confidently across even the most sensitive environments.