Confidential model inference
Enclave provides access to language models, vision-language models, and voice transcription through a unified API for private multimodal workloads.
Sovereign AI infrastructure and agent tools for organizations handling sensitive data.
Prem is a sovereign AI platform for organizations that need to use models and agents while keeping sensitive data and infrastructure under their control. Its offering includes Enclave, a confidential inference API and deployable infrastructure for running models in hardware-isolated environments, and Fluso, an agent platform for building and deploying agents based on enterprise procedures. Prem’s central purpose is to make private AI workloads verifiable: encrypted payloads are processed in trusted execution environments, with cryptographic attestation used to check enclave integrity before data is sent. The platform is presented for regulated and data-sensitive work across healthcare, financial services, government, legal, and retail settings.
Enclave provides access to language models, vision-language models, and voice transcription through a unified API for private multimodal workloads.
Inference runs in trusted execution environments with memory isolation intended to prevent infrastructure operators and host administrators from viewing plaintext data during processing.
Clients can verify an enclave’s identity and integrity before transmitting a payload, using cryptographic proof rather than relying only on provider assurances.
Enclave is described as compatible with existing OpenAI SDKs, allowing developers to connect through a unified endpoint with a client SDK change.
Enclave can be accessed through the API dashboard or licensed to run on-premises or in a customer’s own cloud. Prem also offers Fluso for building and deploying enterprise agents based on proprietary standard operating procedures.
Compliance teams can process sensitive regulatory documents with a model deployed inside their environment. Prem describes a deployment that processes datasets hourly without data leaving that environment.
Healthcare teams can extract structured information from unstructured patient records while keeping the workload within sovereign infrastructure, supporting workflows where public-cloud AI is unsuitable.
Retail teams can train and run an on-premises forecasting model on proprietary transaction data, using sales patterns across stores without sending them to a third-party API.
Enclave processes requests inside hardware-isolated trusted execution environments. Payloads are encrypted on the client, decrypted within the enclave for processing, and the output is re-encrypted before leaving the isolation boundary.
Yes. Enclave supports cryptographic attestation so a client can check the enclave’s identity and integrity before transmitting a payload.
The service is available through an API dashboard, and Prem also offers a license to run Enclave on-premises or in the organization’s own cloud.
The site lists large language models, vision-language models, and secure voice transcription. It describes the API as a unified endpoint for private multimodal inference.
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