Prem

Use Case 1: Secure Regulatory Compliance for Financial Institutions

Problem: Financial firms and RegTech companies must analyze massive volumes of sensitive client data and regulatory updates daily. However, using public AI tools risks leaking "Inside Information" or violating strict data residency laws (like GDPR or FADP), as most AI providers log queries and store data for training.

Solution: Prem provides an "amnesiac" architecture where data exists only in encrypted memory during inference. Its Swiss-based hosting ensures data stays outside the jurisdiction of global surveillance alliances, allowing firms to automate compliance without compromising data sovereignty.

Example: A European bank uses Prem App to connect its internal legal documents and transaction logs. The AI agent identifies potential compliance risks across thousands of pages of new regulations, providing a hardware-signed attestation (cryptographic proof) that the data was processed securely and never stored or logged.

Use Case 2: Privacy-First Clinical Support in Healthcare

Problem: Healthcare providers need AI to summarize patient histories and clinical notes to reduce administrative burnout. However, uploading Protected Health Information (PHI) to a cloud-based LLM is a major security risk and often violates healthcare privacy regulations due to data retention policies.

Solution: Using Prem API, developers can build healthcare applications with "Zero Data Retention." Because Prem utilizes hardware-verified encryption and stateless processing, patient data is processed in real-time and immediately wiped from the system after the inference is delivered.

Example: A hospital integrates the Prem API into their Electronic Health Record (EHR) system. When a doctor requests a summary of a patient's complex 10-year medical history, the data is encrypted, processed by a high-performance open-source model, and the summary is returned in under 300ms. Prem leaves no digital footprint of the patient's records.

Use Case 3: Protecting Intellectual Property during Custom Model Fine-Tuning

Problem: Enterprise companies want to build specialized AI models trained on their proprietary "secret sauce"—such as internal codebases, unique manufacturing processes, or private research. They fear that using standard fine-tuning services will result in their trade secrets becoming part of a provider's base model.

Solution: Prem Studio allows businesses to turn proprietary data into a competitive advantage while maintaining "Sovereign Weights." This means the company owns the resulting model weights entirely, and the fine-tuning process happens within a secure perimeter where the AI provider cannot access the training data.

Example: A specialized engineering firm uses Prem Studio to fine-tune a model on 20 years of proprietary blueprints and technical manuals. The result is a custom "expert" AI that understands their specific engineering language, deployed on dedicated GPUs where the firm retains 100% ownership of the intelligence.

Use Case 4: Confidential Document Analysis for Legal and M&A Teams

Problem: During Mergers and Acquisitions (M&A), legal teams must review highly confidential contracts, patents, and financial statements. Using standard AI tools for this "due diligence" is prohibited because the leak of a potential deal or trade secret could lead to massive financial and legal repercussions.

Solution: Prem App functions as a "Confidential AI Workspace." It allows legal teams to analyze sensitive documents "off the grid." With end-to-end (E2E) encryption and universal connectors, teams can securely link their private document repositories to a private AI environment.

Example: A legal team creates a secure workspace in Prem App for a sensitive acquisition. They upload thousands of confidential contracts to identify "change of control" clauses. The AI provides a deep strategy analysis, but because of Prem’s Post-Quantum Encryption, the firm is confident that even future computing power cannot crack the secrecy of the deal data.