Unleash AI solution
Confidential AI for Enterprise Finance and Forecasting
Forecast with confidence and compliance
Table of Contents
Enable secure AI-driven financial forecasting and planning by keeping sensitive data encrypted in use.
Why it matters
Finance leaders want to apply AI to accelerate forecasting, variance analysis, and scenario modeling yet pre-earnings data, budgets, and strategic plans are too sensitive to expose in standard AI environments. Any accidental data leak or insider access before quarterly results could trigger regulatory, market, or reputational consequences. Today’s AI platforms don’t offer cryptographic proof that financial data stays protected during processing or model execution.
How it works
Fortanix creates a secure, attested runtime where financial models and sensitive data stay encrypted and accessible only to verified workloads.
- Trusted: CPU/GPU to ensure only trusted code runs.
- Secure Key Release: Keys issued only to verified workloads; no key = no access.
- Confidential LLM Execution: Enables AI forecasting and audits without exposing internal data.
- Compliant by Design: FIPS 140-2 Level 3 controls and audit logging meet SOX, SEC, GDPR
Business outcomes
- Zero Data Leak Risk: Sensitive financial data and forecasts never leave the verified enclave.
- Accelerated Insights: Run real-time AI forecasting securely — reducing close-cycle times.
- Audit-Ready Confidence: Immutable logs provide end-to-end transparency for regulators and auditors.
- Operational Efficiency: AI-powered automation within a trusted, compliant boundary.
Partner ecosystem
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Changelog
- Rev.1: Initial release
© Copyright 2026 Hewlett Packard Enterprise Development LP. The information contained herein is subject to change without notice. The only warranties for Hewlett Packard Enterprise products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. Hewlett Packard Enterprise shall not be liable for technical or editorial errors or omissions contained herein.
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