Automate the Hardest Part of Cryptographic Modernization
Knowing where cryptography exists is only the beginning.
The next challenge is changing it—across millions of lines of code, complex dependencies, legacy implementations, performance-sensitive workloads, and systems that cannot simply be rewritten.
Our AI-assisted migration platform connects cryptographic discovery with automated modernization workflows, helping engineering and security teams move from CBOM findings to actionable migration changes.
Let AI Find the Path Forward
Use AI-assisted analysis to understand cryptographic implementations, identify migration candidates, recommend modernization paths, and accelerate the engineering work required to adopt post-quantum cryptography.
The platform can help teams:
- Identify migration candidates
Prioritize cryptographic implementations that require modernization. - Understand dependencies
Trace the impact of changing cryptographic algorithms or libraries across applications and components. - Generate migration guidance
Translate inventory findings into implementation-level recommendations. - Assist code transformation
Use trained models to accelerate repetitive migration and refactoring tasks. - Validate the resulting changes
Connect migration workflows back to inventory and cryptographic verification.
GPU-Accelerated PQC With NVIDIA cuPQC
For performance-sensitive post-quantum workloads, the platform can integrate with NVIDIA cuPQC, NVIDIA's GPU-accelerated cryptographic SDK. cuPQC provides device-side cryptographic libraries that can be integrated directly into CUDA kernels and includes post-quantum capabilities such as ML-KEM and ML-DSA.
This enables a migration strategy designed around both quantum resilience and high-performance computing.
CUDA-Ready Migration Workflows
Modern cryptographic workloads increasingly need to operate at scale. Our migration workflow is designed to identify opportunities where CUDA acceleration can be paired with cryptographic modernization.
Move beyond:
Inventory → Ticket → Manual Rewrite → Repeat
Toward:
Discover → Analyze → Generate → Accelerate → Validate
AI assists the engineering workflow while keeping cryptographic changes connected to the underlying asset inventory.
Models Trained for Migration Work
Generic AI models are not enough for cryptographic modernization.
Our approach uses CUDA-trained models and domain-specific intelligence to assist with the patterns, code structures, dependencies, and transformations associated with GPU-accelerated cryptographic workloads.
The goal is simple:
Reduce the engineering effort required to move from legacy cryptography to modern, high-performance implementations.
Migrate With Context, Not Guesswork
Every cryptographic change can have downstream consequences.
Our migration workflows can connect code-level recommendations with CBOM context, helping teams understand:
- Which components are affected
- Which applications depend on them
- Which cryptographic algorithms are being replaced
- Where compatibility constraints exist
- Where performance optimization matters
- What changed during migration
- What should be re-scanned after implementation
Built for the Post-Quantum Transition
Post-quantum migration is not a single library upgrade.
It is an enterprise engineering program involving discovery, prioritization, architecture, code changes, testing, validation, deployment, and ongoing inventory management.
Our platform brings those activities together in one workflow.
Inventory tells you what you have.
AI helps determine what to change.
CUDA and cuPQC help accelerate what comes next.
Make Migration a Repeatable Engineering Process
Turn cryptographic modernization from a manual, fragmented effort into an intelligent workflow that can operate across large software estates.