Advanced Research
&
Intelligence Systems

We work at the intersection of quantum-safe cybersecurity, digital forensics and quantitative genomics. Typical engagements include hardening critical systems against future quantum attacks, recovering digital and on-chain assets, and designing genomic selection programs that combine AI, statistics and secure data architectures.

Most roadmaps place cryptographically relevant quantum computers in the 2030–2035 window. The real risk, however, is “harvest now, decrypt later”: adversaries can store encrypted traffic today and break it once quantum machines arrive. That’s why we focus on phased migration to quantum-resistant cryptography for long-lived and high-value data.

Genomic datasets are treated as high-sensitivity assets. We combine strong encryption (at rest, in transit and, when required, via homomorphic or secure multi-party computation), strict access controls, privacy-by-design modeling and detailed audit trails. Architectures can be deployed on-prem, in private cloud or in secure research environments depending on regulatory constraints.

Modern post-quantum algorithms and genomic pipelines are designed to be practical. There is overhead compared to legacy cryptography or simple statistics, but with proper engineering (hardware acceleration, batching, caching and model optimization) we keep security and genomics workloads within the performance envelopes required by production systems and research labs.

We usually start with a focused assessment or discovery workshop to map threats, data assets and research goals. From there we design a small, high-impact pilot: a quantum-safe migration plan, a forensic playbook, or a genomic analytics proof of concept. Successful pilots then evolve into long-term research partnerships with shared roadmaps, publications and technology transfer.