PQCrypto offers a SaaS platform that provides production‑ready, NIST‑approved post‑quantum cryptography (ML‑KEM, ML‑DSA, SLH‑DSA) as drop‑in replacements for TLS, VPN, backup, and AI workloads.
Funding
Funding not disclosed
Founders
Product
Problem
Current cryptographic standards such as RSA, ECC, and Diffie‑Hellman are vulnerable to future quantum computers, exposing data in transit, at rest, and in AI models to “harvest now, decrypt later” attacks. Organizations lack a clear, enterprise‑grade path to replace these algorithms without extensive re‑engineering.
Solution
PQCrypto delivers a SaaS platform that provides production‑ready, NIST‑approved post‑quantum cryptography (ML‑KEM, ML‑DSA, SLH‑DSA) as drop‑in replacements for TLS, VPN, backup, and AI vector‑database workloads. The service offers hybrid modes that combine classical and quantum‑safe algorithms, enabling seamless migration while preserving compatibility with existing configurations. APIs, SDKs, and pre‑configured AMIs allow rapid integration across cloud and on‑premise environments, and the PQC‑LENS module scans infrastructure to identify legacy cryptography and generate a migration roadmap. Centralized orchestration and automated updates ensure crypto‑agility and compliance with emerging quantum‑security regulations.
Target Audience
Primary customers are large enterprises and cloud service providers in sectors such as finance, healthcare, government, telecommunications, and AI/ML platforms that must protect long‑lived data and meet upcoming quantum‑security regulations.
Features
- Drop‑in replacement libraries for TLS, VPN, and backup that require no architectural changes
- Hybrid PQC mode supporting simultaneous classical and post‑quantum key exchange for backward compatibility
- SaaS APIs, SDKs, and pre‑built AWS AMIs for one‑click deployment of quantum‑safe servers and services
- PQC‑LENS vulnerability discovery platform that inventories RSA/ECC usage across applications, APIs, certificates, IoT devices, and AI vector databases
- Automated risk scoring, migration roadmaps, and compliance reporting to meet regulatory mandates
- Performance‑optimized implementations of ML‑KEM, ML‑DSA, and SLH‑DSA validated for enterprise‑scale workloads