Platform | QuanteraAI

01 — The Migration Engine

Scan. Find. Recommend.

Four stages. The first three are live today; the fourth is in active development.

Scan Repository

Upload a .zip of your codebase.

Extraction is hardened against zip-slip path traversal and zip-bomb payloads
Verified against a real path-traversal payload — confirmed it can't escape the workspace directory
A source tree view shows exactly what was scanned

Crypto Findings

Python is analyzed via its AST; Java via the JCA's getInstance() call pattern, which also catches Bouncy Castle.

Coverage: RSA, ECDSA, ECDH, DSA, DH, X25519/X448, Ed25519/448, AES, SHA-256 and above, MD5/SHA-1, and embedded PEM keys and certificates
A summary table plus click-through detail per finding: current algorithm, location, quantum risk, recommendation, and the code snippet itself

Recommendation Engine

Genuinely intent-aware — not a fixed "RSA → ML-KEM, ECC → ML-DSA" lookup table.

Key-establishment usage maps to ML-KEM-768 (FIPS 203)
Signature usage maps to ML-DSA-65 (FIPS 204)
Determined from how each key is actually used in your code, not just its algorithm name

Generate & Verify Migration

Guided code migration and post-migration verification, built on the same findings and recommendations above.

Tabs exist in the product today with honest "coming next" placeholders
No fake interactivity — nothing claims to work until it does

In development

02 — Security & Governance

Built to the Standard We Recommend

QuanteraAI is private-by-default software with real, verifiable controls behind it — not just a scanning tool bolted onto a generic chatbot.

Post-Quantum Encryption at Rest

A fresh AES-256-GCM key per file, wrapped with ML-KEM-768 and bound to metadata signed with ML-DSA-65 — the same primitives we recommend migrating you to.

Data Loss Prevention Gate

Anything routed to an external model is scanned first — SSNs, card numbers (Luhn-validated), IBANs (checksum-validated), bank details, private keys, and API keys are blocked or redacted before they leave.

Output Security Scanner

Every generated answer, local or external, is re-scanned for leaked sensitive data and checked that its citations actually match a retrieved source before it's shown.

Tamper-Evident Audit Chain

Every scan and request writes to a hash-chained log, independently verifiable end to end — designed around the logging and traceability intent of the EU AI Act and NIST AI RMF, without ever logging raw prompt or answer text.

Role-Based Access & Account Lockout

Three enforced roles — user, admin, compliance — server-side authorization on every privileged action, and automatic account lockout after repeated failed logins.

Local-First by Default

Local inference, local vector search, and local analytics run entirely inside your environment. External providers are opt-in and always pass through the DLP gate above.

03 — Why It Matters

Encrypted Today Doesn't Mean Safe Tomorrow

Traffic and archives encrypted with RSA or ECC today can be harvested now and decrypted later, the moment a cryptographically relevant quantum computer exists — an incentive that doesn't wait for that hardware to be built. Migrating is a matter of finding every place classical public-key cryptography is actually used, and replacing it correctly. QuanteraAI is built to do exactly that, engineering-first: real static analysis of your code, not a questionnaire.

04 — Deployment

Runs Inside Your Environment

QuanteraAI runs as a single application on your own infrastructure. Scans, findings, and recommendations stay local unless you explicitly route a request to an external model — and even then, it passes through the DLP gate first. Nothing is proxied through QuanteraAI's own servers by default.

See the architecture in action

Walk through a live deployment with our team.

Request a Demo Contact Sales