Aseryx provides a cryptographic data appraisal service that evaluates the value of datasets for AI builders without ever moving the raw data out of the owner’s infrastructure. The two‑layer appraisal scores provenance and richness on‑premises, ensuring compliance with GDPR, HIPAA, and the EU AI Act while allowing owners to monetize access under zero‑custody conditions.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations that hold valuable datasets often cannot monetize them because sharing raw data violates privacy regulations and exposes them to custody risks. Additionally, AI developers lack reliable, verifiable information about data quality, leading to mistrust and inefficient transactions.
Solution
Aseryx offers a two‑layer cryptographic data appraisal that runs entirely within the data owner's infrastructure, producing mathematically verified provenance and richness scores. These scores are shared with AI builders, enabling them to assess dataset value without ever receiving the raw data. The approach maintains full control and compliance with GDPR, HIPAA, and the EU AI Act while allowing data owners to monetize access through transparent, auditable agreements.
Target Audience
Primary customers are enterprises and institutions that own sensitive, high‑value datasets—such as healthcare providers, genomic research groups, financial firms, and industrial operators—who need to monetize data while remaining compliant and retaining control.
Features
- In‑environment cryptographic appraisal that never transmits raw data, ensuring zero custody transfer
- Provenance verification and information‑richness scoring using secure, mathematical proofs
- Compatibility with regulated sectors (genomics, healthcare, finance) and adherence to GDPR, HIPAA, and EU AI Act requirements
- API for AI developers to query verified scores and negotiate access without data exposure
- Auditable revenue distribution model that directs 80‑85% of monetization proceeds to the data holder
- Support for a wide range of use cases, including fraud detection, predictive maintenance, high‑frequency trading, and cost‑engine modeling