Private. Verifiable. Intelligence.
A zero-knowledge compute pipeline for building private, verifiable AI systems.
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Zero-Knowledge Proof of Training
Prove a model was trained on private data without revealing the data itself.
Training
Evaluation
Verify
The ZK compute pipeline
End-to-end flow for private verifiable compute
01
Encrypt
Secure your data before upload.
02
Upload
Store encrypted data to your workspace.
03
Compute
Run private model training and inference.
04
Verify
Cryptographically verify outputs.
Privacy Paradigm
- Private by default — data never leaves control of the owner.
- Proven compute — auditable proofs of correctness.
- Minimal exposure — reduce attack surfaces.
Deep Tech Stack
Verifiable Computation
Zero-Knowledge Ecosystem
Developer Tooling
Enterprise Security
Universal model support · integrations · audits
Data Minimization
Only required derivatives are used.
Verifiable Outputs
Cryptographic proofs with each result.
Regulatory Compliance
Designed for enterprise compliance needs.
Why Zyntra?
| Feature | Zyntra | Traditional |
|---|---|---|
| Data Control | Owner-controlled | Shared |
| Verifiability | Built-in proofs | Not available |
| Integration | SDK & APIs | Limited |
Enterprise-grade Security & Compliance
Hardware enclaves, audits, and verifiable logs.
ZKFT
uptime · proofs · attestations
System Evolution
Q4 2023
Alpha release & small tests
Q2 2024
Beta improvements
Q3 2024
Enterprise features
Q4 2024
Governance tooling