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
72%
Evaluation
34%
Verify
84%

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.

Compute Monitor

  • Active jobs: 18
  • Pending proofs: 3
  • Last run: 2h ago
View console

Deep Tech Stack

Verifiable Computation
Zero-Knowledge Ecosystem
Developer Tooling
Enterprise Security

Universal model support · integrations · audits

Real World Use Cases

Secure private training for sensitive datasets.

Learn more

Zyntra Ecosystem

Tools for builders and enterprises.

Learn more

Data Minimization

Only required derivatives are used.

Verifiable Outputs

Cryptographic proofs with each result.

Regulatory Compliance

Designed for enterprise compliance needs.

Why Zyntra?

FeatureZyntraTraditional
Data ControlOwner-controlledShared
VerifiabilityBuilt-in proofsNot available
IntegrationSDK & APIsLimited

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

Stop trusting. Start verifying.