Cryptographic trust for AI & cloud native workflows
Proof, not promises.
We provide a verifiable execution layer that produces cryptographic proof that AI systems and cloud workloads handled sensitive data correctly.
Can you prove it?
AI-driven systems and cloud-native applications process sensitive data across distributed environments, but lack reliable ways to prove how that data was handled at execution.
We help you prove to your customers and stakeholders that their data was handled correctly so they can verify it, trust it and adopt cutting-edge, AI solutions for sensitive use cases faster.
Enterprise security reviews
Shorten enterprise security reviews
For example, a customer approves where a workload can run. Veritas checks that condition at execution and produces evidence the customer can independently verify during their security review.
Veritas platform overview
Cryptographic trust for AI & cloud native workflows
It is designed for high-assurance AI and cloud workflows where sensitive data, customer approval, runtime integrity and confidentiality all have to be proven without exposing the very details the trust model is meant to protect.
This overview shows how Veritas connects the people, policies, runtime checks, approval points and evidence artifacts needed to prove sensitive execution.
Hover or focus any persona, capability, workflow step, input, output, approval control or business outcome to explore how trust conditions become proof.
Tap a labeled area to see what it does.
Runtime enforcement
Policy decision + execution result
Confidential runtime
Attestation + runtime identity
Approval checkpoints
Approver, reason, and decision state
Evidence artifacts
Receipt, verification result, and proof bundle
Customer verification
Reviewable report tied to the execution