Your customers don’t just want visibility
they want confidence in how their data is handled.
they want confidence in how their data is handled.
Enforce multi-party trust policy, verify trust conditions at execution, support human approval when needed and produce evidence your customers can independently verify.
Built for AI-first and cloud-native platforms that handle sensitive data and need customers to trust, approve and adopt higher-value use cases faster.
Policy driven runtime assurance
Sensitive AI and cloud workloads increasingly run beyond the customer’s direct visibility. Logs and audits can explain activity after the fact, but they rarely provide tamper-resistant proof of how data was handled during execution.
Veritas provides a verifiable execution layer: confidential compute, runtime policy enforcement, cryptographic evidence, and human approval checkpoints where accountability matters.
So your customers do not have to rely on trust alone. They can verify how their data was handled and move faster with confidence.
Verification layer panel
Verifiedworkload
aml-risk-scoring-v3environment
confidential-spacetrust policy
data-use conditions ✅approval
required / approved ✅trust checks
identity • runtime • policyevidence
runtime proof generated ✅Proof customers can verify
Your customers can verify how their data was handled, under which conditions and with whose approval.
Trust friction reduced
Reduce trust friction with evidence customers can inspect instead of another assurance they have to interpret.
From trust to proof
Modern AI and cloud-native systems increasingly ask customers to share sensitive data, approve automated decisions and trust distributed execution. Most platforms still explain that trust with logs, screenshots and post-hoc audits. That is not enough when customers want to know how their data was actually used.
Veritas adds the missing verification layer: trust policies are enforced, trust conditions are verified at execution, human approval can intervene and runtime evidence is generated for customer verification.
assertion.swname
== "CONFIDENTIAL_SPACE"
Trust policies can be checked at execution, including workload identity, runtime integrity, environment placement, approval state and data-use constraints.
That gives your customers more than a narrative: it gives them evidence that data was used under the agreed conditions.
Veritas enables
Before data use
Define the trust conditions for data use: who is acting, what is running, where it runs, which policy applies and whether approval is required.
During execution
Enforce multi-party trust policy at execution and pause for human approval or operator intervention when conditions require it.
After execution
Generate runtime evidence your customers, auditors and regulators can independently verify.
How policy becomes proof
Trust policy checks
assertion.swname == "CONFIDENTIAL_SPACE"
"STABLE" in assertion.submods.confidential_space.support_attributes
assertion.submods.gce.zone == "us-central1-a"
size(assertion.submods.container.env_override) == 0
assertion.hwmodel == "GCP_AMD_SEV"
Runtime evidence
Confidential Space image
Matched
Support attribute
STABLE
Workload zone
us-central1-a
Container overrides
None detected
Confidential hardware
GCP_AMD_SEV
Outcome
Trust conditions matched: data use approved and evidence generated.
Strategic shift
Observability → Attestation
Observability explains system activity. Veritas helps your customers verify that data was used under the right conditions.
Trust → Verification
Customers do not have to rely only on claims. They can inspect runtime evidence generated when execution occurred.
Cost-center → Revenue-generator
Trust becomes easier to evaluate, helping security reviews, procurement and sensitive customer adoption move with less friction.
Trust conditions Veritas can verify
Verify Confidential Space image type and support attributes.
Validate image digest, signatures and runtime configuration.
Detect env and command overrides before execution.
Verify service accounts and workload identity.
Restrict zone, project and instance configuration.
Confirm confidential compute platform (AMD SEV / TDX).
Proof over promises
Your customers can’t verify trust from claims alone.
Today, trust is still built from documents, dashboards, and explanations. Veritas helps your platform turn agreed data-use conditions into runtime evidence customers can verify.
OLD MODEL
Requires interpretation and trust
VERITAS
Runtime verification layer
OUTCOME
Proof customers can inspect
Digital transformation should not force customers to choose between innovation, privacy and control.
Veritas helps your platform make data use enforceable at execution and verifiable afterward.
Use cases
Trust-condition verification capabilities mapped to buyer problems.
The tags are not decorative. They show which kind of runtime assertion or verification capability makes the use case defensible.
Enterprise security reviews
Give customer security teams evidence they can inspect instead of only questionnaires, screenshots or control narratives.
Sensitive AI workflows
Support AI workflows where customers need confidence before sharing regulated, financial, identity, health or confidential data.
Data sovereignty and external data boundaries
Show that sensitive processing happened in an approved project, zone, runtime and policy boundary before data is released.
Human-approved execution
Require a data owner, operator or authorized reviewer to approve a sensitive action before execution or release continues.
Verifiable Execution moves from policy to proof.
Veritas makes the trust sequence visible: define the policy, verify runtime conditions, pause for people when needed and produce Evidence the customer can inspect.
Package
01
Enforce
Enforce multi-party trust policy
Define how data can be used, who can act, which workload is allowed and when Approval is required.
Policy constraints are established before Verifiable Execution begins.
02
Verify
Verify trust conditions at execution
Check identity, runtime, environment, policy and Approval requirements before sensitive data is used.
Runtime conditions are checked where risk actually happens.
03
Intervene
Intervene through Approval
Pause or continue execution when a data owner, Operator or authorized reviewer must approve a sensitive action.
Human judgment becomes an explicit checkpoint, not an afterthought.
04
Prove
Prove execution with Evidence
Generate Evidence at execution that shows what ran, where it ran, which conditions were met and how data was handled.
Evidence becomes something your customer can inspect and verify.
How the verification layer works
Your platform enforces multi-party trust policy, verifies trust conditions at execution, supports Approval when needed and produces Evidence your customers can independently verify.
Veritas sits inside the trust boundary
Veritas connects operators, workload authors, data collaborators, auditors, cloud services, tenant environments and enterprise trust consumers.
The point is not another dashboard. The point is governed execution that turns runtime policy, confidential execution and Attestation into Evidence another party can verify before they approve, buy, audit or expand usage.
Rendering diagram…
Policy and execution happen inside the Veritas trust boundary.
Evidence travels outward to people who need confidence before they approve, buy, audit or expand usage.
Customers, auditors and reviewers can inspect Evidence instead of relying only on internal assurance.
Trust fit
Get the right trust configuration without guessing.
The full Trust Fit assessment now lives on its own page so the homepage stays focused. Use it to map workload sensitivity, proof audience, runtime model, approval requirements, and data-control assumptions to the right Veritas configuration.
Configuration effort map
Recommended default
MediumTenant-dedicated governed session
Best balance for enterprise buyers who need stronger proof without per-job orchestration.
Fastest pilot
LowShared Veritas-managed runtime
Best for proving the business value quickly with lower-sensitivity design-partner workloads.
Highest assurance
HighPer-execution ephemeral runtime
Best when each governed execution needs its own short-lived runtime and evidence path.
Strongest data-owner control
HighCustomer-held key / external data boundary
Best when the customer or data owner must control release outside the Veritas boundary.
Is Veritas a fit for your platform?
You handle sensitive customer data
Strong fit
You need approval before sensitive actions
Strong fit
Security reviews slow adoption
Strong fit
You only need internal dashboards
Probably not yet
Multiple parties need trust
Strong fit
You do not handle sensitive data
Probably not yet
Why verification is becoming
a business requirement.
Across security, compliance, AI adoption and procurement, buyers increasingly expect evidence they can evaluate to verify the assurances they are being asked to trust.
Review friction
0 days
lost to manual evidence gathering
Across security review and procurement, teams lose time translating controls into proof buyers can actually evaluate.
Source: Veritas modelled buyer-review workflow
AI governance
0%
concern level in the latest period
Governance pressure is becoming a buying condition as AI systems move closer to sensitive customer workflows.
Source: Deloitte cited planning stat
Third-party risk
0%
involvement in the latest period
As more value chains depend on vendors and cloud services, trust increasingly needs to travel across organizational boundaries.
Source: Verizon DBIR cited planning stat
Figures are directional market indicators from cited industry research and public summaries. They do not guarantee specific outcomes for any individual customer, deployment or sales process.
Pricing aligned to assurance not compute
Foundation
Growth
Enterprise
Pricing reflects assurance, governance and trust acceleration.
Frequently asked questions
- What is a workload in Veritas?
- A workload is the code your team wants to run on sensitive data, typically packaged as a container, job, pipeline or AI execution flow. Veritas governs how that workload executes and produces cryptographic evidence of the conditions under which it ran.
- Do we need to rewrite our applications?
- No. The goal is to bring existing workloads into a verifiable execution model with minimal architectural change, not force a full application rewrite.
- How is this different from observability?
- Observability explains what happened using logs, metrics and traces. Veritas proves what happened correctly by enforcing policy during execution and generating portable attestation evidence.
- Is this a compliance product?
- Not primarily. Veritas is a trust and governance layer for AI and cloud workloads. It supports audits, procurement reviews and defensible compliance evidence, but it is not just another compliance workflow tool.
- Who is this for?
- Security leaders, platform engineering teams, AI infrastructure companies and cloud-native businesses that need stronger proof of how sensitive workloads handle data.
- Can this help us close enterprise deals faster?
- Yes. One of the core outcomes is reducing security review friction by replacing claims, screenshots and interpretation with machine-checkable evidence.
- What does the evidence artifact actually show?
- It can show the workload identity, environment integrity, approval state, policy-constrained execution conditions and the cryptographic attestation material needed to verify those claims.
- Can our customers independently verify the proof?
- That is the point. Veritas is designed to make trust portable, so customers, auditors and regulators can verify how sensitive execution occurred instead of relying solely on internal assurances.
Still evaluating fit?
Book a demo or contact sales for a proof walkthrough and buyer-fit conversation.
Enable AI-ready trust
Give your platform
the verification layer customers expect.
Enforce multi-party trust policy, verify trust conditions at execution, support human approval and produce runtime evidence your customers can independently verify.