Proprietary AI.
Nothing leaves.
Zavior runs its own AI and ML stack inside your deployment boundary, with redaction and AI safety built in. It is not a thin wrapper that forwards your documents to a public model you never contracted.
The posture security review wants to see.
Typical AI feature
infrastructure you never contracted · terms you never reviewed
Zavior
what runs is ours · where it runs is yours
Zavior's own AI stack
Most AI features in enterprise software are wrappers. The product takes your document, forwards it to a third-party model over an API, and hopes the terms of service hold. Your compliance data becomes prompt payload on infrastructure you never contracted, under retention and training policies you never reviewed.
Zavior's AI and ML are proprietary, built for compliance work and shipped inside the platform. There is no consumer chat product in the loop and no silent dependency on someone else's model endpoint. What runs is ours; where it runs is yours.
Ask your current vendors one question: when our document is processed by your AI feature, whose infrastructure executes the model? The answer decides whether your compliance data has quietly left your contract.
As written
Incident reported by Tan Wei Ming, NRIC S1234567A, contact [email protected]
What the model sees
Incident reported by [NAME], NRIC [ID], contact [EMAIL]
masked before indexing · minimisation by construction
Redaction at ingestion
The accepted discipline for handling personal data is to strip what you do not need before you process it. GDPR codifies it as data minimisation; PDPA frames it through purpose limitation. Most AI products apply it after the fact, if at all.
Zavior applies it in the ingestion path. Personally identifiable information can be masked before a document is indexed for retrieval, so minimisation happens before the model ever sees the content, not as a cleanup afterwards.
For a DPO this changes the risk assessment. The AI feature stops being a new personal-data processing surface to justify and becomes one that minimises by construction.
as shipped · day one
nothing to configure before it is safe
AI safety ships with it
Guardrails bolted on after go-live are guardrails tuned under deadline pressure. Zavior ships AI safety controls with the product.
Regulated teams start from a safe configuration instead of inventing one mid-rollout, and the guardrails travel with every deployment model.
It also means safety behaviour is consistent: tested by the vendor once, not improvised by every buyer separately under their own deadline.
retrieval scope: this corpus only
application-layer boundary
Organisation isolation
AI context and document corpora are isolated per organisation, enforced at the application layer like every other tenant boundary in the platform.
One tenant's corpus never becomes another tenant's context, and a model answering your question retrieves from your documents only.
The guarantee matters most in shared modes. Shared infrastructure never means shared context; your questions are answered from your documents and nobody else's.
Zavior gives you the flexibility. Your deployment decides, not the product.
Sandboxed or air-gapped. Your call.
Zavior gives you the choice. Run the sandboxed AI service that ships already deployed with the platform, isolated to your organisation and ready on day one. Or air-gap the whole stack, where nothing calls home at all.
The sandbox path gets you working immediately with the boundary controls intact: redaction, isolation and safety all still apply. The air-gapped path is for restricted environments, where an AI feature that needs the internet is an AI feature you have to turn off.
Either way the posture is deliberate, documented and yours to choose. Flexibility is the point: your deployment decides the plumbing, not the product.
one architecture diagram, true in every deployment
Controls, not bolt-ons
Redaction and AI safety arrive as deploy-ready controls in every deployment model, from managed cloud to restricted environments.
Security review sees the same posture wherever you run it, which is what keeps the architecture conversation short.
Buyers can put the same architecture diagram in front of every reviewer, in every jurisdiction, and have it be true everywhere.
Where does the prompt go?
Enterprise buyers have learned to ask a blunt question about AI: where does the prompt go? If the answer is a consumer chat product nobody contracted, the deal stalls in security review.
Zavior's answer is designed for that review. The AI stack runs inside your deployment boundary, redaction sits in the ingestion path before content is indexed, safety controls ship in the box, and organisation isolation applies to AI context the same way it applies to everything else. That is the posture security and legal teams want on the page before they schedule the deeper architecture conversation.
Where does the model see our data?
Inside your deployment. Nowhere else.
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