Banking & fintech
Bring AI into banking without exposing customer data
Privacy Gateway masks identities, account numbers, and transaction details before prompts reach the model.
Banking teams need speed without data exposure
From support and onboarding to risk analysis, banking workflows move faster when AI helps. They also carry customer data, transaction context, and regulated information that should not leave the environment raw.
A gateway before the model
We classify the request, redact sensitive values, and route high-risk prompts through policy before the model sees them.
Banking control flow
How the gateway keeps banking prompts safe
The workflow is designed to preserve meaning while limiting exposure and keeping every action auditable.
Classify the request
Detect whether the prompt contains account data, KYC context, payment details, or internal notes.
Mask sensitive values
Replace names, account numbers, and amounts with stable placeholders when the exact value is not needed.
Apply policy rules
Block, route, or approve the request based on role, use case, and data class.
Audit the flow
Keep a record of what was allowed through so security and compliance can review it later.
What banking teams get
Redaction by default
Sensitive customer and account details are removed before the prompt reaches the model.
Policy-based control
Different rules can apply to onboarding, support, fraud, and internal banking workflows.
Full traceability
Every prompt can be audited without exposing the raw information to everyone who touches the workflow.
Fits existing systems
The gateway connects to your current tools instead of forcing a new stack.
Best-fit banking workflows
Related industry pages
Use AI in banking with stronger data controls
If your team wants to move faster without exposing sensitive customer information, we can help design the control layer.