AI data leak prevention that keeps useful work moving.
Give teams a local control before company data reaches supported AI tools. Start with visibility, then warn, redact, or block the data categories that matter to your business.
Book a 20-minute callA normal workday
A teammate pastes a client update into ChatGPT to turn it into a faster reply.
G.A.I.N. checks the content locally at the point of use. The policy can preserve the useful request while removing configured identifiers, or stop the highest-risk data before it is shared.
Policy response
Client data rule
Configured sensitive values are replaced locally before the remaining safe request continues to the supported AI tool.
How it works
A policy needs a real control behind it.
See the real exposure first
Begin in observation mode to identify the supported AI tools and data categories your teams actually use.
Set a policy that matches the work
Choose the category, action, supported tool scope, and department scope instead of applying one blanket rule to everyone.
Review evidence, not prompt content
The dashboard records the tool, category, policy action, and time so managers can prove the control ran without collecting prompts.
Policy actions
Choose the response that fits the risk.
Pause for a deliberate check
Ask the person to review a risky paste when the work may still be appropriate with a safer version.
Remove values, retain context
Replace configured values locally so the AI request can continue without exposing the original data.
Stop data that should not leave
Prevent configured high-risk categories from being sent through the supported workflow.
A practical answer when a client asks how AI use is controlled.
G.A.I.N. shows which supported AI tool was used, the data category, and the policy action. The original prompt content stays on the device.
- Tool
- ChatGPT
- Category
- Client data
- Action
- Redact
- Prompt content
- Not stored
Where this applies
- Supported browser AI tools, including ChatGPT, Claude, Gemini, Microsoft Copilot, and Perplexity.
- Configured local coding workflows where the G.A.I.N. Agent is installed.
- Policy actions scoped by category, supported tool, and department.
What it does not claim to do
- It is not a general network DLP product and does not claim to inspect every website or application.
- Desktop protection is assistive foreground clipboard coverage, not desktop app network interception.
- Prompt content is not sent to the dashboard by default.
Questions
Before you put a policy into production.
Can we begin without blocking anyone?
Yes. Teams can begin with log-only or warning policies, review the observed categories, and choose stronger controls after they understand their normal workflows.
Does redaction mean the dashboard receives the original value?
No. Redaction is performed locally. The dashboard receives metadata about the category and action, not the original prompt content.
Does G.A.I.N. replace a DLP or a secrets manager?
No. It adds a control at the moment people use supported AI tools. Existing identity, endpoint, DLP, and secrets-management controls still matter.
See the policy on your real workflow.
In 20 minutes, we can map the AI tools your team uses and show the policy actions that fit them.
Book a 20-minute call