Insurance organizations operate on uniquely sensitive, high-value data: policyholder records, actuarial models, underwriting methodologies, reinsurance structures, claims documentation, litigation strategy, and proprietary risk scoring logic.
The exposure is not limited to PII. It includes aggregated case files, internal risk models, pricing strategy, and confidential carrier relationships.
Traditional tools detect fragments of data. They do not understand insurance-specific context.
The Outcome with Bold
Bold prevents customer data leakage from high-access teams, protects engineering IP, and enables secure AI adoption at enterprise scale. For companies built on trust, that control is foundational.
1. Professional Services and Support Teams
These teams access live customer environments, export logs, and handle tenant data daily.
Risk: Customer production data is exported locally for debugging and can be copied, uploaded, or stored without centralized visibility.
Why Bold is uniquely positioned
On-device AI classification distinguishes customer tenant data from internal content in real time
Prevention happens at the moment of export, copy, upload, or transfer across any application
Behavioral baselining detects abnormal cross-tenant access or unusual export volume
Control extends beyond browser into local files, desktop apps, screenshots, and AI tools
2. Engineering and Intellectual Property Protection
Core enterprise value lives in distributed code, architecture, models, and roadmap materials.
Risk: Engineers can intentionally or accidentally move proprietary IP into personal tools, AI assistants, or unmanaged storage.
Why Bold is uniquely positioned
On-device classification identifies proprietary code, model artifacts, and technical documentation without static rules
Real-time controls govern copy, paste, upload, and transfer across both browser and non-browser channels
Role-based behavioral baselining highlights abnormal bulk access or movement of sensitive assets
No customer content leaves the device for analysis, preserving engineering trust and privacy
3. AI Governance Without Disrupting Innovation
AI adoption is business-critical across engineering, product, and business teams.
Detects sensitive data before it is submitted to AI tools
Context-aware coaching guides users in real time rather than defaulting to hard blocking (with an over 90% successful redirection rate)
Policies can differentiate customer data, proprietary IP, and lower-risk content
Visibility spans sanctioned and unsanctioned AI tools across the endpoint
Bold enables secure AI usage at scale instead of attempting to prohibit it.
4. Personal Versus Corporate Boundary Control
Enterprise endpoints are oftentimes dual-use environments.
Precise distinction between corporate and personal accounts and destinations
Real-time prevention of sensitive uploads to personal email and storage
Governance across copy, paste, screenshots, and local file sharing
Visibility into sensitive files stored locally that increase accidental exposure risk
Bold closes the gap most organizations cannot see, where personal context intersects with corporate data.
