How Teambridg Handles Data Security: A Technical Deep Dive

Security by Architecture, Not by Policy

In workforce monitoring, security isn't just about protecting data from external threats — it's about ensuring that the data collected is the minimum necessary and that access is strictly controlled. Our security architecture is designed so that even if every policy were violated, the technical architecture would prevent privacy breaches.

This article is for security teams evaluating Teambridg and for customers who want to understand how their data is protected. We'll cover every layer, from the endpoint agent to our cloud infrastructure.

Layer 1: Endpoint Security

The Teambridg endpoint agent runs on employee workstations and is the first line of both data collection and data protection.

Local processing: Raw activity data (application focus events, idle/active states, keystroke velocity) is processed on the employee's device. Only aggregated signals leave the device — never raw events. This means that even intercepting the data in transit reveals nothing about specific activities.

Signal computation: The agent computes signals locally using a deterministic algorithm: focus time blocks, break patterns, application category time, work-hour boundaries. These signals are one-way derivatives — you cannot reconstruct raw activity from the computed signals.

Encryption in transit: Signals are transmitted to Teambridg servers over TLS 1.3 with certificate pinning. The agent validates the server certificate against a pinned hash, preventing man-in-the-middle attacks even on compromised networks.

Minimal footprint: The agent uses less than 2% CPU and 50MB RAM. It has no access to file contents, email/chat content, browser history, or microphone/camera. Its system permissions are limited to process enumeration and window title access (for application categorization only).

Layer 2: Cloud Infrastructure

Teambridg's cloud infrastructure follows zero-trust principles:

• Network segmentation: Customer data is stored in isolated environments. No cross-customer data access is possible at the network level.
• Encryption at rest: All data is encrypted with AES-256 using customer-specific encryption keys managed through AWS KMS. We cannot read customer data without the customer's key.
• Access controls: Internal access to customer data requires multi-party approval, is logged immutably, and is restricted to specific incident response scenarios. No Teambridg employee has routine access to customer data.
• Data retention: Signals are retained for 90 days by default (configurable per customer). After retention expiry, data is securely deleted using cryptographic erasure — the encryption keys are destroyed, rendering the data irrecoverable.

Layer 3: Application Security

Beyond infrastructure, our application layer implements defense-in-depth:

• Role-based access control (RBAC): Managers see only their team's data. Department heads see aggregated department data. Employees see only their own data. The AI Insights Engine enforces the same RBAC — you can't use natural language queries to access data outside your permissions.
• SSO integration: Enterprise customers use their existing identity provider (Okta, Azure AD, Google Workspace) for authentication. We never store passwords for SSO customers.
• Audit logging: Every data access, configuration change, and report generation is logged with timestamp, user identity, and action details. Audit logs are immutable and retained for one year.
• Penetration testing: We conduct annual third-party penetration tests and continuous automated security scanning. Results are available to enterprise customers under NDA.

Security is never finished — it's a continuous process. If you're a security professional evaluating Teambridg, we welcome your questions. Reach out to our security team at security@teambridg.com or review our security documentation page.