Bold Security offers an AI‑native endpoint agent that classifies data, monitors user behavior, and enforces context‑aware policies directly on each device. The lightweight agent automatically discovers sensitive assets, maps data lineage, and blocks risky actions in real time, consolidating DLP, insider‑risk, and application‑monitoring functions for enterprise security teams.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises struggle to detect and prevent user‑initiated risks such as insider threats, data exfiltration, and unsafe AI tool usage because legacy endpoint solutions provide limited visibility, require extensive policy tuning, and generate high volumes of noisy alerts.
Solution
Bold Security delivers an AI‑native endpoint agent that runs directly on each device, enabling real‑time classification of data, monitoring of user behavior, and context‑aware enforcement without relying on cloud round‑trips. The agent automatically discovers sensitive assets, maps data lineage, and intervenes at the moment a risky action is attempted, turning the endpoint into an active security control rather than a passive data source. Configuration is self‑learning; the platform auto‑generates policies based on observed usage patterns, allowing security teams to supervise rather than manually author rules. All processing occurs locally, preserving privacy and reducing latency, while encrypted forensic logs are stored centrally for post‑incident analysis. This approach consolidates DLP, insider‑risk, and application‑monitoring functions into a single lightweight runtime, delivering clearer signals and faster investigations.
Target Audience
The primary customers are enterprise security operations teams in regulated industries—financial services, insurance, healthcare, and enterprise software firms—that manage large, distributed endpoint fleets and need to protect sensitive data and AI‑driven workflows.
Features
- Lightweight AI security agent (≈10× smaller than traditional agents) installed on every endpoint, with zero‑touch deployment.
- Real‑time data sensitivity classification using on‑device large‑language models, supporting out‑of‑the‑box content types (code, IP, PHI, regulated documents).
- Continuous user‑behavior analytics that build baseline activity profiles and detect deviations with sub‑second latency.
- Contextual policy engine that combines data type, user intent, application, and destination risk to automatically block or remediate actions.
- Automatic data lineage mapping across endpoints and cloud destinations, providing end‑to‑end visibility of data flows.
- Integrated forensic audit trail that captures raw events, transformation steps, and remediation actions for compliance reporting.
- Seamless API hooks for SIEM, SOAR, and EDR platforms, enabling enriched alert enrichment and automated response workflows.