About This Agent
Aurascape is an AI governance and security platform engineered to provide continuous visibility, control, and protection over enterprise AI adoption. Its core architecture integrates automatic and embedded AI discovery engines that inventory all AI applications, agents, and models across the organization, including shadow AI. Real-time risk scoring and deep intention decoders analyze user and agent behavior to identify malicious or non-compliant intent, while real-time policy enforcement and entitlement enforcement ensure that every AI interaction adheres to corporate and regulatory standards. The platform extends to agentic AI control, managing autonomous agents with granular permissions and audit trails. Sensitive data fingerprinting and AI-driven data protection prevent data exfiltration by detecting and redacting personally identifiable information (PII), intellectual property, and other critical assets in real time. AI-driven threat prevention stops prompt injection, data poisoning, and other AI-specific attacks. Aurascape eliminates the operational pain of unmanaged AI sprawl, compliance audit failures, and data leakage. It delivers measurable gains by reducing incident response time by up to 80% and cutting compliance reporting effort by 50%. Use cases span regulated industries such as healthcare (HIPAA), finance (GLBA), and legal, as well as technology enterprises deploying copilots and autonomous agents.
Agent Capabilities
- Automatic AI Discovery: Continuously identifies all AI applications, models, and agents across cloud, on-premises, and edge environments without requiring agents.
- Embedded AI Discovery: SDK and API-based detection within custom applications and internal tools to map AI usage at the code level.
- Real-time Risk Scoring: Dynamically assigns risk scores to AI interactions based on data sensitivity, user context, and behavioral anomalies.
- Deep Intention Decoders: Uses transformer-based models to interpret the underlying intent of prompts and actions, distinguishing benign from malicious requests.
- Real-time Policy Enforcement: Enforces granular policies on AI usage, blocking or flagging actions that violate compliance or security rules.
- Agentic AI Control: Manages autonomous AI agents with identity, permissions, and activity monitoring to prevent unauthorized actions.
- Entitlement Enforcement: Ensures users and agents only access AI capabilities and data for which they are authorized, reducing over-privileged access.
- Sensitive Data Fingerprinting: Identifies and tracks structured and unstructured sensitive data across AI interactions, including PII, PHI, and financial records.
- Real-time AI-Driven Data Protection: Applies adaptive redaction, masking, or encryption to sensitive data before it reaches AI models or external services.
- AI-Driven Threat Prevention: Detects and mitigates prompt injection, model extraction, and data poisoning attacks using behavioral analytics and anomaly detection.
Primary Workflows & Use Cases
- Healthcare compliance: Monitor and secure AI-assisted clinical documentation and diagnostic tools to ensure HIPAA compliance and prevent PHI leakage.
- Financial services governance: Enforce real-time policies on AI chatbots and trading algorithms to meet SEC and FINRA record-keeping requirements.
- Enterprise copilot security: Control access and data flow for Microsoft 365 Copilot and other productivity assistants to prevent IP exfiltration.
- DevSecOps pipeline protection: Scan AI-generated code and automated testing agents for malicious patterns and sensitive data exposure before deployment.
- Customer support triage: Deploy AI agents for customer care while ensuring they only access approved knowledge bases and never expose private customer records.
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