Harmonic Security Platform

Intercepts prompts and completions to prevent sensitive data (PII, credentials, internal IP), from being transmitted to external LLM services or returned in model responses.

Records prompts, completions, and metadata for all AI interactions with tamper-resistant storage, supporting compliance, forensics, and policy investigation.

Discovers, governs and allowlists the Model Context Protocol servers and tools that AI agents are permitted to invoke.

Secures AI coding assistants and their Model Context Protocol connections against unsafe actions, data exposure and supply-chain risks.

Enforces IAM-style policies on LLM API access, controlling which users and applications can invoke which models and data sources, with audit logging.

Discovers and categorizes the organization's use of third-party AI, whether consumed as a service, installed locally, or embedded inside other applications, building a continuously updated inventory of AI usage including shadow AI.

Assesses and scores the risk of discovered AI services and embedded AI features (data handling, training-use terms, hosting, vendor posture) to drive sanction/block decisions.

Defines organizational AI usage policies and enforces them at the point of use - allowing, blocking, redirecting, or constraining specific AI services, models, and features per user, group, or data context.

Inspects prompts, uploads, and AI-generated responses for sensitive data across modalities, preventing exposure of regulated or proprietary information to third-party AI services.

Enforces AI usage controls through multiple local inspection points - browser, endpoint, and network - coordinated from a cloud-delivered control plane, so coverage does not depend on a single interception path.