Operant AI

Detects and blocks adversarial inputs designed to override system prompts, extract training data, or redirect model behavior. Detection approaches include pattern matching, input semantic analysis, and secondary model classification.

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

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

Evaluates model outputs against content policy, data classification rules, and format expectations before delivery to end users, blocking responses containing sensitive data or policy violations.

Discovers the AI models, agents, MCP servers and AI-enabled applications in use across the organization, including those deployed without IT authorization, and keeps them in an inventory that records type, ownership and criticality. Discovery runs through traffic inspection and code repository scanning at minimum; some products add cloud provider, application server or AI engineering tool integrations. The inventory anchors exposure management and risk scoring.

Detects sensitive or regulated data in AI training, fine-tuning, or third-party LLM flows without appropriate controls, such as unencrypted PII in inputs or PHI sent to external APIs.

Scans the configuration of AI model and inference endpoints, and of the MCP servers and tool endpoints that agents call, and flags public exposure, weak or missing authentication, default credentials and excessive permissions as posture findings. Findings come from configuration and passive scanning rather than inline traffic inspection, which belongs to runtime defense. Products differ in the endpoint types covered and in whether findings carry a severity score.

Maps data lineage and provenance across AI training and inference pipelines, tracing how PII, PHI, and IP move into models and external services.

Defends live APIs against exploits, abuse, access violations and denial-of-service attacks using AI-driven anomaly detection, content inspection and traffic management. Delivered by dedicated API threat protection tools, API gateways or a WAAP platform.

Continuously discovers and inventories all APIs across the environment, including shadow and zombie APIs that are not tracked in the official catalog.

Identifies APIs that transmit or return sensitive data such as personal information, credentials, or tokens, so exposure can be flagged and controlled.