Gravitee vs. Enkrypt AI

Gravitee is an enterprise AI agent management, API management, and event management platform that centralizes governance across agents, models, APIs, tools, and data streams. Its AI Gateway sits between AI applications and enterprise systems to provide a single enforcement point for model access, MCP tools, and agent-to-agent interactions. The LLM Proxy gives organizations one front door to multiple model providers, while the MCP Proxy controls how agents access tools and the A2A Proxy secures communication between agent systems. Gravitee can issue, verify, and revoke identities for AI agents and apply least-privilege policies to determine which systems and services each agent may access. Security controls can include authentication, authorization, PII redaction, rate limiting, spend caps, key protection, and detailed logging of prompts and agent activity. The platform also provides visibility into AI traffic, model usage, token costs, agent dependencies, and behavior so teams can identify shadow AI and uncontrolled integrations. Cost and risk controls help organizations manage token consumption, monitor spend, and reduce the operational impact of unreliable or overactive agents. Gravitee extends the same management approach to REST APIs, GraphQL, gRPC, Kafka, and other enterprise API and event technologies. Internal APIs, event streams, MCP tools, and workflows can be exposed as governed products for developers, partners, applications, and AI agents. This unified approach allows enterprises to manage conventional integration infrastructure and newer agentic workloads without maintaining completely separate governance systems. Gravitee is designed for enterprises, security teams, API platform teams, AI engineering organizations, and regulated businesses that need centralized control over AI agents, model traffic, APIs, and event-driven systems.

Enkrypt AI is an agentic AI security and compliance platform that helps enterprises identify, mitigate, monitor, and govern risks associated with AI models, applications, agents, and supporting infrastructure. The platform is designed to cover AI security threats and compliance requirements across different models and modalities while allowing organizations to continuously evaluate AI systems as they evolve. Its dynamic red teaming capabilities generate use-case-specific attacks that adapt in real time to uncover security, safety, compliance, and brand risks beyond those identified through static testing. Enkrypt AI can test for threats including prompt injection, jailbreaking, data leakage, model inversion, adversarial attacks, drip attacks, unsafe actuation, policy violations, and misuse by end users. It also evaluates AI quality and safety risks such as hallucinations, model drift, bias and discrimination, toxic content, deceptive behavior, misleading outputs, lack of explainability, and brand misalignment. Real-time guardrails detect and stop risky interactions as they occur while adapting to new prompts, behaviors, and emerging threats. Continuous monitoring gives security and compliance teams visibility into AI risks, protection effectiveness, and areas requiring action as models and applications change. Enkrypt AI's compliance functionality converts internal policies and external regulatory requirements into automated guardrails and generates evidence that can support audits and compliance programs. The product portfolio includes Agent Red Teaming, Agent Guardrails, an Agent Policy Engine, AI Data Risk Audit, MCP Scanner, and MCP Gateway for protecting AI agents, their data, and their connections to tools and infrastructure. Enkrypt AI supports use cases including customer-facing AI agents, frontier models, AI compliance and auditing, third-party AI risk, secure AI development, data risk assessment, and MCP security.