About
Enkrypt AI is an enterprise-grade AI security platform purpose-built for the agentic AI era. It provides end-to-end protection across the full AI lifecycle — from pre-deployment red teaming to real-time runtime guardrails, continuous monitoring, and automated compliance reporting. The platform's Agent Red Teaming capability continuously stress-tests AI systems with dynamic, use-case-specific adversarial attacks, uncovering security, safety, and brand risks that static testing misses. Agent Guardrails intercept threats at inference time, getting smarter with every prompt to keep AI safe and under control. The Agent Policy Engine translates internal policies and external regulations (e.g., EU AI Act, NIST AI RMF) into automated guardrails with auditable evidence. For data security, the AI Data Risk Audit detects and removes hidden risks in the data layer of AI deployments with high precision. The newly launched MCP Scanner and MCP Gateway extend protection to Model Context Protocol servers, addressing vulnerabilities in agentic tool usage. Enkrypt AI is designed for security teams, AI architects, and compliance officers at large enterprises operating in regulated industries. It claims to reduce time-to-certify and ship AI by 90% by automating security and compliance workflows. Customers include organizations on Salesforce.com, Skyhigh Security, NetApp, and Phot.AI.
Key Features
- Agent Red Teaming: Continuously stress-tests AI agents with dynamic, use-case-specific adversarial attacks that adapt in real time, uncovering security, safety, and brand risks beyond static testing.
- Real-Time Agent Guardrails: Intercepts and neutralizes threats at inference time, learning from every prompt to provide continuously improving protection for LLM-powered applications.
- Agent Policy Engine: Translates internal policies and external AI regulations (EU AI Act, NIST, etc.) into automated guardrails with auditable compliance evidence for regulators and auditors.
- AI Data Risk Audit: Detects and removes hidden data-layer risks in AI deployments with high precision, addressing PII leakage, poisoning, and other data vulnerabilities.
- MCP Scanner & Gateway: Scans Model Context Protocol (MCP) servers for vulnerabilities and secures agentic tool interactions, protecting against prompt injection and misuse of external tools.
Use Cases
- Securing customer-facing AI chatbots and virtual assistants against prompt injection, jailbreaks, and unsafe outputs before and after deployment.
- Red teaming LLM applications and agentic workflows to identify security and brand risks prior to production release.
- Automating AI compliance reporting and evidence generation for audits against frameworks like the EU AI Act or NIST AI RMF.
- Protecting multimodal AI pipelines (text and image generation) in ad-tech and e-commerce from adversarial attacks and policy violations.
- Scanning and securing MCP servers used by AI agents to prevent tool misuse, data leakage, and unauthorized actions.
Pros
- End-to-End AI Lifecycle Coverage: Covers red teaming, runtime guardrails, monitoring, and compliance in a single platform, eliminating the need for multiple point solutions.
- Gartner-Recognized & Enterprise-Trusted: Named a Gartner Cool Vendor in AI Security 2025 and used by enterprises at Salesforce, NetApp, and Skyhigh Security, signaling strong credibility.
- Accelerates Compliance & Certification: Claims to reduce time-to-certify and ship AI applications by 90% through automated security and compliance workflows.
- Adaptive Threat Intelligence: Guardrails and red teaming capabilities continuously improve with new prompts and emerging threat patterns, staying ahead of novel attack vectors.
Cons
- Enterprise-Only Pricing: No self-serve free tier or transparent public pricing; onboarding requires scheduling a demo, making it inaccessible for smaller teams or individual developers.
- Implementation Complexity: The breadth of features — red teaming, guardrails, policy engine, MCP security — may require significant setup time and dedicated security expertise to fully operationalize.
- Limited Public Documentation: As an enterprise sales-driven product, detailed technical documentation and self-service resources may be limited compared to open-source alternatives.
Frequently Asked Questions
What is Enkrypt AI?
Enkrypt AI is a purpose-built AI security and compliance platform that helps enterprises detect threats, enforce policies, and maintain continuous compliance across LLM and agentic AI deployments.
What is Agent Red Teaming and how does it work?
Agent Red Teaming automatically attacks your AI system with dynamic, use-case-specific adversarial prompts that adapt in real time. It continuously uncovers security vulnerabilities, safety gaps, and brand risks that manual or static testing would miss.
What compliance regulations does Enkrypt AI support?
Enkrypt AI helps organizations comply with major AI regulations and frameworks including the EU AI Act, NIST AI RMF, and industry-specific standards in finance, insurance, and life sciences by automating policy-to-guardrail translation and generating audit evidence.
What is the MCP Scanner?
The MCP Scanner is a newly launched tool that scans Model Context Protocol (MCP) servers for security vulnerabilities, helping organizations secure agentic AI systems that rely on external tools and APIs.
Who is Enkrypt AI designed for?
Enkrypt AI is designed for enterprises — specifically AI architects, security teams, and compliance officers — building and deploying production AI applications in regulated industries like finance, insurance, life sciences, and technology.
