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Trust at the frontier of agentic AI.

Enkrypt AI is the trust layer for agents, tools, RAG, and MCP—built to find risks before launch, enforce policy in production, and produce audit-ready evidence continuously.

Continuous automated Red Teaming
Real-time Guardrails for actions and data
Evidence-ready Compliance reporting
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Trusted by security teams and AI leaders deploying agentic AI in regulated environments.

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One policy engine at the center of everything.

Enkrypt is built around a unified policy engine that powers testing, enforcement, and evidence generation across your entire AI stack.

Testing

Red teaming and evaluation coverage

Enforcement

Guardrails for outputs and actions (including tools + MCP)

Evidence

Compliance reporting and audit trails

Define policy once. Apply it everywhere—across models, prompts, tools, MCP, and workflows.

Enterprise software dashboard Control panels Dashboard interface

Built for the real ways agents fail in production

Real-world solutions for critical AI deployment challenges

Conversation Agents

Conversation Agents

Keep customer-facing agents safe, compliant, and on-brand. For chat and voice agents that interact with users and can trigger actions.

Block prompt-injection and jailbreak-driven unsafe behavior

Prevent sensitive data leakage (PII/PHI/PCI) in responses and tool calls

Enforce tone, policy, and escalation rules with a consistent audit trail

Outcomes:

Safer conversations • Fewer incidents • Faster approval from security & compliance

MCP

Secure the tool ecosystem—before and after it hits production. For teams adopting MCP servers and tool-based integration patterns.

Scan MCP: discover tools/servers, identify risky capabilities, surface exposures

Gateway MCP: enforce least privilege, validate tool responses, log every action

Detect and block indirect prompt injection and malicious tool outputs

Outcomes:

Controlled tool access • Reduced blast radius • Full traceability for audits

MCP Security
Agents & Workflows

Agents & Workflows

Govern agents that execute multi-step work across systems. For autonomous and semi-autonomous workflows that call tools, retrieve data, and make decisions.

Apply policy checks at every step (inputs, retrievals, actions, outputs)

Stop unsafe actions before execution (approval/modify/block)

Continuously test workflows with automated red teaming and produce evidence

Outcomes:

Reliable automation • Policy-by-default execution • Audit-ready by design

Everything you need to ship agentic AI—without stitching tools together

From a customer's point of view, Enkrypt covers the full lifecycle

Before Production

Automated red teaming finds jailbreaks, data leakage, prompt injection, and tool/workflow abuse

In Production

Guardrails + action controls enforce least privilege and policy in real time

After Production

Evidence-ready compliance reporting supports audits, investigations, and regulators

One system
One set of policies
One evidence trail
AI Security Workspace
AI Security Workspace
AI Security Workspace

Latency

Inline controls designed for production latency.

Agent systems can't tolerate slow security. Enkrypt is built for real-time decisions so teams can govern actions without breaking UX.

Low-latency policy checks

Designed for sub-100ms paths (implementation dependent)

High-throughput optimization

Built for high-throughput tool calls and workflow execution

MCP optimized

Optimized for MCP and action-heavy environments

High-speed server room Server infrastructure Data servers

Multilingual & Multimodal

Governance that works across languages.

AI risk isn't English-only. Enkrypt supports multilingual testing and enforcement so global organizations can apply the same standards everywhere.

Multilingual red teaming coverage

Policy enforcement across languages and locales

Consistent evidence generation for global audits

Global team collaboration International team working together Diverse team collaboration

Built for builders. Ready for security teams.

Start in hours—not quarters. Use Enkrypt SDKs and APIs to test, enforce, and prove policy across agents, tools, and MCP.

What developers get

Policy SDK

Inline evaluation and enforcement

MCP integrations

Scanning + gateway for governed tool traffic

Red Teaming API

CI/CD and pre-release testing

Evidence exports

To your security and compliance stack

Quickstart

pip install enkrypt
enkrypt policy eval \
--policy "pii_exfiltration,unsafe_tool_use" \
--input "$USER_PROMPT" \
--context "$RAG_SNIPPETS"
Developer coding workstation Developer workspace Developer collaboration

Built for regulated environments and security reviews

SSO/SAML, RBAC

Enterprise-grade authentication and authorization

Audit logs + configurable retention

Complete audit trails with flexible retention policies

Encryption in transit and at rest

End-to-end encryption for all data

Deployment options

SaaS, VPC, self-hosted

Security documentation

Available for review

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