Enkrypt ai by Anaconda
Ship AI Faster and Safer
One product, one policy engine, built for agents that change faster than manual reviews can keep up. Enkrypt brings red teaming, runtime guardrails, and audit-ready evidence into one product and policy engine — from development through production.
200+
Leading Foundation Models Tested
50,000+
Dynamic Red-Teaming Evaluations Per Model
90%
Reduction in Time to Certify and Ship
Enkrypt AI recognized as a Gartner® Cool Vendor in AI Security, 2025.
Agents Change Faster Than Reviews Can Keep Up
You can't say today what your agents can reach, what's in their training data, or what your MCP servers expose. That leaves your business and customers exposed.
The Risks Red Teaming Uncovers
- Access control: Prompt injection, jailbreaking
- Privacy: Data leakage, Model inversion
- Tool misuse: Unmonitored agent actions, adversarial attacks
- Output quality: Hallucinations, bias, Toxicity, model drift
- Reliability: Explainability gaps, drip attacks
- Agent behavior: Deceptions, misuse
- Governance: Policy violations, compliance failures, brand damage
The Cost of Finding Out Too Late
Evidence assembled the week before an audit costs more than evidence collected as you go. By the time someone’s checking, the exposure has already been live for months.
A scan of 25,000 MCP servers uncovered 143,000 vulnerabilities across 268,000 tools. 73% of the servers were affected. Nobody running them knew until someone looked.
Independent Research Validates AI Security Leadership
Recognition
by Accenture, InfoSec, Cyber Security, RSA, and IntellyX.
Research
Reports covering CBRN, Gemini Models, Red Teaming Cloud Providers AI Guardrails, AI21, Mistral, and DeepSeek Safety Report
Taxonomy
Agent Risk Taxonomy with 6 categories, 300 subtypes
Responsibility
Shared responsibility framework defining provider, deployer, and user roles.
By integrating Enkrypt AI’s generative AI risk capabilities and advanced guardrails, we’ve significantly strengthened our CASB offerings — empowering customers with real-time visibility and control over AI-driven LLM focused risks.
Thyaga Vasudevan
EVP, Product, Skyhigh
Enkrypt AI has the unique ability to detect and remove data layer risks in AI deployments. And they do it with extremely high precision.
Arunkumar Gururanjan
VP, Data Science, NetApp
Securing AI agents is uniquely challenging. Enkrypt AI ensures every interaction is safe, secure, and compliant — safeguarding our brand, data, and customers at every touchpoint.
Arunkumar Gururanjan
VP, Data Science, NetApp
Not All Models are Created Equal
The industry’s first LLM Safety Leaderboard: benchmarking 200+ models with continuous red teaming, not a one-off test. Choose the best model with confidence and move fast without risking your brand.
200+ models • 4 risk scores, including NIST and OWASP • 24×7 real-time data
One Policy Engine Secures the Full AI Lifecycle
Red teaming hardens agents in development. Guardrails hold the line in production. Compliance turns both into evidence — all governed by one policy.
DETECT
Pinpoint Hidden Risks
Continuously challenge AI agents with use-case-specific attacks that adapt in real time, uncovering risk far beyond what static testing catches.
- Agent Red Teaming: uncovers prompt injection, jailbreaks, data leakage and behavioral weaknesses that static testing misses before attackers or users find them.
- MCP Scanner: identifies vulnerabilities before connection.
REMOVE
Stop Threats and Clean Risk Before It Ships
Protect agents at runtime and remove unsafe data before deployment.
- Agent Guardrails: real-time guardrails stop prompt injection, jailbreaks, and data leakage as it happens, and get smarter with every prompt.
- AI Data Risk Audit: scans training data, fine-tunes, and embeddings for hidden or malicious content, then clears it before anything ships.
MONITOR
Gain Insight as You Iterate
See how agents behave across prompts, tools and workflows in production.
- MCP Gateway: routes every interaction through one governed endpoint with centralized policy enforcement, access control and visibility
COMPLY
Stay Ahead of Emerging Regulation
Translate internal policies and external regulations into automated, enforceable controls.
- Agent Policy Engine: detects violations and risk early, applies guardrails consistently, and creates audit-ready evidence across the AI lifecycle, with mappings to frameworks including the EU AI Act and NIST.
Security Becomes an Accelerator, Not a Gate
- Certify and ship 90% faster: Automated security testing and compliance workflows remove manual review bottlenecks without lowering standards.
- Turn policy into protection: Translate evolving policies and regulations into enforceable controls, then produce the evidence required to prove compliance.
- Stay ahead of emerging threats: Continuously monitor production AI for new attacks, policy drift and risky behavior before they damage customers or reputation.
Consolidate AI Security Without Sacrificing Coverage
Six Products, One Policy Engine
Govern red teaming, runtime guardrails, data risk, compliance, and MCP security through one policy — not disconnected tools.
Research-Backed Expertise
Original taxonomies, safety reports and responsibility frameworks inform the product, supported by 10+ free Academy courses, live Q&A and certification.
Deployed in Your Environment
Keep prompts, model calls and customer data inside your security boundary.
From Fragmented Controls to Continuous Risk Assurance
Before Enkrypt AI
|
With Enkrypt AI
Security review happens on a schedule; agents change continuously
→
Guardrails enforce policy the moment a request is made
A different vendor for red-teaming, guardrails, and compliance evidence
→
One policy engine secures the full AI lifecycle
Third-party and MCP risk goes uninventoried
→
MCP Scanner and Gateway inventory and govern every connection
Training data and fine-tune risk ships unaudited
→
AI Data Risk Audit catches it before deployment
Certifying and shipping takes weeks
→
Certify and ship up to 90% faster
Model choice restricted to control risk
→
Broad model choice, still bound by policy
Built for AI Teams and Governed for Those Accountable
Security & Compliance
Provable, exportable controls mapped to the frameworks your auditors already ask about. Continuous evidence instead of alert triage.
Builders & AI Engineers
Guardrails and red teaming sit inside the workflow you already use. Hardening an agent doesn’t mean rewriting it, or waiting on a review queue.
Product & IT
One endpoint for every MCP server, self-service access with policy attached, usage and risk visible in one view — without becoming the ticket queue for every access question.
Customer Facing
Safe agents in production, with the same guardrails and monitoring applied to every customer-facing interaction.
Research That Keeps Pace with Attacks that Don’t Stand Still
The attack surface keeps growing, and the regulatory floor keeps rising: the EU AI Act became active August 2, 2026, with NIST and industry frameworks layering on top.
- Continuous red teaming adapts to new attack patterns dynamically, not a static test suite that ages out.
- The LLM Safety Leaderboard refreshes in real time, 24×7 with new frontier models scored as they ship.
- Original research including the Agent Risk Taxonomy, Shared Responsibility framework, model-specific safety reports keeps the product ahead of the threat landscape it protects against, not behind it.
Secure and Govern the Full Agent Lifecycle
Area
What it covers
Products
Solutions
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Enkrypt AI is Part of Anaconda
How it works:
Complete the form, and we’ll reach out within 1 business day to discuss your requirements. Then, we’ll build a demo that addresses your real challenges.
Enkrypt AI Frequently Asked Questions
Will guardrails slow our developers down?
No. Red teaming and guardrails sit inside the workflow your builders already use. Hardening an agent doesn’t mean rewriting it or waiting on a review queue. Policy is enforced in the runtime, not requested through a ticket.
Does our data leave our environment?
No. Red teaming, runtime guardrails, and evidence collection all run inside your own environment. Prompts, customer data, and model calls stay inside your walls.
We already have a security review process. What changes?
Your review happens on a schedule. Agents change continuously. Guardrails enforce your policy the moment a request is made, and evidence collects on its own between reviews.
Which frameworks are covered?
The EU AI Act (active August 2, 2026), NIST AI RMF, and SOC 2. Controls map to the framework language your auditors already use.
Do we have to restrict which models our teams use?
No. Broad model choice, still bound by policy — teams select from a wide catalog while the policy engine governs what any of those models is permitted to do.
We are an existing Enkrypt AI customer. What happens to our account?
Existing Enkrypt AI products, plans, and support continue unchanged.