Enkrypt ai by Anaconda
Ship AI Faster and Safer
Red teaming, runtime guardrails, audit-ready evidence. One policy engine.
200+
Leading foundation models tested
50K+
Dynamic red-teaming evaluations per model
90%
Reduction in time to certify and ship
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.
You Can't See What Agents Do
Prompt injection, jailbreaks, data leakage, and unmonitored tool use hide inside agents and MCP connections that a point-in-time review never inspects.
You Find Out too Late
By the time someone checks, the exposure has been live for months. Evidence scraped together the week before an audit costs far more than evidence collected as you go.
You Juggle Too Many Tools
One vendor for red teaming, another for guardrails, a third for compliance evidence. Nothing shares a policy, MCP risk goes uninventoried, and certifying takes weeks.
25K
MCP servers scanned over two months
143K
vulnerabilities found across 268K tools
73%
of the servers scanned were affected
We've Seen What Periodic Assessments Miss
Reviews on a calendar can’t keep pace with agents that change daily. We know: we scanned 25,000 MCP servers in two months and found 143,000+ vulnerabilities across 268,000+ tools. 73% were affected.
Risks Uncovered With Enkrypt
- 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
Enkrypt AI recognized as a Gartner® Cool Vendor in AI Security, 2025.
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.
AI Architect, Salesforce.com
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 of it governed by one policy, so security becomes an accelerator instead of a gate.
Pinpoint hidden risks before anyone else does
Red teaming hardens agents in development. Guardrails hold the line in production. Compliance turns both into evidence. All of it governed by one policy, so security becomes an accelerator instead of a gate.
Stop threats live and clean risk before it ships
Real-time guardrails stop prompt injection, jailbreaks, and data leakage as it happens, and learn from each prompt. Audit training data, fine-tunes, and embeddings for hidden or malicious content, then clear it before deployment.
Turn policy into protection, and proof
Translate internal policies and external regulations into enforceable controls. The Agent Policy Engine catches violations early, applies guardrails consistently, and generates audit-ready evidence mapped to the EU AI Act and NIST AI RMF.
See It on One of Your Own Agents
You don't need to rip anything out to see what Enkrypt AI catches. Bring one production agent and watch it get tested against your own policy, in your own environment.
Step 1
Step 2
Watch it get red-teamed against your business context and responsible AI policy. See exactly what it finds and which guardrails would have stopped it.
Step 3
Turn on guardrails and the policy engine in your own environment. Evidence starts collecting on its own, between reviews, from day one.
The Industry's First LLM Safety Leaderboard
Benchmarking 200+ models with 24×7 real-time data, and four risk scores including NIST and OWASP. Choose the best model with confidence, and move fast without risking your brand.
Security Becomes an Accelerator, Not a Gate
The audit arrives and the evidence is already there. Your teams keep shipping. You can say what each agent can reach.
Certify and ship 90% faster
Automated security testing and compliance workflows remove manual review bottlenecks without lowering standards. Broad model choice, still bound by your policy.
Prove compliance as you go
Evolving policies and regulations become enforceable controls the moment a request is made. The evidence to prove compliance is produced as you go, not the week before.
Stay ahead of emerging threats
Monitor production AI for new attacks, policy drift, and risky behavior before they reach customers or your reputation. Original research keeps the tests current.
BEFORE & AFTER WITH ENKRYPT AI
From Fragmented Controls to Continuous Risk Assurance
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
Exposure Doesn't Wait for Your Next Review
Each week agents run unreviewed is risk nobody has measured, and evidence you’ll pay more to rebuild later. Bring one production agent. See what red teaming finds, what guardrails stop, and what audit-ready evidence looks like.
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. Teams select from a wide catalog while the policy engine governs what any of those models is permitted to do. Broad model choice, still bound by policy.
We are an existing Enkrypt AI customer. What happens to our account?
Enkrypt is now part of Anaconda’s AI Security & Guardrails. Existing Enkrypt AI products, plans, and support continue unchanged.
Where can I learn more about the independent research Enkrypt has done?
Click on the links here to see original research including the Agent Risk Taxonomy, Shared Responsibility Framework, and reports covering CBRN, Gemini Models, Red Teaming Cloud Providers AI Guardrails, AI21, Mistral, plus the DeepSeek Safety Report.