AI SECURITY & GUARDRAILS Every package, model and agent is secured and governed before it ships, and stays governed once it’s running. Security Risks Scale Faster Than Teams Can Keep Up Every new model, package and integration expands your attack surface, and most security teams can’t see what’s actually running in production. Agentic AI makes it worse when agents pick their own dependencies and tools. 800K+ Python Packages in the wild, available to developers with no security guardrails. 143K+ Vulnerabilities found over 2 months across 25K MCP servers, affecting 73% of them. 60% of AI Breaches will come from compromised models and datasets by 2029. 350K+ Safety & Security Issues found across 2M+ publicly available AI models. The Cost of an Unvetted AI Every unvetted package, model and agent creates exposure, whether you see it or not. Incident response, breach disclosure and compliance findings all cost more than the secure foundation and validation that would have caught it first. Trust That Extends From Python Packages to AI Agents For more than a decade, Anaconda has helped enterprises build on trusted Python and open source. Today, that trust extends across packages, models, agents and MCPs across the full AI-native development lifecycle from experimentation to production. 50M+ users and 95% of the Fortune 500 run on Anaconda. SOC 2, HIPAA, GDPR, and CCPA compliance support built into the platform’s access and audit layer. new to anaconda Trust Can't Be Added After an AI Agent Ships AI development is getting more agentic. Enkrypt AI brings security validation and guardrails right into your workflow running inside your own environment and tools of your choice. Red-teamed models from Anthropic, OpenAI, Gemini & more Recognized as a Gartner Cool Vendor, 2025 Move AI to Production With Continuous Assurance Every package, model and agent follows a governed path through pre-deployment validation, runtime protection and continuous compliance. Anaconda’s trusted open-source foundation combines with Enkrypt AI’s agent security capabilities to extend trust from development through production. Validate Before It Ships Automated adversarial security testing of AI models and agents before they ship and continuous evaluation after deployment. Pre- and post-deployment security red-teaming across 300+ attack categories. Continuous package and model scanning: Security vulnerabilities, license issues and malicious code caught before production. Constrain What It's Allowed to Do Runtime guardrails constrain agent behavior in real time. MCP governance keeps agents inside approved scope, enforced inside your own environment, never an external provider. Role-based access and SSO across every package, model and environment you use. Real-time monitoring catches drift and anomalies as they happen. Prove It Stayed in Policy Continuous evidence collection for AI regulatory frameworks, not a periodic audit.

Complete audit trail and lineage: every package, environment, model and agent action logged, down to the exact configuration. Automated compliance tracking for the EU AI Act, NIST AI RMF, and SOC 2. Full AI-BOM and SBOM generated automatically. Continuously Govern AI Where It Runs Security validation, guardrails and policy enforcement run inside your environment across clouds, frameworks and models. Compliance becomes an everyday operating control, not a once-a-year audit exercise. From Manual Audit to Enforced Control Continuous vulnerability scanning and usage observability Discover unsafe agent behavior after an incident Red-team models and agents before they ship Hope agents stay in scope Runtime guardrails constrain behavior in real time MCP governance bounds and audits every connection Compliance is a once-a-year scramble Compliance evidence collected automatically, continuously Trust routed through an external provider’s promises Validation runs inside your own environment Security is a gate at the end of the workflow Security is built into every step Keep Every Team Moving Without Losing Control Security Leaders Enforce security and compliance without becoming the bottleneck. Automated evidence maps EU AI Act and NIST AI RMF requirements to continuous controls. AI & Platform Teams Enable innovation without another stack to manage. Give teams consistency, keep developer choice. Ship agents without waiting for manual security reviews. Guardrails operate automatically in the environment where you already build and run. Stay Governed as AI And Regulation Evolve The attack surface keeps expanding while the security and compliance bar continues to rise. New models, connections and regulatory requirements should strengthen existing controls, not create another governance process. Map new frameworks to existing controls without rebuilding your audit program. Give every new model and MCP server the same governed path as those already in production. How Will You Keep Your Next AI Build Trusted? Get the validation, guardrails, monitoring and compliance evidence you need to secure packages, models and agents from development through production. Give builders the freedom to move fast without losing control. 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. AI Security & Guardrails Is Where Trust Gets Proven AI security & guardrails provides continuous assurance across the Anaconda Platform: Build in AI workspaces, validate and protect before and after deployment, then scale with AI orchestration. Packages, models, and agentic development environments to build with. AI Orchestration Get more AI ideas out of experimentation and into production, faster. Start from trusted open-source building blocks, secured and governed for enterprise use.