Enterprise AI Gateway with Built-In, Responsible AI Guardrails
Kubernetes-native AI Gateway with NVIDIA-powered safety, unified multi-LLM connectivity, and complete infrastructure sovereignty. Deploy with GitOps workflows anywhere—cloud, on-premises, or air-gapped.
TRAEFIK LABS IS TRUSTED BY LEADING ENTERPRISES WORLDWIDE
3 Key Challenges of Deploying AI in the Enterprise
Organizations adopting AI, language models, and autonomous agents to drive innovation face critical challenges:
Breaking Free from Lock-In
Enterprise AI is hampered by multiple layers of lock-in: dual vendor lock-in (LLM + cloud), SaaS incompatibility with air-gapped deployments, complex multi-LLM integration, & limited click-based UIs without support for code-driven operations.
Controlling AI Without Sacrificing Sovereignty
AI deployments face numerous threats—jailbreaks, prompt injection, toxic outputs, PII leaks, policy breaches, data sovereignty compromise. Cloud-based solutions cannot address these without losing data control.
Managing AI Without Visibility or Cost Control
Without unified AI observability, organizations face fragmented monitoring, untracked costs & security threats, exponential spending from uncached API calls, slow responses, & no audit trails to prove responsible AI practices.
Introducing the Traefik AI Gateway
Our AI Gateway delivers the complete enterprise AI infrastructure stack in a single, self-hosted platform. Integrate NVIDIA Safety NIMs for responsible AI, Presidio for PII protection, semantic caching for cost optimization, and unified connectivity to all major LLMs—deployed entirely within your infrastructure through GitOps workflows.
Unlock the Potential of Your AI Endpoints
Experience seamless integration, enhanced security, and comprehensive insights.
Built-In AI Safety & Governance
Effortless Multi-LLM Integration
Intelligent Model Routing
Centralized Security & Credential Management
Semantic Caching & Cost Optimization
Advanced PII Protection & Content Guard
Comprehensive Observability & Insights
1.
Built-In AI Safety & Governance
Jailbreak Detection: Block prompt injection & adversarial attacks before they hit your LLM.
Content Safety: Real-time filtering across 22+ categories (e.g., harmful content, violence, PII violations) for inputs & outputs.
Topic Control: Policy-based guardrails keep conversations compliant & on-topic.
True Data Sovereignty: Safety checks run in your infrastructure. Zero external calls. Full air-gap support.
Extensible: Modular design supports new, emerging safety models. No vendor lock-in.
Kubernetes-Native: Deploy & chain NVIDIA Safety NIMs & manage via GitOps with standard K8s manifests.
2.
Effortless Multi-LLM Integration
Unified API Access: Connect LLMs via a single OpenAI-compatible interface for Anthropic, Azure OpenAI, AWS Bedrock, Cohere, Gemini, Mistral, Ollama, OpenAI, & more.
Simplified Architecture: Eliminate the need for multiple client SDKs & complex integrations.
Easy Switching: Change between LLM providers without modifying client applications.
Vendor Agility: Avoid vendor lock-in & choose the best LLMs for your evolving needs.
Air-Gap Ready: Deploy with self-hosted models in fully disconnected environments.
3.
Intelligent Model Routing
Identity-Based Routing: Route by user, role, or business unit to appropriate models (GPT-4, GPT-3.5, self-hosted, public, etc.).
Time-of-Day Routing: Leverage different models for business hours, off-peak hours, & geography, all with automatic failover to optimize costs & performance.
Flexible Deployments: Utilize canary & blue-green, progressive rollouts, A/B testing, automatic rollback, & zero-downtime upgrades.
Responses API Support: Use the successor to the Chat Completion API with advanced tool support & structured outputs (JSON, etc), enabling unified agentic workflows across providers.
4.
Centralized Security & Credential Management
Centralized Credentials: Manage all LLM API keys in one secure place, hidden from clients.
Consistent Policies: Enforce AuthN, AuthZ, & rate limits uniformly across all LLM traffic.
Unified Governance: Maintain compliance with policies & regulations via GitOps workflows.
Eliminate Shadow IT: Provide secure, managed AI internally to reduce use of external services.
Air-Gapped Deployment: Self-hosted models + Safety NIMs = secure, zero-egress deployments in sovereign & disconnected environments.
5.
Semantic Caching & Cost Optimization
Smart Response Caching: Return cached results instantly based on query meaning, not just exact matches.
40-70% Cost Savings: Dramatically reduce spend on repeated patterns—e.g., support, docs, reports, & analytics.
10-100x Faster: Cut latency & token processing with sub-10ms cached responses vs 3-10s LLM calls.
Enterprise Vector DBs Support: Integrate with Redis, Milvus, Weaviate, & Oracle DB 23ai (coming soon).
Smart Cache Management: Utilize adjustable semantic thresholds, customizable vectorizers & content templates, cache poisoning avoidance mode, & TTL expiration, all with K8s-native & GitOps workflows.
6.
Advanced PII Protection & Content Guard as Code
Superior Detection: Use Natural Language Processing & contextual understanding to significantly boost accuracy vs regex-based or generic PII detection.
Comprehensive PII Coverage: Deploy 35+ global recognizers including SSNs, passports, credit cards, medical IDs, etc.
Flexible Handling: Leverage redaction, de-identification, encryption, & blocking to protect sensitive data.
Custom Rules: Define organization-specific data patterns, including product codes, project names, competitive intel, & more.
Bidirectional Protection: Analyze both inputs & outputs to prevent leaks throughout the entire interaction flow.
Compliance Ready: Meet GDPR, CCPA, HIPAA, PCI-DSS, FERPA, & other regulations.
7.
Comprehensive Observability & Insights
Performance Monitoring: Analyze & optimize LLM request & error rates, latency, & throughput via OpenTelemetry.
Safety Metrics: Track jailbreaks, content violations, topic drift, & PII detection incidents.
Cost Attribution: Analyze token consumption & cost per app, team, model, & use case in real time.
Cache Performance: Monitor & optimize semantic cache hit rates, savings, & latency.
Platform Agnostic: Integrate with any OTel stack, including Grafana, Prometheus, Datadog, New Relic, Elastic, Splunk, etc.
Compliance Reporting: Generate audit trails & compliance reports to demonstrate responsible AI practices.
Why Leading Enterprises Choose Traefik + NVIDIA Safety NIMs
Traefik is the only platform combining AI connectivity with native, infrastructure-level AI governance
Capability
AWS Bedrock
Azure OpenAI
SaaS AI Gateways
Traefik + Safety NIMs
Multi-LLM Support
Limited
Limited
Varies
All Major Providers
Deployment Model
SaaS/Managed
SaaS/Managed
SaaS Only
Self-Hosted
Air-Gap Compatible
-
-
-
Fully Supported
Kubernetes-Native
-
-
-
Cloud-Native
Intelligent Routing
Basic
Basic
Limited
Identity, Time, Canary
Safety Guardrails
Cloud Only
Cloud Only
External Tools
On-Premises NIMs
PII Protection
Proprietary
Proprietary
Varies
OSS-Powered
Data Sovereignty
Requires AWS
Requires AWS
External SaaS
Complete Control
When to Choose Self-Hosted Over SaaS
No External Dependencies
Run in air-gapped environments
GitOps-Driven
Manage everything as code, not click-ops
Kubernetes-Native
Deploy alongside your workloads
Complete Data Sovereignty
No data leaves your infrastructure
No Cloud Calls
NVIDIA Safety NIMs + Presidio run locally
Semantic Caching
Reduce costs by 40-70% without external services
Tracked, Signed Bundles
Full SBOM transparency & container signing verification
Deploy Anywhere
Cloud, hybrid, on-premises, or fully disconnected
What are NVIDIA Safety NIMs and why do they matter for enterprise AI?
NVIDIA Safety NIMs (NVIDIA Inference Microservices) are self-contained, security-validated containers that provide specialized AI safety capabilities—like jailbreak detection, content filtering, and topic control—that run entirely within your infrastructure without external dependencies. They enable responsible AI deployment while maintaining complete data sovereignty.
How does Traefik AI Gateway differ from AWS Bedrock or Azure OpenAI?
Unlike cloud-based platforms that require sending data to their infrastructure for safety checks, Traefik integrates NVIDIA Safety NIMs that run locally within your environment. This provides complete data sovereignty while maintaining enterprise-grade AI governance. Additionally, Traefik supports all major LLM providers through a single API, while AWS and Azure lock you into their ecosystems.
What makes Traefik's PII protection better than basic solutions?
Traefik integrates Presidio, which uses advanced NLP with contextual analysis rather than simple regex patterns. This provides significantly higher accuracy by understanding surrounding context—distinguishing between "President John Smith" and "John Smith, SSN: 123-45-6789." With 35+ predefined recognizers covering global and country-specific PII types, plus the ability to define custom patterns, Presidio offers enterprise-grade protection suitable for regulated industries like healthcare, finance, and government.
Can I use safety models other than NVIDIA Safety NIMs?
Yes. Traefik's modular architecture is designed to be extensible. While we integrate NVIDIA Safety NIMs today because they represent best-in-class safety capabilities, our platform can incorporate emerging safety models as they become available—ensuring you're never locked into a single vendor's solution.
Why is a self-hosted AI Gateway better than SaaS for enterprises?
Enterprise AI deployments often require air-gapped capabilities for classified, regulated, or high-security environments where SaaS solutions cannot operate. Self-hosted gateways like Traefik provide complete data sovereignty, integrate with GitOps workflows for infrastructure-as-code management, and eliminate external dependencies. With self-hosted LLMs (Ollama, Mistral), NVIDIA Safety NIMs, Presidio, and semantic caching all running locally, organizations achieve zero external dependencies suitable for DoD, intelligence agencies, financial trading floors, and critical infrastructure.
How does GitOps integration work with Traefik AI Gateway?
Traefik AI Gateway is Kubernetes-native and fully declarative. Define all configurations—LLM routes, NVIDIA Safety NIM policies, Presidio PII rules, semantic caching settings, rate limits, authentication rules—in YAML manifests stored in Git. Deploy through ArgoCD, FluxCD, or standard CI/CD pipelines. Changes are versioned, peer-reviewed, and auditable—eliminating UI-driven click-ops and ensuring configuration consistency across environments.
How does Traefik handle model versioning and progressive rollouts?
Traefik AI Gateway supports canary deployments and progressive rollouts for model version testing. Start by routing 5% of traffic to a new model (e.g., GPT-4 to GPT-4 Turbo), monitor performance metrics through built-in observability, and gradually increase traffic based on success criteria. Automatic rollback triggers if error rates or latency thresholds are exceeded. All routing rules are defined in Git as code, enabling version control and peer review of model deployment strategies.
Deploy the Most Secure Cloud-Native AI Gateway
Start deploying self-hosted, Kubernetes-native, GitOps-driven AI workloads—with NVIDIA-powered safety NIMs and Presidio PII protection in under 30 minutes.