Executive Summary

Enterprises across BFSI, insurance, healthcare, retail, and public sector are rapidly adopting Large Language Models (LLMs) and AI-driven automation. However, running AI in production introduces new challenges:

NGINX Plus provides a unified, enterprise-grade gateway that enables organizations to deploy AI workloads safely, efficiently, and at scale — whether running on-premises, in cloud GPU environments, or hybrid.

This whitepaper outlines how NGINX Plus delivers the performance, reliability, governance, and security necessary for enterprise AI systems.

AI Adoption Challenges in Enterprises

1. Multiple LLMs and Fragmented APIs

   Enterprises often use combinations of OpenAI, Anthropic, Azure OpenAI, local open-source models, and vendor-provided models — each with incompatible interfaces.

2. Inference Latency & GPU Overload

   LLM response time varies dramatically depending on:

   • model size
   • GPU temperature
   • batch load
   • memory fragmentation

   This unpredictability directly impacts business SLAs.

3. Cost Explosion from Uncontrolled AI Usage

   LLM calls are significantly more expensive than traditional APIs. A poorly written application can cause runaway GPU usage.

4. Security and Compliance Concerns

   AI endpoints often process:

   • personal data
   • financial records
   • medical documents
   • proprietary content

   Which makes enterprise security mandatory.

5. Lack of Observability

   Most AI systems lack operational visibility into:

   • latency per model
   • throughput
   • failure rates
   • anomalies

NGINX Plus: The AI Gateway for Enterprise-Grade Deployments

NGINX Plus brings together powerful capabilities across:

These capabilities enable enterprises to confidently deploy AI services in production.

10 Essential AI Gateway Use Cases Enabled by NGINX Plus

1. Unified AI Gateway
   • Eliminates complexity for application developers.
   • Future-proofs AI investments.
2. Cost Governance with Rate Limiting

   Prevent uncontrolled costs by enforcing:

   • per-user limits
   • per-team quotas
   • per-model throttling

   Protects GPU infrastructure and budgets.

3. High Availability & Failover

   NGINX Plus automatically:

   • tests LLM endpoints
   • detects failures
   • reroutes traffic to healthy nodes

   Ensures uninterrupted AI-powered applications.

4. Smart Multi-Model Routing

   Send requests to the model that is:

   • fastest
   • cheapest
   • most accurate
   • domain-specific

   Maximizes performance and cost efficiency.

5. Streaming Output Proxy

   Modern AI apps rely on token streaming.

   NGINX Plus provides smooth, uninterrupted streaming to end users.

6. Enterprise Security for AI Endpoints
   • JWT / OAuth2 validation
   • mTLS
   • API firewalling
   • Payload size protection
   • NGINX App Protect WAF

   Prevents unauthorized or malicious AI usage.

7. On-Prem GPU Inference Gateway

   NGINX Plus intelligently distributes traffic across GPU servers running:

   • open-source LLMs
   • vendor LLMs
   • custom fine-tuned models
8. Document & Media Pipeline Normalization

   AI pipelines often require:

   • OCR
   • image analysis
   • document extraction

   NGINX Plus + NJS transforms and normalizes API calls.

9. Multi-Tenant AI Platform

   Centrally manage AI access for:

   • various business units
   • partner systems
   • internal tools

   With per-tenant quotas and routing.

10. Full Observability & Compliance

    NGINX Plus provides:

    • latency metrics
    • real-time dashboards
    • upstream health
    • audit logs

    Essential for regulated industries like BFSI, insurance, and healthcare.

Conclusion

Enterprises adopting AI need more than model endpoints — they need governance, reliability, security, and operational stability. NGINX Plus provides the AI gateway architecture that modern organizations require for mission-critical AI workloads.

If your organization plans to deploy AI at scale, NGINX Plus is the foundation on which to build a secure, future-proof AI platform.