A review of the top AI gateways for observability, caching, and management when building generative AI applications with Vercel and Next.js. This post covers options like Bifrost, LiteLLM, and Cloudflare AI Gateway, ranking Bifrost as the top choice for its performance and enterprise-grade features.
The Vercel AI SDK has made it dramatically simpler for developers to build streaming, conversational user interfaces in Next.js. By providing a unified API for interacting with large language models (LLMs), it handles the complexities of streaming responses and managing UI state. However, as applications scale and move to production, managing the underlying LLM infrastructure presents a new set of challenges: cost control, latency, provider outages, and observability. This is where an AI gateway becomes an essential part of the modern AI stack.
An AI gateway is a proxy server that sits between an application and one or more LLM providers. It centralizes request routing, authentication, and logging, giving engineering teams a single control plane for their AI traffic. For a Next.js application using the Vercel AI SDK, a gateway can add critical features like automatic provider failover, semantic caching, and detailed request observability without requiring significant code changes.
This article reviews the seven best AI gateways that integrate with the Vercel AI SDK and Next.js, enabling developers to build more robust, scalable, and cost-effective AI applications.
Key Criteria for Evaluation
When selecting an AI gateway for a Vercel-based project, several factors are critical:
- Performance: How much latency does the gateway add to each request?
- Observability: What level of detail is available for monitoring requests, costs, and errors?
- Reliability: Does it support automatic failover and load balancing across multiple providers or keys?
- Caching: Does it offer semantic caching to reduce costs and latency on repeated queries?
- Ease of Integration: How simple is it to integrate with the Vercel AI SDK and Next.js?
The Top 7 AI Gateways for Next.js
1. Bifrost
Bifrost is a high-performance, open-source AI gateway from Maxim AI, written in Go. It is designed for enterprise-grade performance, reliability, and governance, making it the top choice for mission-critical applications built on Vercel.
Its key differentiator is performance. Bifrost's own published benchmarks show it adds only 11 microseconds of overhead per request at 5,000 requests per second, ensuring that the gateway is never the bottleneck in an application's response time. This focus on speed is critical for maintaining the fluid, streaming user experiences that the Vercel AI SDK enables.
Best for: Enterprises and teams building production-grade, low-latency applications that require robust governance and reliability features.
Key Features:
- Automatic Failover: Implements zero-downtime routing by automatically failing over to healthy providers or models when a primary provider experiences an outage.
- Semantic Caching: Reduces costs and improves latency by caching responses for semantically similar prompts.
- Virtual Keys: Provides granular access control, allowing teams to set budgets, rate limits, and model permissions per user, project, or customer.
- Enterprise Governance: Includes features like audit logs for compliance (SOC 2, HIPAA), role-based access control (RBAC), and integration with secret managers like HashiCorp Vault.
- Endpoint Governance: Through Bifrost Edge, it extends governance controls to AI traffic on employee machines, tackling the problem of shadow AI.
Integrating Bifrost with a Next.js application using the Vercel AI SDK is straightforward. Since Bifrost provides an OpenAI-compatible endpoint, you only need to change the base URL.
// app/api/chat/route.ts
import { OpenAI } from 'openai';
import { OpenAIStream, StreamingTextResponse } from 'ai';
const openai = new OpenAI({
apiKey: process.env.BIFROST_VIRTUAL_KEY, // Use a Bifrost virtual key
baseURL: 'https://<your-bifrost-instance-url>/v1', // Point to your Bifrost gateway
});
export const runtime = 'edge';
export async function POST(req: Request) {
const { messages } = await req.json();
const response = await openai.chat.completions.create({
model: 'gpt-4-turbo',
stream: true,
messages,
});
const stream = OpenAIStream(response);
return new StreamingTextResponse(stream);
}
2. LiteLLM
LiteLLM is a popular open-source library that provides a unified interface for calling over 100 LLM providers. It can be deployed as a standalone proxy server, acting as a lightweight AI gateway. Its primary strength is its simplicity and the breadth of its provider support.
Best for: Startups and developers who need to support a wide variety of models with a simple, open-source solution.
Key Features:
- Extensive Provider Support: Unifies the API for a vast number of LLM providers.
- Simple Deployment: Can be quickly deployed as a Docker container.
- Basic Observability: Offers logging and cost tracking for requests.
To use LiteLLM's proxy with the Vercel AI SDK, you would run the proxy and point your OpenAI client configuration to its endpoint.
3. Cloudflare AI Gateway
Cloudflare's AI Gateway is a managed service that provides observability and control for AI applications. As part of the broader Cloudflare ecosystem, it benefits from the company's robust global network, offering low-latency connections and DDoS protection.
Best for: Teams already invested in the Cloudflare ecosystem or those who prefer a fully managed solution from a major infrastructure provider.
Key Features:
- Analytics and Logging: Provides detailed logs and analytics on requests, users, and costs.
- Caching: Caches responses to reduce latency and costs for frequent requests.
- Rate Limiting: Protects applications from abuse and controls costs with granular rate limiting.
Integration involves creating an AI Gateway in the Cloudflare dashboard and using the provided endpoint URL in your Next.js application.
4. OpenRouter
OpenRouter is a hosted AI gateway that aggregates a wide range of open-source and proprietary models, often at competitive prices. It finds the best routes for prompts based on model capabilities and cost, simplifying model discovery and optimization.
Best for: Developers who want access to a diverse set of models, including new and experimental ones, through a single API with built-in cost optimization.
Key Features:
- Model Aggregation: Provides access to a massive and constantly updated list of models.
- Cost Optimization: Routes requests to the most cost-effective model that meets the required performance.
- Unified API: Offers an OpenAI-compatible API for easy integration.
5. Kong AI Gateway
Known for its popular open-source API gateway, Kong now offers an AI Gateway specifically for managing LLM traffic. It leverages Kong's powerful plugin architecture to add capabilities like AI-specific traffic control, observability, and security.
Best for: Large organizations, especially those already using Kong Gateway for their microservices architecture.
Key Features:
- Plugin Architecture: Extensible with plugins for custom logic, authentication, and more.
- Multi-LLM Support: Manages traffic across multiple different LLM providers.
- Advanced API Management: Includes sophisticated traffic control, security policies, and analytics.
6. LastMile AI
LastMile AI provides a developer platform for building and scaling AI applications, which includes a gateway component for managing production workloads. It focuses on workflows for fine-tuning, evaluating, and deploying models.
Best for: Teams looking for an integrated platform that covers more of the AI development lifecycle, from model evaluation to production management.
Key Features:
- Model Management: Tools for managing and versioning different models.
- Evaluation and Testing: Workflows for evaluating model quality before deployment.
- Production Observability: Monitors performance and cost of models in production.
7. Portkey
Portkey offers an AI gateway with a focus on observability and reliability. It provides features like semantic caching, automatic retries, and provider fallbacks to improve the resilience of AI applications.
Best for: Teams focused on improving the reliability and observability of their LLM-powered features.
Key Features:
- Observability Dashboard: A user-friendly interface for tracking requests, latency, and costs.
- Semantic Caching: Reduces duplicate costs and improves response times.
- Reliability Features: Includes automatic retries and fallbacks to handle API errors gracefully.
Conclusion
While the Vercel AI SDK provides an excellent foundation for building AI user interfaces, an AI gateway is a crucial component for managing production applications. It adds a layer of control, reliability, and observability that is essential for scaling AI features.
For teams building on Vercel and Next.js, the choice of gateway depends on specific needs. However, for those requiring top-tier performance, robust security, and enterprise-level governance, Bifrost stands out as the most comprehensive and production-ready solution. Its low latency ensures that the gateway never compromises the user experience, while its advanced features provide the control and reliability needed for mission-critical applications. Teams evaluating AI gateways can request a Bifrost demo to see it in action.
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