As organizations continue to adopt AI-driven applications, managing usage and costs becomes more critical. Large language models (LLMs), such as those provided by OpenAI, Google, Anthropic, and Mistral, can incur significant expenses when overused.
This blog will explore how you can streamline your AI workloads by leveraging Kong’s token rate-limiting and tiered access features.
AI models have become vital for everything from customer support to advanced data analysis. However, their power comes at a cost — both financially and in terms of system resources. If left unchecked, unrestricted AI requests can quickly spiral into overwhelming expenses and overburdened infrastructure.
Without proper governance, overuse of AI resources can lead to overloaded systems and budget overruns. Equally concerning is the risk of malicious or unintended misuse, such as when tools that are meant for legitimate research end up being exploited for prohibited or resource-intensive tasks.
As AI becomes integral to business operations, managing access to these powerful resources is essential. Kong’s AI Gateway provides a solution by enabling organizations to define granular policies for controlling AI usage. With features like token rate-limiting, businesses can limit how often users or systems access AI models, ensuring fair usage and managing the costs of resource-heavy models.
In addition, tiered access functionality allows companies to offer different levels of service based on user profiles or subscription plans. For example, premium users can have faster or more frequent access, while basic-tier users can be limited. Together, these features provide a flexible framework to optimize AI access, improve cost management, and ensure efficient use of valuable AI models.
When interacting with AI models, you often pay per token. Tokens represent segments of text. This can include prompt tokens (your request), completion tokens (the model’s response), or total tokens (the sum of both). Token usage scales with the complexity and length of queries, directly translating to costs.
Token usage directly correlates with the length of queries:
This scaling of token usage — especially as longer, more complex queries are used — directly impacts costs, making efficient token management crucial for cost-effective AI implementation.
Cost optimization
Implementing token limits is essential for preventing unexpected cost spikes due to uncontrolled queries. By setting appropriate limits, organizations can:
Fair usage and system health
Token limits ensure equitable resource distribution and maintain system performance:
Tiered access control involves categorizing users or applications into groups (e.g., gold, silver, and bronze). Each tier carries distinct entitlements, usage limits, and access permissions.
Cost-effective resource allocation
Tiered access control allows organizations to reserve premium AI resources, such as current-gen state-of-the-art (SOTA) models, for top-tier users who genuinely require their capabilities. This approach ensures that expensive computational resources are utilized efficiently, maximizing return on investment.
Prioritized performance
By implementing a tiered system, organizations can guarantee that higher-tier users experience consistent performance without slowdowns caused by heavy consumption from lower tiers. This prioritization ensures critical operations and high-value users receive the necessary computational power and response times.
Enhanced user experience
Tiered access provides clear expectations regarding resource availability and service quality for each user group. This transparency helps manage user expectations and allows for a more tailored experience based on specific needs and priorities.
Why do you need an AI proxy?
As organizations integrate LLMs into their applications, managing usage, cost, and access becomes critical. Out of the box, most LLM APIs don’t support granular rate limiting, token tracking, or role-based access controls across multiple consumers. That’s where an AI proxy comes in.
An AI proxy sits between your users and the LLM provider, enabling centralized control, observability, and governance.
With Kong acting as the AI proxy, you gain the ability to:
This setup becomes essential when using Kong’s AI Rate Limiting Advanced plugin, which brings AI-specific token logic into traditional API management workflows.
You can learn more about setting up AI Proxy in the docs or by reaching out to your Kong account rep. Not a customer but want a deeper dive? Chat with an API expert today.
Security integration
Integrate tiered access control with broader security measures, ensuring each tier adheres to appropriate security protocols. This may include:
Compliance and governance
Ensure the tiered access control system aligns with relevant regulations and internal governance policies. This is particularly important when dealing with AI systems that may process sensitive data or make critical decisions, considerations crucial when dealing with AI in highly regulated environments.
Kong offers a selection of AI plugins related to AI governance (including Prompt Guard, Prompt Decorator, and AI Sanitizer) to help provide a more layered security approach.
User education and support
Develop comprehensive documentation and support systems for each tier, helping users understand their access levels, available features, and any limitations. This transparency contributes to a better overall user experience and reduces potential frustration or misunderstandings.
By implementing a well-designed tiered access control system, organizations can effectively manage their AI resources, optimize costs, and provide a tailored experience for different user groups. This approach enhances operational efficiency and ensures that AI capabilities are leveraged in the most impactful and appropriate manner across the organization.
Monitoring and alerting
Effective monitoring is your first line of defense in managing API and token consumption. By implementing real-time dashboards and sophisticated alerting mechanisms, you create a proactive environment that prevents unexpected disruptions. Key focus areas include:
Planning for scale
As your application grows, your token utilization strategy must evolve. Scalability planning ensures you're prepared for increased demand while maintaining cost-effectiveness and performance. Strategic approaches include:
Ensuring seamless user experience
The ultimate goal is to create a seamless experience that balances technical constraints with user innovation. Transparency and flexibility are key to maintaining user trust and engagement. Some user-centric strategies include:
Recap
Token rate-limiting and tiering are not just technical configurations — they're strategic imperatives in the AI service ecosystem. These mechanisms serve multiple critical functions:
Kong's approach transforms rate limiting from a mere technical constraint into a sophisticated governance framework that adapts to your organization's evolving AI service needs.
Looking ahead
As AI technology evolves, Kong’s unified gateway approach will simplify how you govern usage. From AI rate-limiting plugins to dynamic access policies, there’s a wide array of tools at your disposal to ensure responsible scaling of your AI-driven applications. Start your AI governance journey today!
The complexity of AI services requires proactive, intelligent management — Kong provides the tools to make this not just possible, but seamless and strategic. Get a demo today!
In this blog post, we'll talk about the significant challenge of managing and governing a growing number of APIs across multiple teams in an organization — and how Control Plane Groups are a clear solution to avoid the chaos of inconsistent policies
Meet Emily. She’s an API product manager at ACME, Inc., an ecommerce company that runs on dozens of APIs. One morning, her team lead asks a simple question: “Who’s our top API consumer, and which of your APIs are causing the most issues right now?”
Ever feel like you're fighting an uphill battle with your API strategy? You're building APIs faster than ever, but somehow everything feels harder. Wasn’t API-first supposed to make all this easier? Well, you're not alone. And now industry analys
The healthcare industry is buzzing about FHIR (Fast Healthcare Interoperability Resources). Pronounced “fire,” this widely adopted data standard has been revolutionizing how healthcare information is exchanged. But building a truly modern, secure, a
Behind every smooth user experience is a maze of APIs quietly handling requests, responses, and data flows. This makes APIs critical connectors that enable applications to communicate and share data seamlessly. When these vital conduits fail, the
As enterprises increasingly embed AI and Large Language Models (LLMs) into their digital experiences, enforcing robust AI guardrails becomes paramount to safeguard users, protect data, manage operational costs, and comply with regulatory and ethical