AI gateways: What are they & how can you deploy an enhanced gateway with Redis?

As companies increasingly deploy Generative Artificial Intelligence (GenAI) applications in production, new challenges have emerged that focus more on scaling and securing usage, especially when interfacing with users outside the organization. To address these issues, companies are starting to use AI gateways as a key component of their AI infrastructure. An AI Gateway simplifies, secures, and governs access to Large Language Models (LLMs) within an enterprise setting by acting as a centralized platform for managing AI workflows. Key features of an AI gateway include unified API, rate limiting, routing based on intent, caching, PII redaction, guardrails, usage tracking and chargebacks, and credentials management. Companies can build their own custom platforms or use established open-source solutions like LiteLLM, Guardrails AI, Langfuse, Hashicorp vault, and Redis to construct GenAI gateways or platforms.

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