AI Customer Support Chatbot with Smart Rate Limiting Using Redis

This is a submission for the Redis AI Challenge: Real-Time AI Innovators.

What I Built

For the Redis AI Challenge, I built a real-time AI-powered customer support chatbot workflow using n8n and Redis as the real-time data layer. This chatbot isn’t just reactive, it tracks user activity and throttles requests to ensure scalability and prevent abuse.

Each user session is assigned a unique UUID. Redis then keeps track of how many messages that session sends within a 60-second time window. If a user sends more than 10 messages in that timeframe, Redis prevents further interaction until the TTL resets. This allows for intelligent, real-time rate limiting directly within the chatbot flow.

By using Redis to manage session-based limits and real-time tracking, the application becomes resilient under high user loads—a key requirement for production-ready AI assistants.

Demo

How I Used Redis 8

I used Redis 8 as the core real-time data layer to power session-level message tracking and throttling:

• INCR + EXPIRE pattern: For every user session (keyed by UUID), I increment a counter each time a message is sent.
• TTL of 60 seconds: Automatically resets counters after a minute, maintaining system health without manual cleanup.
• Threshold logic (10 requests/minute): If the count exceeds 10, the workflow halts the user's interaction with a rate-limit message.
• Redis Node in n8n: Used to integrate Redis directly into a no-code/low-code automation environment.

This makes the AI chatbot resilient, rate-aware, and truly real-time—leveraging Redis not just as a data store, but as a real-time traffic manager for an AI system.