What I Built
I built a Second Brain for Real-Time Automation, powered by Redis and n8n — a smart memory engine that:
- Captures, stores, and recalls human-like context from multi-session conversations
- Automates business workflows in real time
- Uses Redis as the core memory, delay timer, and trigger controller
It works across platforms like WhatsApp, and it's designed for use cases such as:
- Order and delivery automation
- Agent memory recall
- Time-based workflows (e.g. "start in 1 hour", converted into seconds using Redis TTL)
- Context-aware task delegation
The system dynamically routes messages based on role (Admin, Customer, Agent), and it persistently remembers chat states using Redis JSON. It’s capable of acting like a CRM, automation layer, and AI memory unit — all in one.
Demo
🚀 [Live Workflow Screenshot] https://drive.google.com/file/d/1mXRqrzDCtEMs4yr2IO4Wst5pp825vOF6/view?usp=drive_link
🎥 [Demo Video] https://drive.google.com/file/d/1NKhmdgOHxA9NFlbc8Xe_8cxHCKxz5pRE/view?usp=sharing
📸 Screenshots:
- Redis key structure
- Message context stored and recalled
- Real-time delivery timers firing workflows via TTL expiration
How I Used Redis 8
Redis was at the core of the brain. I used:
- RedisJSON to store structured session history, roles, and memory per phone number.
- Redis TTL + Key Expiry to schedule timed workflows ("start in 1 hour" is auto-converted to seconds and scheduled in Redis).
- Redis Streams for logging and chaining AI agent interactions.
- Pub/Sub to push live triggers to n8n for follow-ups, reminders, or escalations.
This allowed me to build a modular second brain that remembers, reacts, and acts in real time — like a digital operating system for conversations.
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