Support bots that forget every conversation aren't support bots. They're expensive FAQ pages.
I built SupportMind to fix that — a customer support agent that actually remembers.
The architecture is two layers:
Memory (Hindsight): After every interaction, the agent stores structured context in a vector namespace per user. Next session, it recalls semantically — "payment problem" retrieves "Visa charge failing" even if the words don't match.
Routing (cascadeflow): Not every query needs GPT-4. Password resets go to Groq's free tier. Complex billing disputes escalate. Every decision is logged with model, cost, latency, and reason.
The delta that matters:
Session 1: "Can you tell me your card details and the error you're seeing?"
Session 3 (same user, same issue): "I see you've had recurring issues with your Visa ending in 4242. Last time, clearing billing cache fixed it — want to try that first?"
Same infrastructure. Completely different agent.
On a typical support workload: ~80% simple queries handled by the cheap model. Cost per query dropped from ~$0.012 to ~$0.002.
The part I didn't expect: routing and memory compound. When Hindsight shows a user has had the same issue four times, cascadeflow automatically classifies their next message as complex — even without explicit signals. That fell out of the architecture. 👇
https://lnkd.in/gn8NwP6Z hashtag#AIAgents hashtag#AgentMemory hashtag#Hindsight hashtag#cascadeflow hashtag#LLM hashtag#AI