Built an AI-powered customer support automation workflow that can classify incoming emails, ident...Built an AI-powered customer support automation workflow that can classify incoming emails, ident...
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Built an AI-powered customer support automation workflow that can classify incoming emails, identify support requests, retrieve relevant information from a knowledge base, and assist with generating the right response.
The workflow combines AI agents, RAG, embeddings, Pinecone, Gmail, and automated notifications to reduce repetitive support work while keeping human review in the loop.
The flow includes:
📩 Incoming email detection
🤖 AI-based support request classification
📚 Knowledge base retrieval with Pinecone
🧠 Context-aware customer support agent
✍️ Automated response draft generation
🔔 Reviewer notification through Telegram
⚡ Separate handling for non-support emails
I’ve been exploring more ways to combine AI + automation + real-world business workflows, rather than using AI only as a chatbot.
A closer look at ROVR, a landing page concept for an autonomous delivery robot.
A robot at your door is new for most people, so every section answers a question a first time customer would ask: how it gets here, what it can carry, what it costs and what happens if it gets stuck.
Our favorite part is the FAQ, rebuilt as a chat where you can ask ROVR anything.
What would you want to know before a robot delivers your groceries?
Love the idea of turning the FAQ into a conversation. My first question would be: what happens when the robot encounters something unexpected mid-delivery? Showing how ROVR handles those moments could build more trust than any feature list.
We designed and built a high-trust Framer landing page for an enterprise AI platform, turning complex back-office workflows and policy-driven governance into a high-converting visual experience.