The challenge 🎯
Support teams face slow response cycles, fragmented documentation, and repetitive customer requests that reduce satisfaction.
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Project spotlight ✨
Huluve
Huluve rethinks customer interaction with seamless conversational assistance: voice AI for call-center workflows and AI chat embedded directly in the website.
How I approached it 🗺️
Built an AI support workflow that starts from company data ingestion (website, docs, custom instructions), then powers both voice AI call-center conversations and website-integrated AI chat through a unified assistant layer.
Why it matters 💡
A support experience designed to reduce waiting time, improve customer interaction quality, and scale continuously without degrading responsiveness.
Highlights 🌟
Key takeaways with the most relevant technical signals in focus.
1
AI applied to customer support, product Q&A, and augmented docs 2
Seamless conversational assistance across voice AI call-center channels and website-integrated AI chat 3
Human-like interaction model to avoid bot-style support experiences 4
Structured flow: ingest data, configure AI behavior, automate processing 5
24/7 support coverage with multilingual positioning 6
Product messaging targets up to 50% support volume reduction Technology stack 🧰
Grouped by role so the stack is easier to read at a glance.
Languages
📘 TypeScript 🐍 Python
Runtime and APIs
🚀 Node.js (Fastify)
Data layer
💾 Redis
Infrastructure
🐳 Docker
DevOps
⚙️ CI/CD
Project profile fit 🧠
A compact view of the signals this project communicates.
What it reflects ✨
Product thinking
Customer-obsessed design
Automation-first mindset
Balancing UX with operational scalability
What it shows 🔎
AI product development
Support automation
Documentation intelligence
End-to-end delivery
Open the live project to explore the full implementation and documentation.
Open Huluve 🌍