Hey Product Hunt! 👋 I'm Takreer, founder of Voicefox AI. Three years ago, I was sitting in a call center at 2am watching agents answer "when do you close?" for the 200th time that shift. Everyone was burned out. Customers were furious at the IVR maze. And the "AI solutions" on the market were either $100K enterprise deployments or shallow chatbots that collapsed the moment a caller went off-script. So we built Voicefox — an LLM-native voice agent that handles real conversations, not just keyword matching. What makes it different: 🟢 Actually sounds human — 96.8-97.5% ASR accuracy even with background noise. Handles interruptions naturally. Stops when you cut in, re-contextualizes, responds. Most bots fail here. 🟢 5-7 day deployment — pre-built CRM connectors, upload your docs and it's live. No 3-month integration project. Switch based on compliance, cost, or performance. No lock-in. 🟢 100-300 concurrent calls on one tenant. Scales to peak season. Real numbers from production: - Chengdu World Games:51%of bilingual ticket inquiries resolved by AI without human touch - Enshi AAAA Scenic Areas: 60%AI resolution rate during tourist peak, deployed with China Telecom - Dental chain: voice-cloned their real advisors, replaced most manual follow-up dialing - K12 enrollment hotline: zero missed calls during admission rush Pricing is straightforward: ¥20K-150K/year (~$2,750-20,600/year), no per-minute surprises. Honest ask: if you've dealt with IVR pain, abandoned calls, or call center burnout — what would make you trust an AI to handle phone calls? Where's your line between "automate this" and "I need a human"? AMA — happy to talk architecture, pricing, or the scars from building voice AI in production. 🎤

What is voicefox.ai

LLM voice agents for inbound & outbound calls at scale.

LLM voice agents for inbound & outbound calls at scale.