Brandon Chase

Brandon Chase

Co-Founder, Furie.ai.
All activity
Most chat widgets leave you blind. Furie™ calculates Heat Scores for every visitor based on real-time behavior and context. Score 95? They are reading your pricing. Furie™ jumps in to close the deal. All free: ✅ Live Heat Scoring ✅ Intelligent chatbot ✅ Live Agent Handoff ✅ Unlimited History We offer optional power-ups like: 🧠 WingMate™ (AI agent coaching) ⚡ Proactive Messaging (Engages visitors automatically) 📈 Deep Analytics w/ QA scoring 🏷️ Promo Pops™ for upselling Now Fly with Furie™
Furie.ai
Furie.aiBot/Agent Chat that scores guests in real-time (Free 4 Life)
Brandon Chasestarted a discussion

Why we made the core features Free Forever (and how we survive)

We debated the pricing model for weeks. Ultimately, we decided that visibility (Live Prospecting) shouldn't be gated behind a paywall. Small businesses need that data the most. So, the core stack (Widget, Heat Scoring, Live Handoff, History) is $0. We only monetize via optional 'AI Power-Ups' (like Agent Coaching and Automated Outreach) for teams that are scaling. We hope this aligns...

Brandon Chasestarted a discussion

Solving the "Chat Plugin Bloat" problem on WordPress

A huge constraint we set was that Furie could not touch the host WordPress database. Too many chat plugins destroy PageSpeed scores by writing logs to wp_options or loading heavy assets. We architected the plugin as a lightweight async wrapper. All the socket connections (Pusher) and state management happens on our external API layer. Even the chat history is stored remotely. If you are a WP...

Brandon Chasestarted a discussion

Moving from "Reactive Support" to "Proactive Sales"

We built Furie based on a frustration with the status quo: standard chat widgets are blind. You install them and wait for a 'bing.' Meanwhile, your highest-intent traffic (people reading your pricing page twice) leaves silently. We tried to solve this by building a client-side 'Heat Score' algorithm. It monitors scroll depth, dwell time, and specific URL regex patterns to score purchase intent...

Brandon Chasestarted a discussion

Why we ditched Vector DBs (RAG) for Perplexity's Live API

While building the AI context engine, we realized that standard RAG (Vector Databases) was too slow for dynamic content. If a user is looking at a flash sale or a live inventory count, a cached vector embedding is useless. We decided to architect Furie using Perplexity's Sonar models to live-crawl the specific URL the visitor is on during the chat. It added about ~400ms of latency compared to...