@Sajid Ali thank you!!

@Phil Wilson will do for future work. Thanks for the feedback Phil!

@Phil Wilson Hey Phil, thanks for launching this! You are absolutely 100% right. The reason field services (HVAC, plumbing, roofing, facility management) are so incredibly lucrative for AI agencies—but so brutal to execute—comes down to one specific bottleneck: The Pricing Layer. Traditional LLMs are probabilistic. They excel at context, conversation, and semantic search. But complex service pricing requires 100% deterministic mathematical accuracy. If an AI assistant miscalculates a multi-variable HVAC change-out quote by even 5% because of a token hiccup, the agency loses the client, and the client loses margin. Furthermore, legacy giants in this space (like ServiceTitan and Housecall Pro) are aggressively locking down their API gates to protect their own ecosystems and processing fees. With that being said, I built a specialized infrastructure layer to solve this exact problem—completely decoupling the LLM from the mathematical engine so numbers stay 100% accurate, consistent, and secure. If you are currently building for home services or facility management and hitting these exact walls, drop a comment below. Let’s get this BoF cohort together, break down the backend architecture, and map out how to bypass these legacy bottlenecks!

Hey Titons! Joining the fight against legacy software walled gardens 🛡️ - Name: Hisham Juneidi - Nationality: Jordanian - Current Location: Stamford,CT One unique or fun fact about me: I have a weird obsession with finding architectural backdoors into multi-billion dollar legacy ERPs like ServiceTitan and Housecall Pro. I love building systems that legally strip away their power to gatekeep data or force businesses into high-fee native payment processors. What’s your current goal? I’m scaling Quotix.ai, which is a specialized backend framework and schema-driven infrastructure layer. My goal is to empower HighLevel agencies to comfortably pitch and close mid-market and enterprise accounts ($10M–$100M+ firms) by positioning GHL as the front-end intake valve, while using n8n to handle complex data routing and external financial reconciliation completely outside of legacy software restrictions. What’s the biggest challenge you’re facing right now? Right now, it's standardizing these deep-tech backend automation layers so that a traditional marketing agency can deploy them out-of-the-box. Legacy platforms intentionally try to make third-party integrations a manual, administrative nightmare for contractors to protect their processing fee margins. Turning that broken workflow into a seamless, automated, and repeatable SaaS module for agencies is the current hill I'm climbing. Excited to connect with everyone here and turn some of this "AI Fog" into highly scalable, concrete backend infrastructure! 🚀

Thanks for having me on your podcast! It was great talking with you and sharing how GHL can leverage Quotix.ai in their businesses and agencies