The Problem

Generative Engine Optimization is a real category most agencies can't speak to. Buyer-intent queries increasingly get answered inside ChatGPT, Perplexity, and Gemini, and when a reader does click through, GA4 files it under "Direct." Agencies are being asked to prove performance on a channel their tools can't see. There's no established playbook, and the existing tools each solve one piece and estimate the rest.

What We Built

A SaaS platform combining three previously-separate capabilities: AI visibility scanning across six platforms in parallel (querying the same models real buyers actually see), evidence-based AI traffic attribution, and a Bayesian marketing mix model treating AI as its own channel.

The attribution engine doesn't guess. A visit is credited to AI only when a stored receipt proves an AI retrieval agent fetched that exact page minutes before the human arrived: bot fetch paired to human visit, attributed per platform. No heuristics, no inflated numbers. If Faneros says ChatGPT sent the visitor, it can show you the receipt.

Nine deploy-ready deliverables generate per scan. Fixed model routing assigns the right frontier model to each one, and every output passes deterministic structural validation plus an automated QA gate before it can be downloaded.

The Problem

A North American field sales team of 38 account executives, each managing roughly 80 accounts in their patch. Every Monday, every seller faces the same question: which five accounts to call this week, which to deprioritize, and what to actually say when they get on the phone. Salesforce can produce a list and a CSV. It can't answer those questions. Sellers were guessing.

What We Built

A single-operator platform that turns Monday-morning planning into minutes instead of hours. Three capability surfaces under one filter bar: territory hunting (drop a 15–50 mile radius around any city, see every account fully hydrated), one-click intelligence (executive briefings and internal sales plans generated in ~3 minutes from internal data plus live 10-K and 10-Q filings), and a manager-level coverage heat map for partner gaps and white-space planning.

The Problem

A customer calls while the front desk is already helping someone. A website inquiry arrives after hours. Someone needs help in a language the team doesn’t speak. The business has earned their interest, but the conversation never gets started.

Another inbox is not the answer. The first response needs to understand the request, gather the right details, and give the customer a useful next step without turning every routine question into another interruption for the team.

What We Built

LunaPhone: a multilingual voice-and-chat front-desk experience. Five specialized roles organize the customer journey: intake, lead qualification, scheduling, frequently asked questions, and human escalation.

The product supports 50 languages. Visitors can hear original English, Spanish, and Polish phone conversations, switch between recordings instantly, and explore customer-service scenarios through guided chat.

A high-definition, audio-reactive interface makes the experience tangible. The circular agent is alive from arrival; its light and motion respond to the recordings. Visitors can also try a permission-based local microphone visualizer. The interface makes the work approachable instead of asking a buyer to imagine what voice AI might feel like.

The Business Value

The value is not a talking circle. It is a better front door to the business. The system is designed to make first responses more useful, help customers communicate comfortably, and reserve the team’s attention for conversations that actually need a person.

For a company or its agency, the opportunity is to connect the first hello to the right next step, not bolt on another disconnected chatbot. LunaPhone makes that workflow something a buyer can hear and explore.