--- title: "Use Case: AI Sales Pipeline for Hospitality | Kylon + Apollo Outreach" description: "How a US hospitality firm used Kylon and Apollo to automate 1,000-contact cold outreach, AI reply scoring, and lead routing." url: "https://kylon.io/use-cases/ai-sales-pipeline" language: "en" --- [HOME](https://kylon.io/)\>[Use Cases](https://kylon.io/use-cases)\>How a US Hospitality Firm Built an AI Sales Pipeline with Kylon Use Case8 min read # How a US Hospitality Firm Built an AI Sales Pipeline with Kylon A US-based hospitality company used Kylon to automate 1,000-contact outreach, AI reply scoring, and lead routing. [Get started](https://app.kylon.io/sign-up) Kylon TeamProduct July 21, 2026 ## The Challenge The company sells premium event packages to corporate decision-makers, brand managers, and event planners across the United States. Their sales team was small. One coordinator could handle about 20 personalized emails a day. At that rate, reaching 1,000 qualified prospects would take months. And the follow-up sequences that actually convert were falling through the cracks. ## What They Built with Kylon ### Lead Sourcing with Apollo The head of business development asked a Kylon agent to pull a targeted list from Apollo. The agent searched for decision-makers matching their ideal customer profile and built a list of **1,000 contacts** with verified email addresses, company names, titles, and firmographic signals. The list lives inside Kylon as a structured dataset. No export-import dance between Apollo and a spreadsheet. ### Automated Email Sequences The agent sends **30 personalized cold emails per day**, spaced throughout the day to avoid spam filters. Each email is tailored based on the prospect's company and role. The system follows a multi-step sequence: - **Initial email** with a personalized hook based on company signals - **Follow-up emails** if no reply - **Break-up email** after a set number of attempts, ending the sequence respectfully The agent handles the entire sequence autonomously. For high-volume cold outreach, the team chose to let the agent send without manual approval on each message, trading per-email control for throughput. ### AI Reply Scoring and Routing When prospects reply, the agent scores each response: - **Hot**: The prospect is interested and wants to learn more - **Warm**: They asked a question (pricing, availability, details) - **Cold**: Not interested, out of office, or unsubscribe requests For hot and warm replies, the agent checks whether it has the information to respond. If someone asks "How much is a weekend package?", the agent looks up the answer from its knowledge base and replies directly. If the prospect says "I'm interested, tell me more," the agent sends a calendar link to book a call with the sales coordinator. For replies the agent can't handle confidently, it escalates by CC'ing the human sales coordinator, who picks it up manually. ## See It in Action The chat panel shows real-time agent updates. The dashboard tracks every lead's status, score, and last action. No tab-switching. No copy-paste between tools. The outreach pipeline inside Kylon. Chat and dashboard in one view. [Find clients together: a Kylon demo with sample data](https://static.purework.app/files/8750896058f90bcb2fa93676723db99a/demo-find-clients-together.mp4) Demo · sample data. One request finds prospects with a reason for each, the team corrects the list in the thread, and the agent builds a CRM and drafts the intros for a person to send. ## Continuous Improvement The head of BD periodically reviews the agent's sent replies. When he spots a response that doesn't match the brand voice or misses a nuance, he screenshots it and sends it to the agent in the room. The agent updates its internal guidelines and improves over time. The team also uses **room guidelines** to set behavioral rules the agent follows: tone, escalation thresholds, and which topics require human sign-off. ## Results - **30 personalized emails sent daily** without any human effort - **80%+ of replies handled by AI**, with only edge cases escalated - **Sales call bookings happen end-to-end** without manual scheduling - **The agent improves over time** through screenshot feedback and guideline updates - **One sales coordinator** manages what previously would have required a team of 3-4 SDRs ## What Makes This Work This isn't a chatbot bolted onto a CRM. The agent lives in the same workspace as the sales team. It reads the same guidelines, operates on the same data, and gets corrected in real time. The feedback loop is measured in minutes, not sprint cycles. - **Apollo integration** for lead data without manual imports - **Email connection** for sending and receiving directly from the company's domain - **Room guidelines** as a living playbook the agent follows - **Database App** as a shared source of truth for the pipeline - **Human-in-the-loop** where it matters, fully autonomous where it doesn't If your calls are recorded in Fathom, the pipeline update can start from the summary instead of memory. See [Kylon for Fathom users](https://kylon.io/solutions/fathom). Your first company harness. Where humans and agents run your business together. [Get started](https://app.kylon.io/sign-up) ## More Use Cases [View all](https://kylon.io/use-cases) [ ### How an AI Startup Automated Talent Sourcing with Kylon A growing AI startup built a recruiting system where agents parse resumes, score candidates against open roles, and manage outreach, all from one room with a structured database. 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