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Capturing 100% of inbound demand with AI voice agents

Capturing 100% of inbound demand with AI voice agents

Overview

Iyuno is a global leader in localization, dubbing, and media services.

Sector

Manufacturing

Team size

2500+

Location

Global

Established

2002

Funding

Public

Core features

Invoice Processing automation

Overview

Topgolf Oberhausen is a high-volume experiential entertainment venue.

Sector

Healthcare

Team size

30,000+

Location

Oberhausen, Germany

Established

2000

Funding

Public

Core features

AI Voice Agents

Problem

Topgolf was losing revenue silently. With ~60% of inbound calls going unanswered, staff were overwhelmed and pulled away from in-venue guest experience. Every missed call represented lost bookings, frustrated guests, and revenue that never had a chance to convert. Call volume had simply outgrown human capacity.

Approach

N-square AI deployed a production-grade AI voice receptionist with human-like speech synthesis, context-aware conversation, and RAG-based retrieval for verified answers. The system handles bookings confidently, answers real questions naturally, and seamlessly escalates complex cases to humans.

Outcomes

Outcomes

  • 100% of inbound calls answered

  • 5,000+ calls handled monthly

  • Consistent ~75% call success rate

  • No additional staffing required

Turning Missed Calls into Captured Revenue

Like many high-volume experiential venues, Topgolf Oberhausen faced a silent but costly problem: their team was overwhelmed by inbound calls — and missing nearly 60% of them.

Executive Summary

Topgolf Oberhausen partnered with TrueHorizon AI to eliminate missed inbound calls and turn their front desk into an always-on, revenue-capturing system. Like many high-volume experiential venues, Topgolf Oberhausen faced a silent but costly problem: their team was overwhelmed by inbound calls — and missing nearly 60% of them. Every missed call represented lost bookings, frustrated guests, and revenue that never even had a chance to convert.

TrueHorizon AI deployed a production-grade AI voice receptionist that answers 100% of inbound calls, handles bookings and enquiries in real time, and seamlessly escalates to humans when needed. The result: zero missed calls, higher booking capture, and immediate revenue uplift — without adding headcount.

The Problem: High-Intent Calls, No Capacity to Answer Them

Topgolf Oberhausen operates in a high-intent environment. People don't call casually — they call to book bays, plan events, ask time-sensitive questions, and confirm availability. But call volume had outgrown human capacity.

Key challenges included:

  • Approximately 60% of inbound calls going unanswered

  • Staff pulled away from in-venue guest experience

  • Missed bookings during peak hours

  • No scalable way to handle demand spikes

  • Revenue loss that was invisible but compounding daily

When a guest calls and no one answers, they don't wait — they move on. Topgolf didn't need more "call analytics." They needed someone to pick up — every time.


The Vision: Never Miss a Call Again

The goal was simple and uncompromising: answer 100% of inbound calls — with human-level quality — at all times.

Not voicemail. Not "press 1 for this, press 2 for that." And not a brittle IVR that frustrates customers.

Topgolf wanted a voice agent that:

  • Sounds natural and human

  • Understands context and intent

  • Answers real questions accurately

  • Handles bookings confidently end-to-end

  • Knows when and how to escalate to a human

  • Runs reliably in production, not just in a demo

The Solution: A Human-Like AI Voice Receptionist

The Solution: A Human-Like AI Voice Receptionist

N-square AI designed and deployed a production-grade voice agent purpose-built for real-world hospitality operations.

The core architecture includes:

  • ElevenLabs for human-like speech synthesis

  • Anthropic’s Claude models for workflow orchestration

  • Advanced Retrieval-Augmented Generation (RAG) as the knowledge engine

  • High-speed semantic retrieval via a vector database

  • Dynamic web scraping + scheduled refreshes for live data ingestion

  • A static knowledge base covering canonical policies, FAQs, pricing, hours, and events

This was not a demo bot. It was a reliable, enterprise-grade system designed to operate continuously in a high-volume, revenue-critical environment


How the Voice Agent Works

How the Voice Agent Works

Every inbound call is picked up instantly — no queues, no missed rings.

From the customer's perspective, it feels like calling a highly trained receptionist:

  • The agent distinguishes booking intent vs. general enquiry

  • Answers detailed questions in natural, conversational language

  • Pulls correct and up-to-date information from live and static sources

  • Handles interruptions, clarifications, and follow-up questions gracefully

Thanks to a cutting edge RAG system, the agent doesn't hallucinate or guess — it retrieves verified answers grounded in Topgolf's real data.

Operationally:

  • Booking enquiries are handled immediately and end-to-end where possible

  • High-confidence resolutions stay fully automated

  • Complex or edge cases are transferred cleanly to a human, with context

No dead ends. No frustrated callers repeating themselves.

What Makes This System Different

What Makes This System Different

"N-Square AI is a smart and capable team, and you guys did a great job" — Philip Fu, CTO of Topgolf Europe


This was not just "LLM + prompt." TrueHorizon built a defensive, production-safe AI stack designed for reliability and control.

Key differentiators:

  • Dynamic web scraping to reflect live updates (hours, events, pricing changes)

  • Statically curated knowledge for critical, canonical facts

  • Scheduled refresh pipelines to keep information current without manual overhead

  • Vector-based semantic search for fast, context-aware retrieval

  • Guardrails against hallucination, ensuring responses stay grounded in approved data

  • Deterministic workflow logic via n8n, so key flows behave predictably every time

The result is a voice agent that behaves like a trained employee — not an experiment.


Measurable Results

Measurable Results

Within weeks of deployment, Topgolf Oberhausen achieved:

  • 100% of inbound calls answered

  • Thousands of calls handled autonomously

  • A consistent ~75% call success rate at scale (fully resolved without human intervention)

  • Increased booking capture and reduced leakage

  • Immediate reduction in missed revenue

  • No additional staffing required

From the live dashboard:

  • 5,000+ calls handled in a single month

  • Average call duration ~1.5 minutes

  • Stable performance under real-world load and peak demand

Every call answered is a chance to convert. Previously, most of those chances were lost.


Business Impact

Business Impact

What changed wasn't just call handling — it was revenue certainty.

  • Demand is no longer throttled by staff availability

  • Peak hours no longer mean missed bookings and unanswered phones

  • Staff can focus on in-venue guest experience instead of juggling calls

  • Management gains confidence that inbound demand is fully captured

This is what AI looks like when it works quietly in the background — and pays for itself.


Why This Matters

Why This Matters

For hospitality, entertainment, and experience-driven businesses, inbound calls are high-intent revenue. Missing them is equivalent to locking the front door during peak hours.

AI voice agents in this context are not about novelty.
They are about:

  • Reliability at scale

  • Consistent execution, 7 days a week

  • Always-on coverage for high-intent demand

Topgolf Oberhausen now has an always-on receptionist with:

  • Infinite patience

  • Zero sick days

  • Consistent, policy-aligned performance


Takeaways

Takeaways

This is not a chatbot. This is not an IVR. This is not a demo.

It is a production-grade AI employee — designed to capture revenue that was previously lost, silently and permanently.

Topgolf Oberhausen didn't just add automation. They removed a revenue ceiling.