Hospitality businesses cut call costs by 60-95%

The situation

Every hospitality operator knows the pattern: a ringing phone during the dinner rush, staff pulled from the floor to answer the same question for the seventh time that day.

The calls do not stop being expensive just because headcount is frozen. They pile up. Some go unanswered. Some get to a human who spent four minutes saying the same thing they said to the last caller. Nobody has a transcript of what was asked. Nobody knows how many calls went cold while the team was busy.

Call Eva exists to break that pattern. We built it as a voice AI assistant that picks up every call 24/7, carries a natural two-way conversation, and resolves the request (a reservation, a question about hours, a payment reminder) without putting anyone on hold unless the situation genuinely needs a human.

Within the first month of deployment, hospitality businesses running Call Eva reported 60 to 95% lower support call costs. Staff recovered their focus.

Whoever answers first usually wins the job. A missed call does not show up on a report as a lost sale. It just disappears.

What we had to solve

• Making the voice response feel like a person, not a phone tree

  The biggest reason voice AI fails in hospitality is response latency. A pause longer than half a second sounds like a glitch, and callers hang up. We had to get the full loop (speech recognition, intent processing, response generation, and voice synthesis) under 300ms. ElevenLabs gave us the voice quality; the architecture gave us the speed. Getting both right together took most of the early build cycles.

• Building a system that knows when it does not know the answer

  An AI that guesses wrong on a hospitality call costs the business the booking. Call Eva had to be confident on the things it knows (opening hours, menu items, reservation availability) and immediately transparent about the things it does not. When a call reaches the edge of what the knowledge base covers, Eva hands off to a live agent with a complete call summary rather than attempting an answer. Getting the confidence scoring right, so handoffs happen at the right moment rather than too early or too late, required real call testing with live operators before we were satisfied.

1. Every call answered regardless of time or volume, most resolved in under 90 seconds

   Eva picks up every call regardless of time or volume: no hold music, no voicemail. It introduces itself, understands the request, and resolves it in a natural back-and-forth conversation. Most calls resolve in under 90 seconds.

   

2. Standard bookings confirmed within the same call, no staff involvement, no callback needed

   Eva integrates with calendar and booking systems to check availability, confirm reservations, and send follow-up SMS confirmations, all within the same call. No callback required, no staff involvement for standard bookings.

   

3. Operators trigger outbound campaigns, no staff time required to execute them

   Operators trigger outbound campaigns for unpaid invoices, upcoming appointments, or seasonal promotions. Eva calls the customer by name, references the specific context, and handles responses in the same conversation. No staff time required to execute the campaign.

   

4. Operators see peak hours and top questions; escalated calls hand off with a full briefing already done

   Every call generates a transcript, intent classification, and resolution status. Operators see peak hours, top questions, and escalation rates without listening to recordings. When a call needs a human, Eva hands off with a full call summary so the agent is already briefed.

   

The technical choices that made the voice experience feel natural

ElevenLabs

Low-latency voice synthesis that produces natural-sounding responses in under 300ms. At longer latencies, callers assume the line dropped. ElevenLabs was the only option that hit both the quality and speed targets we needed for hospitality calls.

Twilio

Reliable call routing, SIP integration, and programmable outbound dialling at scale. Twilio handles the telephony layer so the application logic stays focused on the conversation, not on carrier negotiation.

Next.js

The operator dashboard needed fast initial load and real-time transcript streaming as calls came in. Next.js App Router with server components handled both without a separate backend service.

AWS

Call recording, transcript storage, and event processing run on Lambda and S3. AWS gives the platform the storage reliability and processing scale hospitality call volumes require.