Solution Database / Hospitality and Events
Reservation Concierge Agent
Restaurants still take most bookings by phone or WhatsApp, forcing staff to interrupt prep, write on paper and double book when the diary is not checked. The agent reads and writes directly to the restaurant's real diary and sounds warm enough for regulars, trained on the owner's own voice rules.
01The offer
For owner-operators of small restaurants and trattorias, turn casual voice notes and text messages into confirmed diary entries with reminders and calendar invites. Address the recurring problem: staff stop mid prep to answer calls and double book when the diary is not checked. The value hypothesis is a quieter phone and fewer no-shows; the pilot must establish whether the agent sounds warm enough for regulars.
- For
- Owner-operators of small restaurants and trattorias
- Takes in
- Voice notes and text messages from diners, plus the restaurant's booking diary
- Delivers
- Confirmed diary entries, calendar invites and reminders
- Message
- Let the phone answer itself and never double book again.
- Lead magnet
- A free two week trial on the owner's own phone with their own voice rules.
02How it works
- Transcribe and detect language from voice notes and text
- Cross check availability against the diary
- Ask one clarifying question when the request is ambiguous
- Write the booking with guest name, party size and phone number
- Send a calendar invite and a four hour reminder
- Log every conversation for review
Workflow
Receive message, transcribe and detect language, check diary, ask for missing details, confirm and write entry, send invite and reminder, and log the conversation. Start with casual voice notes and text messages and finish with confirmed diary entries and reminders.
AI and people
Use speech recognition and language models to interpret casual multi language requests and hold a short conversation. Keep the diary as structured data. A human owner reviews the conversation log and can override any booking before it is used.
Screens
Key screens: Diary view, conversation log, rule settings. Use a calendar grid as the main screen, with a side panel showing the latest conversation transcript and a status badge for each booking. Let the owner edit a booking directly or add blocked days. Show a weekly summary of covers handled. In this product, the first view is diary view, followed by conversation log and rule settings.
Admin
Owner account per venue, conversation logs, booking versions, override permissions, blocked day rules, and an audit trail of every change.
03Market gap
Alternatives buyers use today
Paper diaries, shared spreadsheets, or staff answering calls and WhatsApp manually. This differs by removing the need for any app, portal or POS integration and by logging every conversation.
Where this wins
The more conversations the agent handles, the better it learns each venue's rules, table layouts and regulars' preferences, making it harder for a competitor to match that local knowledge.
04Why now
Hospitality and Events teams are adopting AI for exactly this kind of repeatable work, and the cost of language and vision models has dropped far enough that a narrow, reviewed workflow pays back quickly. The buyer already feels the problem: restaurants still take most bookings by phone or WhatsApp, forcing staff to interrupt prep, write on paper and double book when the diary is not checked.
05Proof & signals
Channels where buyers gather: Local restaurant associations, WhatsApp groups for hospitality owners, and direct outreach to neighbourhood bistros.. Metrics that prove it works: Two measurable outcomes: reduction in missed calls and double bookings, and increase in confirmed bookings with reminders sent..
Paid pilot
Five restaurants run the agent for two weekends. Baseline is current missed calls and double bookings. The pilot proves value if booking count holds or rises and no double bookings occur, with the owner deciding to continue after seeing the conversation log.
06Execution plan
MVP
One city, five restaurants, one shared Google Calendar, two languages. The agent handles text and voice notes; the owner reviews the log daily. First two modules are booking confirmation and reminder sending, with manual review of ambiguous requests.
First 30 days
Week 1: Build the WhatsApp agent connected to a shared Google Calendar in two languages. Week 2: Onboard five restaurants and run the first weekend. Week 3: Measure booking count and missed call reduction. Week 4: Refine the clarifying question flow and present results to the pilot group.
After the pilot
After the paid pilot, automate waitlist filling, birthday follow ups, weekly occupancy summaries, and learning the owner's rules from the conversation log without a setup call.
Retention
The agent keeps earning a monthly fee by handling every booking and reminder; the owner stays because the phone is quieter and no shows drop.
Integrations
WhatsApp Business API, Google Calendar, a simple spreadsheet, and later a web grid and POS systems.
07Investment and running costs
| Phase | Scope | Time | Budget |
|---|---|---|---|
| MVP | One buyer segment, one recurring use case. Manual review in the loop. | 2 days | $5,000 |
| Paid pilot | Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers. | 3 days | $4,500 |
| Full product | Self-serve onboarding, billing, monitoring and the wider integration set. | 5 days | $6,500 |
| Total | $16,000 | ||
| Running | Hosting | AI usage | Total a month |
|---|---|---|---|
| MVP and paid pilot (about 3 customers) | $30–$60 | $40–$90 | $70–$150 |
| Full product (about 50 customers) | $110–$210 | $280–$560 | $390–$770 |
Revenue model to test
Test three tiers: USD 99, 199 and 349 per month based on monthly covers handled, not features. Base tier includes the agent and calendar.
Cost drivers
WhatsApp Business API fees, speech recognition and language model usage per message, and a setup call with each venue.
Safeguards
The agent must not accept bookings outside opening hours or for blocked days, must never cancel a booking without owner approval, and must log every conversation for the owner to review. It must not sound pushy or robotic with regulars.
Take it further
Solution blueprint, rewritten from an earlier Nexibeo concept. Demand, pricing, build scope and integrations are working assumptions, not verified market findings. The MVP and the paid pilot exist to confirm them for your business before the larger build.