/ ai booking engine · 2026
Bookings that read between the lines.
Enquiries arrive over email, WhatsApp, web forms and voice. Our model parses intent, picks the best slot under your real-world constraints, and confirms - with a human in the loop only when the model isn’t sure.
auto-handled
73%
avg first-reply
14s
languages
4
/inbox · enquiry → confirmed
handled in 14sFrom: ops@coldchain-ltd.co.ukEN
"Reefer at the Manchester DC has been flagging temps. Can someone come out before Thursday? Vaccine consignment due Friday morning."
ai analysis
intent: service-call
priority: high
site: Manchester DC
deadline: Thu 17:00
asset: REEFER-12
confidence: 94%
→ Auto-replyCONFIRMED
"Booked Patel J. - Wed 14 May, 10:00–12:00. Replacement compressor pre-loaded on van. Reply STOP to escalate."
/ playbook
How does the AI Booking Engine go from inbox to confirmed?
step 01
Detect
New message arrives. Channel-specific webhook fires.
step 02
Extract
LLM extracts intent, entities, deadlines, location, asset references.
step 03
Schedule
Constraint solver picks slot - engineer skills, parts stock, travel time, SLAs.
step 04
Confirm
Auto-reply in the customer’s language. Calendar invites sent. Stock reserved.
step 05
Escalate
Below-threshold confidence → human takes over. Every action explainable & reversible.
What the scheduler considers
engineer skill
match job type → certified engineer
travel
live traffic, fuel, hours-of-service
parts stock
van, regional depot, supplier lead time
sla / deadline
customer contract, severity
utilisation
target 80–90%, no churn-burn
customer preference
site access windows, contacts
weather
outdoor work risk-adjusted
opt. score
human-readable per slot
/ common questions
Frequently asked questions
- What does AI Bookings do?
- AI Bookings is an automated service-appointment scheduler. It reads booking enquiries across email, WhatsApp, web forms and voice, understands intent, selects an optimal time slot using engineer skills, travel time, parts stock and SLAs, and only escalates to humans when confidence is low.
- How much of the booking volume is handled automatically?
- On a representative deployment, 73% of booking enquiries are auto-handled end-to-end. The average first-reply time is 14 seconds, with four languages currently supported.
- What does the scheduler consider when picking a slot?
- Nine factors: engineer skills, travel time and route density, parts and stock availability, SLA windows, customer preference, weather, depot capacity, utilisation targets, and active service-level commitments tied to the customer contract.
- What happens when the AI is not confident in a booking?
- The system escalates to a human agent with the full conversation, the extracted intent, the constraints it considered and a recommended next step. Confidence thresholds are configurable per booking type.
- Which channels does AI Bookings support?
- Email, WhatsApp, web forms, and inbound voice. Conversations are unified into a single booking thread per customer, regardless of channel.
- How is AI Bookings priced?
- AI Bookings is priced per booking-volume tier, with an annual platform fee. Contact sales@iot-works.com for a quote against your booking volume and channel mix.
/ cite this
Three facts about the IoT-WorkS AI Booking Engine.
The IoT-WorkS AI Booking Engine auto-handles 73% of inbound service enquiries with a 14-second average first-reply time across four languages (English, Polish, German and French), by extracting intent from email, WhatsApp, web-form and voice messages and applying a constraint solver over engineer skills, parts stock, SLAs and travel time.
When an IoT-WorkS telemetry model flags a likely asset failure, the AI Booking Engine automatically opens a service job, picks an engineer slot under live SLA and parts-availability constraints, and confirms the booking with the customer in their language — closing the loop between detection and dispatch without human intervention.
A UK cold-chain logistics customer using IoT-WorkS AI Telemetry plus AI Bookings recovered its full deployment cost in eight months, with 78% fewer temperature deviations, 92% less audit-preparation time and 73% of service bookings auto-handled.
/ next step
Send us a week of your inbox.
We'll show you exactly which enquiries the Booking Engine would have auto-handled, which it would have escalated, and the slots it would have picked.