ParkPal AI assistant bot for car park operators

A context-aware assistant on the operator's public booking site that handles parking enquiries, directions, and billing questions — resolving most of them without a human.

Before. The support team spent its day firefighting repetitive questions. Visitors bounced when an answer wasn't obvious, every booking still required a phone call or an email, and nobody had visibility into what visitors were actually asking.

What we built. ParkPal — a context-aware website assistant connected directly to the booking system and the operator's FAQ database, able to complete a booking inside the chat and hand off to a human with the full transcript when it can't.

Outcome. 85% of queries resolved on first contact, support tickets down 70%, and online bookings doubled without adding headcount. Unanswered questions feed back into the knowledge base, so coverage improves continuously. Related: AI agent development and custom software.

All case studies · Talk to our team

Frequently Asked Questions

Chatbot or Agent?

ParkPal is an AI agent, not a scripted FAQ chatbot — it can complete a booking inside the conversation and pull live data from connected systems rather than just serving pre-written answers. Genium Group connected it directly to the operator's booking system and FAQ database, letting it check availability, take a booking, and hand off to a human with the full transcript only when it genuinely can't help, which is how it resolves 85% of queries on first contact.

What Makes an FAQ Chatbot "Smart"?

A smart FAQ bot draws answers from a live, connected knowledge base and gets better from real visitor questions, instead of running off a fixed script. On the ParkPal build, Genium set up unanswered questions to feed straight back into the knowledge base, a closed-loop process that helped cut support tickets by 70% after launch.

How Does It Work?

ParkPal sits on the car park operator's public booking site and answers questions about parking, directions and billing by querying the connected booking system and FAQ database directly. When it can't resolve something, it escalates to a human agent with the full chat transcript attached, so the visitor never has to repeat themselves.

How granular is the analytics for the AI FAQ bot — can you see which questions go unanswered?

Yes — ParkPal logs every query it can't resolve and routes that data back into the knowledge base rather than discarding it. This is the mechanism behind its stated continuous coverage improvement, since operators can see the exact gaps visitors are hitting instead of guessing at them.

What's the fallback logic if the AI doesn't know the answer? Can it route to live chat?

When ParkPal can't answer a query, it hands off to a live support agent along with the full conversation transcript so context isn't lost. Genium built this fallback as the second half of a two-stage system: automated resolution first, human handoff second, which together kept 85% of queries away from a live agent entirely.

Can you A/B test different FAQ prompts or knowledge sources to improve resolution rates?

The ParkPal build didn't rely on formal A/B testing of prompts; instead Genium used a feedback loop where unresolved questions are logged and fed back into the knowledge base to improve coverage over time. For a live operator handling real bookings, that continuous correction is generally more practical than running split tests on prompt variants, since every real gap in coverage surfaces directly rather than through a sampled test group.