AI Voice Dispatcher
Answers calls naturally, gathers trip details, confirms information, and handles common booking questions.
TaxiFlow AI is Faimara’s AI voice-dispatch and booking platform concept for taxi and passenger-transport companies. It is designed to answer calls, collect trip details, confirm bookings, coordinate with dispatch systems, and escalate exceptions to a person.
Disconnected customer and staff workflows create avoidable friction.
Each implementation is scoped around the business’s real process, approved systems, customer experience, and human-control requirements.
Answers calls naturally, gathers trip details, confirms information, and handles common booking questions.
Structures pickup, destination, passenger count, vehicle needs, scheduling, and contact details.
Transfers uncertain, sensitive, high-value, accessibility, complaint, or emergency-related calls to a person.
Can be designed to pass confirmed requests into an existing dispatch workflow or browser-based operator console.
Supports confirmation, vehicle status, delay notifications, and common service questions.
Tracks call reasons, abandoned calls, booking conversion, escalation patterns, and service demand.
Explore interactive concepts and case studies designed to show how the customer or operational experience could work.
Start as the passenger. Click Call Acme Taxi, speak naturally to TaxiFlow Voice AI, confirm the ride, and watch Booking AI hand the request directly into the Dispatch AI workflow.
Pricing is scoped in Canadian dollars. Final cost depends on call volume, phone configuration, languages, dispatch integrations, messaging usage, fleet size, and support requirements.
For taxi companies that want to validate the customer and dispatcher experience before connecting live systems.
For operators ready to test AI-assisted phone booking on a defined workflow with human oversight.
For fleets ready to connect approved booking, dispatch, passenger messaging, and operational workflows.
For multi-company or multi-location operators that need one governed dispatch intelligence layer.
Faimara’s recommended path is to understand the current process, identify a measurable bottleneck, deploy a controlled pilot, and expand only after results are reviewed.
The AI answers with the company’s approved greeting and service area rules.
It collects pickup, destination, timing, passenger, and vehicle requirements.
The caller hears the important trip details repeated back for confirmation.
The request is sent to the approved dispatch workflow or operator queue.
A person takes over when confidence is low or company policy requires it.
Managers review booking volume, missed opportunities, escalations, and call trends.
A discovery conversation is used to validate technical feasibility, business fit, risks, and the smallest useful pilot.
A production deployment can be designed for continuous availability, subject to telephony, hosting, support, escalation, and business-continuity requirements.
Modern speech systems can handle many accents, but no system is perfect. The workflow should confirm critical details and transfer uncertain calls to a human.
Potentially. Integration depends on the dispatch provider’s APIs, webhooks, database access, or supported workflows. This is validated during discovery.
Company policy should route complaints, safety concerns, medical emergencies, and uncertain situations to trained human staff or appropriate emergency services.
The greeting, tone, supported languages, prompts, escalation rules, and service information can be configured within technical and legal limits.
Tell us what happens today, where the process breaks down, and what a successful outcome would look like.