Contact person: Multi-Tenant AI Voice Receptionist Suite

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Location: Greenacres, Australia

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a production-ready voice receptionist that lives both on the web and inside a companion mobile app. The system must answer inbound calls with a natural-sounding AI, recognise the caller’s voice, transcribe speech in real time, and hold a fluid NLP-driven conversation. From that conversation it should be able to capture every lead, book appointments directly into the calendars I connect, and, when required, hand customers off to a live agent without losing the context.

Because I serve multiple clients, the entire stack has to be multi-tenant. Each tenant needs its own phone numbers, call-flow rules, branded prompts, and a permission-based CRM portal where staff can review transcripts, listen to recordings, and follow up on captured leads. A high-level analytics dashboard must expose call volumes, conversion metrics, and appointment-booking rates, with the raw data exportable as CSV or via API.

Deliverables I expect:
• Cloud-hosted backend with API endpoints for voice, data sync, and webhook events
• AI pipeline combining Speech-to-Text, Voice Recognition, and NLP, deployable on AWS, GCP, or Azure
• Secure multi-tenant database, role-based access control, and audit logging
• Documentation and a short hand-off session so my internal team can operate and extend the platform

I’m happy to discuss preferred telephony providers (Twilio, AWS Connect, etc.) and any open-source frameworks you feel will speed up delivery, provided the end result is scalable, reliable, and easy to brand per tenant. If you’ve shipped similar voice or chatbot products, show me live links or repo samples so I can gauge fit." (client-provided description)