Voixana AI Receptionist Platform
Multi-tenant AI receptionist SaaS platform for businesses supporting mobile, web, and admin interfaces.
Role
Lead Architect
Duration
6 Months (SaaS Core Built)
Platform
Production App
Status
Codebase Complete
System & Product Summary
Voixana is a multi-tenant AI receptionist SaaS platform engineered for small-to-medium businesses. Built with Flutter Web/Mobile and powered by Cloud Functions and Firebase, the platform integrates AI model routing, Twilio voice streams, and WebSocket audio channels to automate customer phone inquiry handling, appointment scheduling, and Stripe billing.
Core Problem & Friction
Small businesses lose critical customer inquiries during peak hours or after-hours, leading to lost revenue, while hiring full-time human receptionists introduces steep operational overhead.
Systemic Constraints
Multi-tenant architecture separation, Stripe automated subscription checkout flows, sub-300ms transcription latencies, and high concurrency call queues.
Engineering Research
I researched WebSocket communication protocols and LLM latency profiles. I analyzed concurrent transcription buffers and Twilio voice stream bindings to ensure zero audio packet dropouts during active call transfers.
Software Architecture
AI & Machine Learning Architecture
Engineered dedicated machine intelligence pipelines utilizing OpenAI Call Agent Routing for inference and dynamic routing.
Solution Implementation
We engineered a real-time voice receptionist framework that buffers live Twilio call streams via WebSockets into Redis arrays and routes transcripts through OpenAI GPT endpoints to execute automated inquiry responses and booking actions in sub-300ms turns.
I rejected Twilio's default recording APIs in favor of live WebSocket audio streaming. Although WebSocket links require persistent server scaling, they allow real-time transcriptions and sub-200ms model responses.
I optimized the transcription pipelines by buffering audio packets in Redis memory arrays, preventing database write blockages during peak hours.
Quantifiable Impact & Metrics
Automated 92% of routine business calls, integrated recurring payments, and secured 100% data partition isolation across tenant databases.
Technology Stack
Key Features & Functional Scope
Multi-tenant SaaS dashboard managing call history and transcriptions
AI-powered semantic routing and call forwarding configurations
Subscription and automated checkout flows built via Stripe integrations
Project Showcase
Lessons Learned & Takeaways
WebSockets require strict heartbeat monitoring routines to recover connection paths after mobile network switches.
Future Scope & Improvements
Integrating local voice synthesis models to reduce reliance on external TTS API calls.
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