CaribDX is an interactive health news reader avatar, accessible at caribdx.com. The system combines a conversational AI avatar with a live data pipeline to deliver Caribbean health news updates through a natural, voice-driven interface. Below is a walkthrough of the product — first a live demo, then a full back-end technical overview.

Watch · Product Demo
CaribDX in Action
Watch · Technical Walkthrough
How It Works: Behind the Scenes

Section 01

Avatar Platform — Trulience

The avatar is built on Trulience and serves as the primary user-facing interface. Three AI components are configured within Trulience to handle conversation, input, and output:

  • Language model: Llama, hosted on Groq
  • Speech-to-text: Deepgram — transcribes user speech to text in real time, chosen for accuracy and cost efficiency
  • Text-to-speech: ElevenLabs — generates the avatar's spoken responses using a Caribbean female voice, regarded as the industry standard for voice quality
Trulience homepage — the interactive avatar platform powering CaribDX
Trulience homepage
Trulience Avatar Creator — where appearance, brain, and voice components are configured
Trulience Avatar Creator dashboard
Section 02

Function Calling & Workflow Trigger

When a user asks the avatar for a Caribbean health update, a function attached to the avatar fires a webhook call into an n8n automation workflow. This workflow handles data retrieval and story delivery, returning the response through to the avatar for playback on the front end.

n8n workflow — CaribData News Aggregator: Webhook → Static Stories → Writing AI Agent → Respond to Webhook
n8n CaribData News Aggregator workflow
Section 03

Data Layer — Supabase

Caribbean health statistics data is stored in a Supabase open-source database. The schema contains multiple tables, with the core health dataset forming the primary source for story generation.

Supabase — the open-source Postgres platform hosting the CaribDX health dataset
Supabase homepage
Schema visualiser — showing the three tables: datasets, unwpp_population, and hba1c_synthetic
Supabase schema visualiser for CaribDX
Table editor — unwpp_population table with 2,646 records of Caribbean demographic health data
Supabase table editor showing unwpp_population data
Section 04

Data Analysis & Story Generation Pipeline

The pipeline from raw data to avatar-ready stories runs as follows:

  • A Python function performs data discovery and analysis against the Supabase database
  • Claude generates narrative health stories from the analysis output
  • Generated stories are injected via API into the n8n workflow as static story content
  • When a user query arrives, n8n retrieves the relevant story and returns it through to the avatar

Execution logs within n8n provide a full historic record of workflow runs and story outputs.

CaribDx Automated Data Intelligence Pipeline — three-phase process: data discovery (Supabase), AI story generation (Claude Sonnet), and n8n workflow injection
CaribDx automated data intelligence pipeline diagram
Section 05

End-to-End Flow

User speaks Deepgram STT Llama on Groq Function call n8n webhook Supabase + Python + Claude ElevenLabs TTS Avatar responds

A daisy chain of purpose-built, best-in-class tools — delivering a conversational health news experience for the Caribbean.