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 Avatar Creator — where appearance, brain, and voice components are configured
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
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
Schema visualiser — showing the three tables: datasets, unwpp_population, and hba1c_synthetic
Table editor — unwpp_population table with 2,646 records of Caribbean demographic health 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
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.