Report extraction
AI reads heterogeneous blood reports and extracts values, units, dates, and reference intervals.
Team & AI Product Architecture
An AI-native biomarker intelligence platform built for scalable cloud delivery.
Founder-led by Dr. Alex Ho Chin Guan, Exia Bio combines laboratory science, biomarker logic, AI document extraction, and cloud architecture.
Launch posture: Exia Bio is being positioned as a production-oriented digital service for launch, with staged automation, manual quality control where appropriate, and a Google Cloud architecture designed to support scale beyond founder-led operations.
AI-first product
Why Exia Bio is AI-first
AI is not used only as a productivity tool. It is designed into the product workflow itself.
Biomarker normalization
Messy report data is converted into structured biomarker records.
Missing-marker detection
The system identifies data gaps that reduce confidence or require targeted follow-up.
Dashboard generation
Pathway logic and biomarker maps become dashboard-ready intelligence.
Product Evidence
Dashboard, logic, and cloud-ready output.
Exia Bio is not presented as a consulting concept. The product is being built around a repeatable digital workflow: uploaded report, AI extraction, biomarker logic, and dashboard-based delivery.
Product Interface
Sentinel dashboard preview showing the intended product interface: biomarker interaction map, efficiency score, and optimization priority stack.
Dashboard Output
Current dashboard output preview showing Sentinel Index, constraint classification, and friction-zone logic.
Signal Classification Module
Biomarker-level module showing how individual markers are translated into drift, warning, and prioritization states.
Digital-native business model
Software-first delivery, not a traditional clinic flow.
Users can purchase online, upload reports, complete secure intake, select pathways, and receive dashboard-based outputs without requiring a traditional clinic visit for existing-report products.
- • Snapshot: existing report dashboard
- • Deep Map: advanced existing report analysis
- • Signal Unlock: targeted missing-marker draw
- • Baseline: new Tier 1 draw + dashboard
- • Apex: full Tier 1 + Tier 2 draw + dashboard
- • Long-term model: recurring dashboard progression and repeat biomarker uploads
Founder-led team
Current Team: Founder-led launch architecture
Dr. Alex Ho Chin Guan | Founder & Lead Architect
Dr. Ho brings scientific training in Materials Science & Engineering, laboratory experience in LC-MS and metabolomics, and business training through an MBA.
- Product strategy and commercial rollout
- Sentinel logic architecture and biomarker data model
- Cloud architecture planning and AI workflow design
- Manual QC and safety boundary design during launch
Why Google Cloud
Google Cloud is central to the scaling path.
Exia Bio expects to rely on Google Cloud infrastructure for document intelligence, serverless processing, structured biomarker storage, dashboard delivery, and AI model deployment.
Vertex AI / Document AI
Report extraction from varied lab formats.
Cloud Run
Serverless processing workers for ingestion and normalization.
BigQuery
Structured biomarker warehouse and longitudinal tracking.
Cloud Storage
Secure upload handling for reports and generated assets.
Firebase / Identity Platform
Dashboard access and user authentication path.
Cloud Logging / Monitoring
Reliability, auditability, and operational visibility.
Scaling roadmap
From founder-led launch architecture to global digital delivery.
Phase 1
Founder-led launch architecture
Production-oriented report ingestion, biomarker extraction, dashboard generation, and launch-phase manual QC.
Phase 2
Cloud automation
Automated workers, BigQuery warehouse, dashboard accounts, and pipeline monitoring.
Phase 3
Team expansion
Bioinformatics architect, full-stack cloud engineer, MLOps specialist, and clinical/dietitian advisor.
Phase 4
Global digital delivery
Support uploaded reports from multiple markets and longitudinal dashboard tracking.