Healthcare & Pharma

Use Case / Problem Statement

Patient interactions were manual — appointment booking by phone, reminders by hand, and no digital access outside clinic hours.

• Limited access to basic guidance outside clinic hours
• Phone-only scheduling with high drop-off
• No medication or regimen reminders
• Stress and mental health support absent
• No consistent escalation for urgent cases

Solution & Development

• Symptom checker with triage guidance.
• Appointment scheduling on WhatsApp and web.
• Personalized health tips and medication reminders.
• Stress and mental wellness support flows.
• Health tracking and education FAQs.
• Emergency assistance and escalation pathways.
• Automation via n8n for confirmations and follow-ups.

Use Case / Problem Statement

Research data lived across silos with no discoverability, lineage, or governance controls.

• Manual data discovery took days
• No metadata or lineage tracking
• Duplicate analysis across teams
• Compliance policies inconsistently applied
• Analytics tools lacked clean data access

Solution & Development

• Centralized data repository with unified schema.
• Metadata management and lineage tracking.
• Tool integrations for BI and ML workflows.
• Automated governance and GDPR controls.

Use Case / Problem Statement

ML models were built but rarely reused — no standard deployment, versioning, or access layer.

• Models inaccessible to non-ML teams
• No standardized deployment pipeline
• Repeated model rebuilds across projects
• No API layer for consumption
• Manual versioning and monitoring

Solution & Development

• Central model registry with documentation and tagging.
• REST API for standardized inference access.
• Automated deployment pipeline with monitoring and retraining.
• Governance: audit trail and explainability layer.
• Integration with BI tools and Azure-hosted infra.