Driving Personalized Healthcare Through Intelligent Agentic Systems
The client is a US-based healthcare technology company focused on proactive, continuous care. Their platform connects individuals with licensed providers through data-driven engagement, remote monitoring, and integrated care delivery across healthcare organizations and payer-led programs.
The client had a strong data-capture infrastructure across EHR data, BLE-enabled medical devices, and manual logging. However, it lacked an intelligent, consumer-facing experience that could turn raw health signals into ongoing guidance, better engagement, and scalable operations across a multi-tenant platform.
Fragmented Data Ecosystem
Device streams needed validation and normalization before they could be trusted for clinical use. The platform also had to filter irrelevant inputs, especially in shared-device scenarios.
Low Engagement in Manual Logging
Users could log meals, workouts, and medication, but the process felt mechanical. Engagement dropped over time, and lifestyle data became incomplete.
Coaching Without Context
The platform supported surveys and audio-visual interactions, but guidance lacked memory and personalization. Advice often felt generic because prior context was not carried forward.
Absence of Conversational Experience
Users needed more than dashboards. They needed a conversational interface that could understand intent, respond naturally, and adapt to individual patterns.
Operational Complexity Across Tenants
With each service provider operating as a tenant, administrators needed stronger oversight for user tagging, device provisioning, and program alignment.
Coditas designed and delivered a GenAI-powered experience layer that transformed passive monitoring into active, contextual care. The focus was sustained user engagement, trusted data, and operational control across a multi-tenant model.
Context-Aware Smart Coaching
A personalized assistant experience interpreted health signals, answered user questions, and adapted guidance based on current metrics and prior interactions.
Conversational Logging and Behavior Tracking
Natural language logging replaced form-heavy inputs, making it easier for users to consistently record meals, workouts, and medications over time.
Signal-to-Insight Data Foundation
We implemented data validation and filtering so only verified device inputs were translated into clinically relevant signals. This improved trust in what providers saw downstream.
EHR and Care-Delivery Integrations
Integration pathways strengthened clinical visibility, enabling providers to access verified data and trigger timely follow-ups when required.
Multi-Tenant Operations and Support Automation
Tenant-level administration and self-serve assistance reduced operational load while improving oversight for tagging, device provisioning, and program alignment.
The platform improvements translated into measurable gains across engagement, data quality, and operations.
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3x increase in daily user engagement through conversational logging and real-time insights
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40% reduction in manual support tickets through GenAI-led product support and assistance
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60% improvement in data quality by filtering irrelevant inputs and validating device data
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Up to 35% faster time-to-intervention through real-time alerts and continuous monitoring workflows
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Adopted by 6+ enterprise tenants with tenant-specific configurations and a subscription model
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80% increase in user-reported satisfaction scores from more personalized, context-aware experiences
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Backend readiness for 1M+ device connections through scalable ingestion and event handling
Our engagement helped the client move from data capture to continuous, personalized care. Coditas delivered the GenAI-powered experience layer and the platform controls needed to improve engagement, raise data trust, and scale across enterprise tenants.
If you are building a connected-care platform and want a workflow-ready GenAI layer that can scale across tenants and care programs, Coditas can help.
Get in touch with our experts to discuss a customized solution.




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