JEEVHITAA -- An HCAI Ecosystem to Support Collective Care
arXiv:2512.06364
JEEVHITAA is a cross‑platform mobile system that enables coordinated, role‑aware health data sharing and verifiable information flows within permissioned care circles, using fine‑grained access control and retrieval‑augmented large language models to generate role‑specific summaries and action plans.
Abstract
Current mobile health platforms are predominantly individual-centric and lack the support for coordinated, auditable multi-actor workflows. However, in many settings worldwide, health decisions are enacted through multi-actor coordination rather than individual users. We present JEEVHITAA, a cross-platform mobile system enabling role-aware sharing and verifiable information flows within permissioned care circles. JEEVHITAA ingests platform and device data, builds layered profiles from sensors and tiered onboarding, and enforces fine-grained, time-bounded access control across care graphs. Data stays secure both within the application and the cloud. Integrated retrieval-augmented Large Language Models produce structured, role-targeted summaries and action plans, offer evidence-grounded verification with provenance and confidence scores, and support advanced insights on reports. We describe the architecture, connector abstractions, and security primitives, and report robustness evaluations using synthetic, ontology-driven data and findings from a feasibility study with real-life care circles across 9-14 weeks. We outline plans for larger multi-site evaluations focusing on operational alignment, longitudinal trust & literacy impact, and relational friction & efforts to sink into the daily infrastructure.
33 pages, 7 figures, 3 tables, 2 algorithms, 1 ontology description. Preprint of work under review