AI Medical Assistant for Families
An AI care-coordination assistant that reads prescriptions, lab reports and discharge summaries, suggests medicines, dates and instructions for the family to verify, and turns confirmed details into reminders, caregiver alerts and a shared family health timeline.
Transforming Digital Experience for Businesses & Users
Codiastic Soft Pvt. Ltd. led product discovery for an AI medical assistant that helps families coordinate care for loved ones. Family members create profiles, upload health documents such as prescriptions, lab reports and discharge summaries, and the AI extracts possible medicine names, dates and instructions — shown beside the source document — for the user to review and confirm. Only verified details become care tasks, reminders and an optional caregiver escalation, all visible on a shared family timeline that also helps prepare for the next clinician visit.
By applying modern design principles and cutting-edge software architecture, Codiastic Soft engineered a solution that dramatically improved operational efficiency while delivering a world-class user interface.
CLIENT
Family Care-Coordination Product
INDUSTRY
AI & Automation
PROJECT TYPE
AI Healthcare Product Discovery & Workflow Design
SERVICES DELIVERED
TECHNOLOGY STACK
Coordinating a Loved One's Care Without Letting AI Make Medical Decisions
Families caring for elderly parents juggle prescriptions, test reports, follow-ups and medicine schedules, often across cities. AI can organise this information, but in healthcare it must never diagnose, prescribe or silently act on its own interpretation.
Medicine instructions are buried in handwritten prescriptions and long discharge summaries
Caregivers need to know when reminders are missed — without false certainty
Health information must be shared only with authorised family members
AI extraction errors in healthcare can be harmful if not verified by a person
AI That Organises, Humans That Confirm: A Verify-Before-Activate Care Workflow
Codiastic Soft designed an end-to-end workflow and a practical use case — a daughter coordinating care for her father — with safety guardrails defined before any feature was built.
Family profiles with consent settings and authorised caregiver access
AI extraction of medicines, doses, dates and instructions shown beside the original document
Mandatory user review against clinician instructions before any care task is activated
Reminder scheduling with time zones, recurrence, quiet hours and channel preferences
Acknowledge, snooze or reschedule responses, with optional caregiver escalation if unresolved
Family timeline and visit-prep summaries with export of selected records
Core Capabilities & Key Modules
Health Document Understanding
Upload prescriptions, lab reports and discharge summaries; AI suggests possible names, dates and instructions with the source shown alongside.
Verify Before Activation
Every extracted detail is checked and confirmed by the user before it can create a care reminder — incorrect suggestions are corrected or ignored.
Smart Care Reminders
Medication, appointment, test and follow-up reminders that respect time zones, recurrence rules, quiet hours and privacy preferences.
Optional Caregiver Escalation
If a reminder is not acknowledged within the configured time, an authorised caregiver can be alerted — only when enabled and permitted.
Family Timeline & Visit Prep
Upcoming tasks, recent records and source-linked summaries in one place, with selected information exportable for the next clinician visit.
Built-In Safety Guardrails
No diagnosis or prescribing, consent with least-privilege access, and honest reminder status that never treats 'delivered' as proof a dose was taken.
Measurable Business Outcomes
Clear, Safe MVP Scope
A defined MVP — profiles, document extraction, user verification, care tasks, reminders, acknowledgement, opt-in escalation and family timeline — gave the client a focused build plan.
Safety Designed In From Day One
Human-in-the-loop verification and explicit guardrails address the biggest risks of AI in healthcare before development.
Validation Roadmap
Key assumptions — customer segment, notification channels, consent model, privacy review, pricing and extraction reliability — were identified for validation before launch.
Product Design & Interface Showcase
A visual overview of the digital interface, user experience, and architecture crafted for AI Medical Assistant for Families.
AI Medical Assistant for Families — end-to-end workflow and safety guardrails
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