Redi
AI-Powered Patient Preparation
How we designed and built an intelligent patient intake assistant that transforms the doctor-patient experience in under 5 minutes.
How we designed and built an intelligent patient intake assistant that transforms the doctor-patient experience in under 5 minutes.
Context
Every day, millions of people walk into medical appointments feeling uncertain, unsure what to say, what to ask, or how to describe what they're experiencing. The result is a lose-lose: patients leave with unresolved doubts, and physicians spend valuable consultation time gathering basic information rather than delivering care.
REDI is a mobile application built by Xmartlabs to solve exactly this problem. Through a guided conversation, it helps patients think through what they want to communicate before walking in: what they're feeling, since when, and what they actually want to ask their doctor. The output is a clear, personalized list of questions the patient owns and brings to the appointment, built in under 5 minutes.
It was designed for any patient who wants to make the most of their consultation, especially those who tend to leave wishing they had said or asked something different. The experience is deliberately calm and approachable, built to make you feel ready rather than anxious before you walk through that door.
"REDI doesn't replace the doctor. It makes the patient a better participant in their own care, so the consultation can focus on what matters."
Problem
Patients arrive at consultations without having organized their thoughts, forgetting key symptoms or the timeline of when they started. In a 10-minute consultation or less, this matters enormously.
All of this can mean delayed diagnoses, poor treatment adherence, and an erosion of trust between patients and the healthcare system. When patients arrive without context, physicians also lose valuable information that would otherwise inform better, faster clinical decisions. Structured patient preparation creates value at every level of the system.
Solution
REDI was built around two core capabilities: an intelligent patient intake flow that prepares users before their appointment, and an ambient AI module that captures and processes what happens during it.
Patient Intake: How it works
The intake experience was designed to feel different from a standard health app. Heavy investment went into animations, gradients, and interaction design — including haptic feedback and a custom onboarding matrix — to reduce pre-appointment anxiety rather than amplify it. The goal was that going to the doctor could feel like something you feel prepared for, not something you dread.
Ambient AI: Architecture
The ambient module allows patients to record their consultation, with the physician's consent — a step built directly into the UX. The recording is processed securely and ephemerally through a cloud pipeline, then mapped by a language model against the questions the patient prepared beforehand.
The result: a structured summary of what was discussed, linked to your own questions. No need to remember everything under pressure.
Results
REDI was built as a proof-of-expertise product — a deliberate investment to demonstrate real capability in healthcare AI, not just describe it. The results are both technical and strategic.
The ambient AI module in particular proved the ability to ship production-grade audio processing pipelines with healthcare-appropriate security constraints — directly applicable and ready to be adapted to real clinical environments.
Conclusion
REDI is a demonstration of what it takes to build AI products in healthcare well. Not just technically, but with the discipline to think about trust, privacy, user anxiety, and clinical integrity at every step of the design process.
The combination of disciplines required — ML engineering, mobile UX, clinical workflow understanding, privacy architecture, and user research — is exactly what differentiates a serious healthcare AI partner from a team that has simply connected a health app to a language model API.
For healthcare organizations looking to improve patient intake, reduce administrative load, or bring ambient AI into their clinical workflows, REDI is both a proof point and a starting line. The architecture, research methodology, and design patterns are repeatable and ready to be adapted.