Research — Multimodal agentic AI for geriatric telehealth

Real-time agentic Patient-Provider care

A simple way for older adults to get everyday help by voice or chat—while care teams can follow along when it matters. Built to feel human, stay clear, and protect people's privacy.

Isometric architecture diagram: older adult on a secure call via smartphone, central Agentic Brain with memory, tools, and LLM modules, and a healthcare professional at a desktop—three interlocking puzzle pieces with encrypted links.

Hybrid voice and text conversations

Older adults interact through voice or text in the Care Companion app. An ultra low-latency agentic AI stack (about 250 ms average voice response) handles each turn with natural overlap: adaptive interruption handling, an on-device end-of-turn model so the agent does not cut in too early, and adaptive voice speed for clarity.

Ultra realistic avatar as the primary interface
~250 ms average latency voice agent with smooth barge-in
Local end-of-turn model plus adaptive pacing and tone
System overview

From real-time agent to clinical workflow

How the voice-and-video care companion connects patient experience, intelligent workflows, and secure provider tooling in one line of sight.

Architecture diagram: older adult with voice and video avatar interface, real-time AI care agent at the center with low latency and turn detection, intelligent care workflows, secure memory, care insights, and provider dashboard outputs.
Architecture diagram: care provider workspace and AI support over a live consultation, data secured in the cloud, and easy patient access across phone, tablet, and laptop.
User Experience

Ethics, privacy, and accessibility

HIPAA-aligned consent and oversight, traceable AI outputs, and encrypted sessions with no unrelated third-party analytics or ads. Open, self-hostable components keep the stack under your governance; live transcription supports users when hearing is limited.

Privacy & consent

Dual patient consent, encrypted transit and at-rest data, audit logging, and no sale of conversation data to third parties.

Open & self-hostable stack

Components and models are composed from open-source, self-hostable software so PHI and workloads can stay on infrastructure you control—not opaque SaaS you cannot audit.

Transparency for clinicians

Dashboard summaries link back to source messages so providers can verify AI-generated text.

Human in the loop

The chatbot does not diagnose; escalations and provider review keep decisions with care teams.

Voice & trust

Built for natural, private conversations

Voice and avatar tuned for clarity, with guardrails and encryption so sessions stay in environments you control. Built on open, self-hostable services for the privacy and deployment expectations of regulated care.

Adaptive interruption handling

Smooth barge-in and overlap so users are not locked into rigid turn-taking when they think aloud or self-correct.

Ultra realistic avatar interface

A lifelike avatar carries tone and attention—often easier to follow than text-only or flat UI for extended sessions.

Ultra low-latency voice agent

About 250 ms average response time so replies land in the same breath as natural conversation.

Intelligent end-of-turn

On-device end-of-turn detection cuts down on clipped sentences and premature agent talk-overs.

Adaptive voice speed

Playback pacing adjusts for clarity—slower when needed, without sounding robotic or rushed.

Secure & private connection

Encrypted sessions with no third-party data sharing for unrelated analytics, ads, or model training—aligned with stacks you can self-host when policy requires it.