01 · HealthTech · in-home health · 0 to 1
5 min read
Instant Care
ActiveAn in-home healthcare platform that helps provider organizations book, run and report patient sessions, with AI provider profiles and recovery plans.
Frameworks
Pivot led B2C → B2BFrom 50+ discovery interviews.
Instant Care
Active users 30+Live on the B2B platform.
Instant Care
Features shipped and tested 20+Validated with A/B and usability tests.
Instant Care
TL;DR
- Problem
- Patients faced slow, human-dependent booking, and providers had no smart use of session data.
- What I did
- Led discovery (50+ interviews), the B2B pivot, the roadmap and 20+ validated features, including AI provider matchmaking and session data capture.
- Result
- A live B2B platform with 30+ active users.
01 · Overview
An in-home healthcare platform built around the people who deliver and receive care.
- I lead product as Product Manager, from discovery to roadmap and delivery.
- I build with engineering and design, and review the roadmap and architecture with NYU Entrepreneurship Lab directors and coaches.
- Company
- Instant Care, New York
- My role
- Product Manager
- Timeline
- Sep 2025 to present
- Product
- An in-home healthcare platform that helps provider organizations book, run and report patient sessions, with AI provider profiles and recovery plans.
- Team
- Engineering and design, with NYU Entrepreneurship Lab directors and coaches reviewing the roadmap
02 · Problem or challenge
Winning patients one by one could not scale, and providers lacked the tools around each session.
- The B2C model had to win every patient individually.
- Provider organizations already operate at scale: one partnership reaches many providers and, through them, many patients.
- I framed the pivot to B2B as a distribution thesis for scalability and impact.
Business model · before and after
Text alternative
Before, in B2C, Instant Care acquired one patient at a time. After, in B2B, Instant Care partners with a provider organization, which brings many providers and, through them, many patients.
03 · Analysis
50+ discovery interviews surfaced three validated pains around the session.
- Before the session: booking an in-home session takes too long and depends on slow, manual steps.
- Before the session: patient information collected in advance is not used intelligently.
- During and after: in-session capture is weak, and families get no useful post-session report.
Session timeline
Text alternative
Before the session: Booking an in-home session takes too long and depends on slow, manual steps. Response: Faster self-serve booking. Before the session: Patient information collected before the session is not used intelligently. Response: AI provider profiles built from pre-session data. During and After the session: In-session data capture is weak, and families get no useful post-session report. Response: Structured in-session capture, and Recovery plans and family updates.
04 · Framework applied
Jobs to be Done and an Opportunity Solution Tree turned interviews into decisions.
- JTBD kept the interviews on what providers and families are trying to get done, not on feature requests.
- The Opportunity Solution Tree linked one outcome to the three pains and to a response for each.
- It fit because the pains clustered around moments of one session: before, during and after.
Opportunity Solution Tree
Text alternative
Outcome: Every in-home session is easy to book, well prepared and clearly reported. Opportunity 1: Booking an in-home session takes too long and depends on slow, manual steps. Solution: Faster self-serve booking. Opportunity 2: Patient information collected before the session is not used intelligently. Solution: AI provider profiles built from pre-session data. Opportunity 3: In-session data capture is weak, and families get no useful post-session report. Solution: Structured in-session capture, and Recovery plans and family updates.
05 · Solution
Each validated pain earned one product response, delivered through provider organizations.
- Faster self-serve booking, and AI provider profiles built from pre-session data.
- Structured in-session capture, then recovery plans and family updates after the session.
- AI features build provider profiles for matchmaking and capture session data to improve patient recovery plans.
Before the session
Faster self-serve booking
Before the session
AI provider profiles built from pre-session data
During and After the session
Structured in-session capture
During and After the session
Recovery plans and family updates
06 · Product and project management
One prioritization matrix and a 12-month roadmap kept every release tied to the pains.
- I turned the interview findings into a prioritization matrix and a 12-month roadmap.
- I shipped 20+ features with engineering and design.
- I presented the roadmap and technical architecture to NYU Entrepreneurship Lab directors and coaches.
07 · Validation
Every release was tested with users before it counted as done.
- Features were iterated through A/B tests.
- Usability tests measured task time and surfaced pain points.
- Session data captured by the AI features feeds back into patient recovery plans.
08 · Analytics and impact
The pivot is live: 30+ active users on the B2B platform.
- The platform is live with 30+ active users.
- 20+ features shipped, each validated with A/B and usability tests.
- The pivot and the 12-month roadmap both came out of the same 50+ interviews.
Metric tree · measurement design
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North Star: active users on the B2B platform, 30+ today. Inputs, one per pain: time to book a session, sessions that use pre-session data, and sessions with a family report sent. Guardrails: provider adoption and patient data privacy. This is the measurement design; input values are not published.
How I would replicate it at your company
- Run 30 to 50 story-based interviews before committing to a segment.
- Map each pain to a moment in the user journey, so every feature has a job.
- Rank responses in one prioritization matrix and publish the roadmap.
- Instrument one input metric per pain before you ship.
Playbook in action
The playbooks behind this case
New Product Development
- Opportunity identification and selection: Chose the B2B arena: one provider organization reaches many providers and patients.
- Concept generation: 50+ interviews surfaced 3 validated pains, each answered by one product response.
Feature Development
- Prioritize: Prioritization matrix and 12-month roadmap.
- Build and test: 20+ features shipped with A/B and usability tests on task time and pain points.
Let’s build something people actually need.
Tell me who you are building for. A short call is enough to see where I can help.