The team building AI care documentation for long-term care.
How we met
Laith and Yusuf met at Cal Poly San Luis Obispo, talking about long-term care. Laith had spent time on California long-term care floors. Yusuf had watched his great-grandfather's care up close. Both kept landing on the same observation: a caregiver spends more of the shift on the chart than with the resident. CareTrace is what came out of that conversation.
Laith A.
Co-founder, CEO
Previously Bain & Company and Goldman Sachs. AI strategy and tech and pharma M&A. Finance, Cal Poly SLO.
Yusuf K.
Co-founder, CTO
Previously built AI infrastructure at a stealth physical-AI company and at DevSpot, acquired for $1M in 2026. CS, Cal Poly SLO.
Why we're building this
Yusuf's great-grandfather had Alzheimer's. He repeated himself so often it became a running joke in the family. He'd just forget what he said a minute ago. What wasn't funny was when the nurse on the next shift didn't have what he'd told the last one. Then things broke. The fix, in hindsight, was simple. Say it once at the bedside. Keep it. Hand it off clean.
Laith has seen shifts on California long-term care floors. The pattern repeats: staff leave the bedside to catch up on charts, shifts run late, good people burn out and leave the profession.
A care manager on a California long-term care floor told us: 'If you don't say something and something happens and no one else knows about it, it's a legal liability.'
CareTrace is what we're building for the nurses and caregivers who would care for him today. We're piloting now and hoping to bring on more communities across the West Coast.
Operating principles.
First.
Documentation should end when the shift ends.
Staff in long-term care work 12-hour shifts, then stay late or take charts home to finish them. Paperwork after clock-out is the biggest driver of burnout in long-term care. Dictate the note at the bedside, let it structure itself as it's said, and the shift ends when the shift ends. That's what survey-ready should actually mean.
Second.
A nurse's observation shouldn't depend on her typing speed.
The best caregiver in the building isn't the fastest typist. She notices things at the bedside that rarely make it into the chart: a change in ADLs, a new bruise, a swallow that didn't go right. Typing each one takes longer than the observation itself, so most of it disappears. Said at the bedside, every detail stays.
Third.
Long-term care is not a smaller hospital.
Most clinical AI is built for acute care: a hospital stay, an outpatient visit, a fifteen-minute encounter. Long-term care is none of that. The shift is twelve hours. The resident is the same resident tomorrow, and the day after. Incident reports, Title 22 documentation, licensing surveys are LTC-native problems a hospital-grade scribe can't touch. CareTrace is built for the shift, not the visit.
Laith & Yusuf
Spend the shift on care.Not charting.
We're piloting now and hoping to bring on more communities across the West Coast. If you run a long-term care community or facility, we'd like to meet you.