By 2030, 80 million Americans will be over 65. We're building the infrastructure to keep grandma home.
Zingage builds AI agents that automate back-office operations for the largest home care companies in America — intake, scheduling, care coordination, compliance, patient engagement. All of it.
Seven figures of new ARR every month. Partnerships with the largest platforms in the industry. ~20 people. Based in New York City.
From a live deployment — 2,632 calls/week · 97% containment · <10s response
01 / WHO WE ARE
People who picked the hard problem.
Ex-Uber, ex-Ramp, ex-Citadel. People who could be at any company in tech — and chose the hardest problem nobody else wants to touch. Not because they ended up in healthcare by default. Because they looked at 80 million aging Americans and decided someone has to build the infrastructure. Might as well be them.
TEAM FROM
BACKED BY
~20 people. Everyone either builds or sells — usually both. The GTM person writes SDR agents. The engineer presents to the customer's board. Nobody watches from the sidelines.
02 / WHAT WE'RE BUILDING
The largest home care provider in the Pacific Northwest called us.
One deployment, start to finish. This is the job.
50+ branches across three states. 4,000 caregivers. 5,000 patients. Grandmothers recovering from hip surgery. Veterans with chronic conditions. Disabled adults who need daily help just to stay in their own homes. The people nobody builds software for.
Every day, 10,000 Americans turn 65. The demand for home care is growing faster than any other segment of healthcare — and the back office runs on phone calls, spreadsheets, and one coordinator who hasn't taken a day off in two years. Not because she's bad at her job. Because you can't hire and train coordinators as fast as the aging population grows. Human labor doesn't scale that way.
Monday, 2:14 PM
A hospital discharge planner calls about Margaret, 82, recovering from a hip replacement. She needs home care starting Wednesday — a nurse for wound checks, an aide for daily living. The discharge planner is calling five agencies. Whoever picks up first wins.
Before Zingage, this call goes to voicemail. The coordinator is on the other line. She'll call back in an hour, maybe two. By then, Margaret is someone else's patient.
Now the AI answers on the first ring. It captures the referral — diagnosis, insurance, physician, address, care needs. Checks caregiver availability against Margaret's location and schedule. Confirms placement. Four minutes. The discharge planner hangs up. Referral secured.
She hadn't taken a vacation in two years.
The scheduling coordinator manages 400 caregivers across the region. No backup. When she's out sick, the operation stalls. She isn't struggling because she's bad at her job — she's doing the work of nine people. She's their best person and there's only one of her.
Margaret needs five visits this week across two disciplines. The AI builds the schedule overnight. Matches a nurse by language and certification. Matches an aide by proximity and availability.
Thursday, 3 AM. An aide calls out sick. The agent picks up, checks 73 potential replacements against weekend availability, med training, Hoyer lift certification, gender preference, and a “do not call until 11 AM” restriction on one caregiver's profile. It assigns the replacement correctly to both ADL and IADL sub-shifts. Confirms with the caregiver. Updates the schedule. Notifies the family. Nobody was woken up.
“I actually ate lunch at my desk today instead of on the phone. That hasn't happened in months.”
— Scheduling Coordinator
3 weeks to close. 10 branches per week.
The deal closed in three weeks. An FDE flew to the first wave of branches. Four went live in week one: 1,979 calls answered, 2,632 scheduling issues resolved autonomously. That's 370 coordinator hours — the equivalent of nine full-time schedulers. Except you can't hire nine coordinators in a week. You can't even hire one.
The AI was live in seven days. Seven product improvements shipped in six — each one from observing the system in the field. A deaf client's profile wasn't flagged. An Oregon Medicaid authorization had an edge case. A caregiver had a “do not call until 11 AM” restriction that the old system didn't enforce. Fixed. Shipped. Live.
By week five, all 50+ branches were running. Missed clock-ins down 80%. Zero authorization expiration surprises. Audit time from hours to minutes. The AI catches things on Monday that humans used to catch on Friday.
“We've been trying to hire our way out of this for five years. You gave us nine coordinators in a week.”
— Regional Director
03 / PROOF
Don't take our word for it.
Anthropic, ElevenLabs, and the sharpest analyst in healthcare AI have all written about the work. Read theirs before ours.
How Zingage automates care coordination for 400+ agencies
How Claude powers the reasoning layer behind staffing, care coordination, and compliance — and cut after-hours labor 82%.
Why home care needs an AI operator, not another workflow tool
An independent deep dive on why home care's operating layer is broken — and why fixing it takes an operator, not another workflow tool.
Zingage supports 3X more home care calls with ElevenAgents
How Zingage runs 24/7 phone coverage that knows when to handle a call autonomously and when a human needs to hear it.
04 / THE BUILDERS WE'RE LOOKING FOR
The kind of builder this needs.
Read these as a filter. If they sound exhausting, this isn't your company. If they sound obvious, keep going.
CUSTOMERS FIRST
“Every line of code now has a patient on the other end. A race condition isn't an edge case — it's a missed visit.”
We deploy to customer sites. We shadow schedulers. We watch the system run. Then we ship improvements from what we observe.
VELOCITY
“7 product improvements in 6 days. Every one from sitting in a branch office watching the system run.”
New enterprise customers every month. Partnerships launching with the two largest platforms in home care. The pace is the product.
IN-PERSON, IN THE ARENA
“You can't build for the real world from a laptop in your apartment.”
We work together in New York City. We fly to customer sites. The best ideas come from being in the same room — and from being in the field.
EXTREME OWNERSHIP
“We don't make excuses. We don't blame anyone or anything.”
You'll own entire deployments end-to-end. Fly to the customer, build the integration, present to their board, ship product from the field.
05 / LIFE HERE
In person, on purpose.
Soho office, long tables, late dinners. The perks exist so the work can stay the main event.
Real equity
Competitive base and meaningful ownership. If this works, it should work for you.
Equipment stipend
Whatever setup makes you fast.
Luxury gym membership
We work in health care — yours counts too.
Lunch daily, dinner late
Lunch every day. Dinner when work runs past dark — big fan of late-night jams!
Time off as needed
Take what you need. We measure output, not hours at a desk.
Soho office rituals
Happy hours, poker nights, and builder events.
You can tell a lot about a company from its snack shelf. Ours:
06 / OPEN ROLES
If you read this far, you're probably our kind of person.
Three roles, all founding scope, all in New York. Apply on Ashby — five minutes, and a human reads every application.
Forward Deployed Engineer
Deploy AI agents inside the largest home care companies in America. Build the integration on-site, ship product the same week, watch it run.
New York City
VIEW ROLE →Deployment Strategist, Enterprise
Embed with home care agencies. Own the account from signed contract to scaled adoption. The FDE builds it — you make it stick.
New York City
VIEW ROLE →Deployment Strategist, SMB
Run a portfolio of 10–15 SMB home care agencies through deployment and adoption. Go wide where the Enterprise DS goes deep.
New York City
VIEW ROLE →“We left jobs people don't leave to build infrastructure for the people nobody builds for. If that trade makes sense to you, we should talk.”
— Daniel Tian & Victor Hunt, founders of Zingage