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Case study | Claude Platform

How Zingage automates care coordination for 400+ home care agencies with Claude

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Industry:
Healthcare
Company size:
Startup
Product:
Claude Platform
Location:
North America
82% reduction
in after-hours labor costs at one Medicaid agency
Under 40 minutes
from caregiver call-out to confirmed replacement

Home care is a 24/7 operation that runs on phone calls, last-minute staffing changes, and complex regulatory compliance. Zingage is an AI agent platform built specifically for home-based care that automates the operational back office for agencies across private pay, Medicaid, hospice, and skilled nursing models.

With Claude powering its reasoning layer, Zingage delivered:

  • 82% reduction in after-hours labor costs at one Medicaid agency, with shift coverage maintained at 98%
  • 35% biweekly revenue growth within six months of deployment at a private pay agency, from $96K to $130K
  • Average issue resolution under 5 minutes, down from 20–30 minutes of manual coordination
  • 4,000 to 8,000 managed care hours per week at one agency, with the same team size
  • 97%+ automation rate on targeted workflows once fully deployed

The challenge

<40 minutes

from caregiver call-out to confirmed replacement

Staffing crises at midnight, with no one to call

Before Zingage, home care agencies managed round-the-clock operations with overextended teams. When a caregiver called out sick for a night shift, a manager had to wake up, manually check the electronic medical record for available replacements, call ten caregivers one by one, get seven voicemails, and document the entire process for Medicaid compliance. “Agencies had managers sleeping next to their phones, running five-person on-call rotations costing $300K or more per year just to fill last-minute call-outs,” said Victor Hunt, CEO at Zingage.

The consequences of missed shifts were serious. No-call, no-shows often went undetected until a client’s family called to ask where the caregiver was. Overnight calls from clients went to voicemail and sat there until morning. And every interaction, schedule change, and incident needed to be documented correctly in the EMR for audit readiness and fraud prevention—work that fell on already-strained staff.

“Caregivers calling out are often stressed, embarrassed, or dealing with a genuine emergency, and clients’ family members are scared,” Hunt said. “The AI has to meet people where they are emotionally, not just process a transaction.”

The solution

Claude for Healthcare

Claude helps healthcare organizations move faster without sacrificing accuracy, safety, or compliance. Less administrative work, more time with the people you serve.

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Claude for Healthcare

Claude helps healthcare organizations move faster without sacrificing accuracy, safety, or compliance. Less administrative work, more time with the people you serve.

Claude for Healthcare

Claude helps healthcare organizations move faster without sacrificing accuracy, safety, or compliance. Less administrative work, more time with the people you serve.

A zero-defect environment required a different kind of AI

Healthcare raised the bar for what Zingage needed from its underlying model. The platform handles protected health information, operates under HIPAA requirements, and takes irreversible actions in production systems: updating medical records, committing caregivers to shifts, and flagging potential abuse incidents.

“We’re not integrating a chatbot,” Hunt explained. “We’re deploying agents that take consequential action in production systems.” 

Zingage evaluated both Sonnet 4.5 and Opus 4.5, and found Sonnet offered the best balance of cost, quality, and latency for the majority of its workflows. Claude stood out for its structured tool calling, which gave Zingage the precision to orchestrate across an EMR, a phone system, and multiple communication channels while keeping PHI properly contained. 

Claude’s contextual reasoning also enabled Zingage to build agents that weigh genuine tradeoffs—like whether to contact a dementia patient’s family versus silently restaffing—rather than pattern-matching to the most common response. “Building on Claude was a different experience than working with other models,” Hunt said. “The reasoning capability meant we could give our agents genuinely complex, ambiguous situations and trust that they would navigate them sensibly.”

How Zingage coordinates care in real time

Zingage operates inside the agency’s electronic medical record: reading caregiver profiles, writing shift notes, updating schedules, and posting visit documentation directly in the systems agencies already use. Because every action happens natively in the EMR, it's immediately visible to the agency's existing workflows and audit systems, with no synchronization layer to introduce errors or delays.

A real example illustrates the system in action. At 1:45 AM, a caregiver at a private pay agency called to say she couldn’t make her morning shift. Zingage’s voice agent answered, recognized the caregiver, confirmed which shift was affected, and passed the details to its coordination system.

Within minutes, Zingage had queried the EMR, identified the patient’s care requirements, and began outreach, texting 23 caregivers and making AI-powered phone calls to qualified replacements. By 3:36 AM, a replacement was confirmed, assigned in the EMR, and shift notes were posted. The agency’s team arrived to find the problem already solved.

A more complex scenario shows the reasoning at work. A patient fell at home on a Saturday evening, and after EMS responded and cleared her, she refused hospital transport. Zingage escalated to the on-call administrator, and when no response came, made a judgment call: a fall requiring EMS, an elderly patient home alone—that warranted notifying the patient's son. Zingage coordinated a wellness check, updated the family, and documented every step. Fifty-six minutes, zero human administrator involvement.

The system handles multilingual calls natively, detecting language directly from the caller’s speech. English and Spanish are fully live, with additional languages in development.

“When the underlying reasoning is strong, the weakest link quickly becomes the instructions you give it,” Hunt said. “That pushed us to get much more rigorous about how we document workflows and edge cases, which ultimately made the whole system better.”

in after-hours labor costs at one Medicaid agency

82% reduction

in after-hours labor costs at one Medicaid agency

The outcome

Agencies shift from reactive to strategic

The impact shows up across cost, revenue, and capacity. One Enterprise Medicaid agency cut after-hours labor costs by 82% while maintaining 98% shift coverage, replacing a $300K-per-year on-call rotation at a fraction of the cost. A Senior Helpers franchise grew biweekly revenue by 35% within six months, because responding immediately to every client inquiry—including after hours—captured business that previously went to voicemail or a competitor.

One agency owner who had recently lost her Director of Operations came into the office one morning to find a new overnight shift on the schedule that nobody on her team had added. A client had called after hours needing help. Previously, that call would have gone to voicemail. Instead, Zingage answered, found a qualified caregiver, confirmed availability, and wrote the shift directly into the EMR. Twelve new billable hours on the schedule, and the owner wasn’t woken up.

The most consistent change customers describe is operational: their teams stop firefighting and start planning. “The people running these agencies can redirect their energy toward growing the business and improving care quality rather than putting out fires,” Hunt said. “Agencies can now run true 24/7 operations without burning out their teams.”

What’s next

Zingage is expanding beyond care coordination into every major operational function of a home care agency: front-office intake, recruiting, client engagement, compliance monitoring, and revenue cycle management. The goal is a connected system that covers the full lifecycle of care delivery, from the moment a caregiver applies to the moment a shift is billed.

“Running Claude in production at scale every day has sharpened our own thinking about what good agentic AI looks like,” Hunt said. “That compounds over time in ways that are hard to overstate.”

“Agencies can now run true 24/7 operations without burning out their teams.”
Victor Hunt
CEO, Zingage

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