CallSara

Revolutionizing healthcare operations with AI - automates scheduling and follow-ups, saving 2 hours daily.

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Appointment Scheduling
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Healthcare AI
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Patient Engagement
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About CallSara

About CallSara

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CallSara revolutionizes healthcare operations with AI agents that automate repetitive tasks like scheduling and follow-ups, saving staff approximately 2 hours daily. Based in New York, they've automated over 100,000 hours of manual tasks and recovered millions in lost revenues. AI agents Sara, Ryan, and Lilly handle appointments, payments, pre/post-op engagement, and care gaps. HIPAA-compliant and SOC 2 certified with EHR integrations.

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Confidential: Total Pain Solutions
Confidential: Stemmee Surgery Center
Falcon Family Orthodontics
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Appointment SchedulingHealthcare AIPatient Engagement

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Total Pain Solutions logo
Business Case

Achieved 100% Automated Patient Interactions and More Proactive Engagement

Total Pain Solutions

Total Pain Solutions faced a heavy burden managing patient communications manually. Staff had to repeatedly call patients to share information and follow up. This reactive approach made it harder to engage patients at the right time. The practice needed a way to improve communication without adding more strain to the team. The clinic deployed an AI healthcare communication platform to automate patient interactions. The implementation handled patient-facing communication so patients received information when they were already thinking of reaching out. This enabled the practice to shift from reactive outreach to a more proactive communication model. The practice reported that patient interactions were completely automated. Patients received information more promptly, which supported more proactive engagement. Patients also appreciated the improved communication and reported higher satisfaction with the experience.

Key Results
  • 100% automated patient interactions

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Healthcare
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Machine Learning
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Nov 5, 2024
Self Reported
Stemmee Surgery Center logo
Business Case

Reduced Patient Calling Time from 5 Days to 2 Days

Stemmee Surgery Center

Stemmee Surgery Center faced a time-consuming patient calling workload. Staff had to call every patient multiple days and multiple times in a row when patients did not answer. This created delays in completing reminder and follow-up outreach. The team implemented an AI-based automation solution for patient reminders and follow-ups. This approach automated routine patient interactions so outreach could continue without repeated manual calls. It reduced the need for staff to spend multiple days attempting to reach each patient. As a result, the center cut patient calling time from 5 days to 2 days. This reduced the effort required to complete outreach cycles and improved how quickly reminders and follow-ups were delivered. Staff no longer needed to repeatedly call patients over many consecutive days.

Key Results
  • 5 days to 2 days calling
  • 60% time reduction

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Healthcare
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Oct 25, 2024
Self Reported
Falcon Family Orthodontics logo
Business Case

Achieved 20+ Language Patient Outreach With Proactive AI Workflows

Falcon Family Orthodontics

Falcon Family Orthodontics needed a better way to engage patients throughout treatment and avoid gaps in communication. Patient engagement was often overlooked, which risked patients not feeling cared for, listened to, or understood. The practice wanted a more proactive, consistent communication approach. The team implemented AI-driven workflows to proactively communicate with patients. The solution automated patient interactions so patients received information right when they were thinking of reaching out. This helped the practice shift from reactive responses to proactive outreach. The implementation transformed how the practice communicated with patients across their treatment journey. Patients were proactively contacted so they felt cared for, listened to, and understood. The workflows improved consistency and timeliness of patient interactions, supporting stronger engagement.

Key Results
  • 20+ languages supported

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Healthcare
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Machine Learning
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Sep 30, 2024
Self Reported
Nephrology Group in Dallas logo
Business Case

Reduced Call Handling by 75% and Hired Fewer Staff

Nephrology Group in Dallas

A nephrology group in Dallas faced heavy inbound patient call volume that pulled nurses and medical assistants away from clinical work. Their existing IVR experience felt robotic and ineffective for patients. The team needed a way to handle calls without expanding headcount. They deployed AI agents to manage inbound and outbound patient calls and automate routine interactions. The implementation focused on removing nurses and MAs from day-to-day call handling while still involving staff when triage required it. The approach enabled more natural patient interactions than traditional IVR. The practice reported that nurses and medical assistants were almost freed from handling calls, stepping in primarily when the system triaged to them. They hired fewer people as a result of offloading call work. The solution handled 75% of phone calls, supporting smoother patient communication at scale.

Key Results
  • 75% phone calls handled

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Healthcare
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Healthcare Staffing
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Aug 20, 2024
Self Reported

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