Hello Patient Analysis: $23M Raised

Automate patient check-ins for healthcare providers; Schedule appointments 24/7 for patient convenience; Verify insurance and collect patient information upfront; Reconnect with no-shows to reschedule visits; Facilitate targeted outreach to bring back lapsed patients

Raised $22.5M in Series A funding; Trusted by leaders in urgent care; Achieved 100% answer rates across calls and texts; 95% reduction in patient wait times reported by clients

Hello Patient's go-to-market (GTM) strategy reflects a hybrid model that combines elements of both product-led growth (PLG) and sales-led approaches. The company emphasizes the capabilities of their AI assistant, Mia, through a live demo on their homepage, allowing potential customers to engage with the product directly, which is characteristic of PLG. However, the lack of transparent pricing information suggests a sales-led approach, as potential customers may need to contact sales for further details. The website includes a "Book a Call" option, indicating a focus on high-touch relationships with healthcare providers. Customer testimonials highlight significant improvements in patient access and experience, suggesting a structured sales cycle. Overall, Hello Patient optimizes for both rapid user adoption and high-touch relationships with healthcare providers.

Hello Patient has notable clients including local clinics like Revive Med Spa and national digital health companies such as Octave Health. These clients utilize Hello Patient's AI-powered platform for patient communication, enhancing access and streamlining workflows in healthcare settings. However, specific details about the nature of the relationships or projects undertaken with these clients are not provided in the available sources.

Hello Patient employs a diverse technology stack that includes both engineering and sales technologies.

Programming Languages:

• Python: Used for backend development, particularly in AI and data processing.
• Typescript: Utilized for frontend development, indicating a focus on modern web applications.

Frameworks and Libraries:

• FastAPI: A modern web framework for building APIs with Python, suggesting a focus on performance and ease of use.
• NextJS: A React framework for server-side rendering, indicating a preference for modern web development practices.

Infrastructure and DevOps Tools:

• AWS: Amazon Web Services is mentioned, indicating their reliance on cloud infrastructure for hosting and services.
• Livekit: A platform for real-time communication, which may be used for features related to patient interaction.

Data Technologies:

• Postgres: A relational database management system, indicating their choice for structured data storage and management.

Sales and Go-to-Market Technologies:

• Specific sales tools were not mentioned in the job postings reviewed, but the presence of roles in sales and marketing suggests the use of CRM systems and marketing automation tools, although these were not explicitly listed.

Overall, Hello Patient's technology stack reflects a modern approach to software development, emphasizing performance, scalability, and real-time communication capabilities, which are essential for their AI-driven healthcare solutions.