Insights from Dentulu Co-Founder & CTO Shiva Kumar | The CTO Story: Episode 10<\/b><\/p>\nIntroduction<\/b><\/h1>\n
Healthcare technology is changing quickly. But building a healthtech platform isn’t simply about adding new features or adopting the latest AI tools. It requires a careful balance between innovation, infrastructure, security, scalability, cost, and the needs of <\/span>healthcare professionals<\/span><\/a> and patients.<\/span><\/p>\n In Episode 10 of The CTO Story, <\/span>Dentulu Co-Founder & CTO Shiva Kumar<\/span><\/a> shared lessons from building and scaling healthcare technology at Dentulu.<\/span><\/p>\n When a technology platform grows, one natural assumption is that infrastructure costs will grow with it. But scaling efficiently requires a different mindset.<\/span><\/p>\n Engineering teams need to continuously evaluate how infrastructure is being used, where resources are being wasted, which services need to scale, where architecture can be optimized, and how performance can be maintained efficiently.<\/span><\/p>\n At <\/span>Dentulu,<\/span><\/a> this approach led to a significant reduction in AWS infrastructure costs from approximately $30,000 per month to $3,000 per month, as discussed in Episode 10 of The CTO Story.<\/span><\/p>\n The lesson isn’t simply about reducing a cloud bill. It’s about understanding that good engineering can directly influence the economics of a healthcare technology company.<\/span><\/p>\n Building a consumer technology product and building healthcare technology are different challenges. <\/span>Healthcare platforms<\/span><\/a> handle sensitive information and operate within a highly regulated environment.<\/span><\/p>\n Technology teams therefore need to think about security, privacy, reliability, and appropriate data handling from the beginning not after a product has already been built.<\/span><\/p>\n For healthtech companies, scalability means more than asking whether a system can handle more users. It also means asking whether it can do so while maintaining trust, security, reliability, and appropriate clinical workflows.<\/span><\/p>\n AI can analyze information quickly, identify patterns, automate repetitive processes, and help surface information that deserves attention. But healthcare requires context.<\/span><\/p>\n Healthcare professionals bring clinical knowledge, experience, judgment, and an understanding of the individual patient. That makes the strongest model for many healthcare workflows, AI plus human expertise.<\/span><\/p>\n Dentulu’s technology ecosystem incorporates <\/span>AI-assisted tools<\/span><\/a> designed to support dental workflows. The objective is not to remove the professional from the process, but to give the professional better information and better tools.<\/span><\/p>\n Technology leaders constantly face the decision of what to build internally and what to integrate from existing technology providers.<\/span><\/p>\n Building everything internally can provide control, but it can also require significant time and resources. Integrating proven technology can accelerate development, but requires careful evaluation of security, reliability, interoperability, cost, scalability, vendor dependency, and healthcare requirements.<\/span><\/p>\nScaling HealthTech Isn’t Just About Adding More Infrastructure<\/b><\/h1>\n
Healthcare Technology has a Higher bar for Trust<\/b><\/h1>\n
AI Should Support Healthcare Professionals- Not Replace Them<\/b><\/h1>\n
Build, Buy or Integrate?<\/b><\/h1>\n