Go to ScienceSoft Global
AI Telehealth Chatbot PoC and Investor Pitch Deck for Prognostic Optimization Group
Summary
In two weeks, ScienceSoft delivered a PoC for a US startup’s AI telemedicine chatbot meant to streamline patient diagnostics and provide clinical decision support to physicians. The startup also received clickable UI prototypes and an engaging pitch deck for investors.
About Prognostic Optimization Group
Prognostic Optimization Group is an innovative US startup aiming to transform telemedicine with AI-driven solutions that improve diagnostics, automate patient triage, and empower healthcare providers with robust clinical decision support.
Trusting ScienceSoft’s experience in developing AI and medical software, including intelligent chatbots for healthcare, Prognostic Optimization Group turned to us to create a proof of concept (PoC) for its AI-powered telehealth chatbot. The chatbot was meant to collect and analyze patient symptoms, perform triage, offer preliminary diagnostics, and recommend next steps, such as scheduling appointments, seeking emergency care, or managing conditions at home. Additionally, the chatbot was intended to suggest over-the-counter medications and lifestyle adjustments to patients, generate tailored reports for patients and physicians, and provide doctors with clinical decision support. The solution was to be integrated with telehealth platforms, popular EHRs, drug databases, and insurance services. Prognostic Optimization Group needed the bot to be fully compliant with HIPAA, GDPR, and WCAG standards for virtual care delivery.
To attract funding and lay the groundwork for future development, the startup also needed a compelling demo, including clickable UI prototypes and an engaging investor pitch deck.
2 Weeks and 4 Talents to Deliver AI Chatbot PoC, Clickable Prototypes, and Investor Pitch Deck
To complete the project within a short timeframe, ScienceSoft assembled a team of a business analyst, a UI designer, a data scientist, and a front-end developer. The team analyzed the startup’s requirements for the future solution and chose to create the AI chatbot PoC using the Azure Health Bot, as it already had a strong foundation for regulatory compliance and a number of essential functional modules, such as symptom checking, a clinical knowledge base, appointment scheduling, analytics, and reporting.
The delivered PoC has the following patient-facing functionalities:
- Symptom input. Patients describe their symptoms via a web-based interface, answering questions posed by the chatbot. If needed, they can select an option from an AI-predicted list of responses.
- Preliminary diagnosis and patient triage. Based on the reported symptoms, patients receive preliminary diagnoses in layman’s terms. Depending on the severity of their condition as determined by the bot, patients receive recommendations for the next steps, such as self-monitoring, seeking emergency care, or scheduling a doctor’s appointment. The bot suggests a list of available providers from integrated telehealth platforms (e.g., Teladoc Health, Amwell, Doctor on Demand, MDLive, Doxy.me) for virtual care delivery.
- Treatment recommendations. For non-urgent conditions, patients get over-the-counter drug recommendations (e.g., acetaminophen), including usage instructions and potential side effects. They are also provided with educational content, such as symptom explanations, general tips on lifestyle adjustments and preventative measures, as well as FAQs.
- Reports. Patients receive chatbot-generated reports detailing potential conditions and recommendations on their management. These reports can be rendered as PDFs in real time for sharing, downloading, or printing.
The physician-facing features include:
- Clinical decision support. Via an integrated dashboard, doctors receive reports generated for each patient. These include patient medical history (including lab test results), information on the defined triage level, symptom records, diagnostic results (including differential diagnoses), suggested treatment options (including first-line treatments, alternative therapies, and potential drug interactions), and interdisciplinary care notes. Physicians can ask patients follow-up questions for better context and decision-making. The bot uses medical terminology and evidence-based references to clinical guidelines, research studies, and other sources to support the provided information.
- Report modification. Physicians can customize treatment plans by adjusting parameters like dosage and treatment duration in the chatbot-generated reports.
Currently, the chatbot operates in an anonymous mode and does not collect its users’ PHI. Prognostic Optimization Group’s future plans include allowing users to create secure patient profiles to store their clinical and non-clinical information.
In addition, the startup aims to enable the solution’s integration with popular EHRs (Epic, Cerner, Athenahealth, Allscripts, and eClinicalWorks), drug databases (Micromedex, DrugBank), and insurance services.
For the demo, ScienceSoft’s UI designer customized the chatbot’s standard interfaces to align with the branding of Prognostic Optimization Group and created clickable prototypes showcasing the bot’s functionality.
To support the startup’s investment efforts, our business analyst prepared a pitch deck highlighting the potential of the AI chatbot and its market viability. This presentation was crafted to effectively communicate the financial and operational benefits to prospective investors.
With the PoC and demo phase complete, Prognostic Optimization Group is now ready to pursue fundraising to advance the chatbot’s MVP development.
Jayson Bakonyi, PharmD and MBA Candidate, Founder at Prognostic Optimization Group, says:
I honestly can’t say enough about how impressed I am with ScienceSoft. They delivered a fully customized AI medical chatbot PoC in just two weeks, which was unbelievable. The attention to detail in the chatbot design, and especially the pitch deck, was amazing — with this kit on hand, we are ready to go into investor discussions confidently. It’s not often that you find a team that moves this fast without sacrificing quality. I’m genuinely grateful to ScienceSoft for their hard work and would absolutely recommend them to anyone looking for top-notch results in health tech.
Key Outcomes for Prognostic Optimization Group
- The delivery of a proof of concept for an AI telehealth chatbot that automates symptom collection, patient triage, preliminary diagnostics, and report generation. The solution is based on Azure Health Bot, which reduces development costs and streamlines the preparation for HIPAA, GDPR, and WCAG compliance.
- Access to clickable UI prototypes illustrating the chatbot’s design, user experience, and reporting features.
- An investor-ready pitch deck that compellingly presents Prognostic Optimization Group’s business case and the app’s potential, increasing the likelihood of securing funding.
- Smooth project completion in just two weeks, exceeding Prognostic Optimization Group’s expectations for speed and quality.
Technologies and Tools
Azure Health Bot, Figma, PowerPoint, HTML, CSS, JavaScript, Python Flask.
