Establishing confidence, efficiency, and reliability for public health communication
Public health communicators needed a tool they could trust with accuracy and speed, so I helped build an AI platform trained only on verified health data instead of the open internet.
Science To People came back to us with a new challenge: to scale their operations and build VeriComms, their first white label product for public health communicators.
Previously, we built an AI content creation platform called VeriSci.AI (now called AKARI; see case study here) for our client, Science To People. With secured funding from our previous work, Science To People sought us out to scale their operations and create their first white label product, VeriComms, for the Public Health Communications Collaborative (PHCC).
“Messages that are simple, clear, and accurate can save lives.”
Public Health Communications Collaborative, About Us
The scope was more complex this time around, with a larger stakeholder team, more product ambiguity, and confidentiality constraints. As part of the UX design team, I shaped the vision of this product and was responsible for all design deliverables for handoff to the outsourced dev team for implementation. From cross-functional collaboration with 5 other teams of 20+ members, the client, and indirect stakeholders, we achieved an excellent SUS usability score of 75.7, client satisfaction rating of 95%, and 4 product changes to strengthen client market positioning.
Public health communicators face challenges in information overload, accuracy, approval bottlenecks, and tool fragmentation, making it difficult to deliver timely, trustworthy public communications.
An AI thought partner and creative assistant designed to address the unique needs of public health communicators. Unlike general-purpose AI, VeriComms is built on a science-focused, closed-corpus LLM specifically trained on verified public health data.
Features validated sources from reliable research and government websites and an AI model trained on a vetted corpus of public health data, ensuring the accuracy and validity that general AI models cannot guarantee for public health communicators.
Features prompt box with a graphical interface that gives public health communicators the flexibility and ability to quickly perform routine actions, while maintaining the freedom to create customized content. This approach incorporates transparency, traceability, and human review in every step of their workflow.