VeriComms: Designing a White-Label AI Platform for Public Health Communicators
Client
Science 2 People
ROLE
Product Designer, Research & Discovery
Project Overview
As a UX Designer on the VeriComms project, I contributed across research, product strategy, and design in an agile, cross-functional setup. Our team partnered with Science 2 People to build the first white-label version of their AI platform for the Public Health Communications Collaborative (PHCC).
VeriComms was envisioned as an AI thought partner that helps public health professionals deliver clear, accurate, and trusted science-based messages quickly. My work turned early ambiguity into a research-backed vision, mapped strategy into actionable features, and shaped the first prototype ready for build.
The Challenge
Public health communicators operate in a high-stakes environment where clarity and trust save lives. They face:
A flood of misinformation competing for public attention.
Pressure to create content quickly without sacrificing accuracy.
Dense scientific research that must be simplified and translated.
Institutional skepticism toward AI adoption.
These barriers cause delays, erode public trust, and can compromise crisis response.
My Role & Contribution
As UX Designer, I wore multiple hats throughout the discovery phase:
Research: conducted intake workshops, interviewed communicators, and audited the AKARI prototype.
Strategy: mapped AKARI features to VeriComms’ needs, shaped MVP scope, and contributed to value proposition framing.
Design: created low- and mid-fidelity prototypes, tested concepts with users, and delivered annotated designs for engineering.
Collaboration: adapted to evolving priorities in an agile setup, working closely with product, technical, and CX partners.
Research & Discovery
We based our design choices directly on the realities and challenges communicators face.
Client workshops clarified PHCC’s goals and constraints.
User interviews surfaced critical pain points—navigation confusion, need for transparency, and skepticism toward generic AI.
AKARI Design Audit: I audited AKARI, the prior prototype, to identify friction in navigation, feature discoverability, and workflow alignment. While I cannot share visuals due to confidentiality, these findings directly shaped VeriComms’ design direction.
Personas and journey maps synthesized insights into communicator archetypes and mapped their end-to-end workflows.
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Reflections & Takeaways
This project reinforced that designing for trust, clarity, and adoption is as critical as solving usability challenges. Working with PHCC communicators confirmed that AI adoption in high-stakes public health environments depends on credibility, transparency, and human oversight.
Key lessons from this phase:
User-centered discovery drives design focus: Early research and audits (including the AKARI review) clarified which features were essential, shaping a high-value MVP.
Iterative prototyping uncovers real-world gaps: Usability testing highlighted feature discoverability issues and guided solutions like coach marks, contextual AI prompts, and translation assistance.
Collaboration is essential: Designing AI for public health requires balancing automation with human expertise, particularly for culturally and linguistically nuanced tasks.
Clear communication strengthens impact: The Loom walkthrough translated research insights into a tangible experience for stakeholders, demonstrating the rationale behind design decisions.
While this prototype is not the final product, this phase validated the core features users need and set the foundation for a trustworthy, efficient, and human-centered AI platform for public health communicators.
Impact statement:
This work established evidence-based design priorities that directly inform a scalable, user-trusted AI platform for critical public health communications.
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