About Backyard-AI
Practical AI, grounded in real public-health work
Backyard-AI was created to help organizations move beyond vague excitement about AI and toward thoughtful, useful implementation. The focus is on practical systems that improve communication, synthesis, learning, and workflow efficiency while keeping people, judgment, and trust at the center.
About Nick Swope
Nick Swope is a public health professional and AI educator focused on practical, responsible uses of Artificial Intelligence in public health practice. With more than a decade of experience in the field, he helps organizations move beyond curiosity about AI and toward clear, usable workflows that support real public health work.
His experience includes serving as Health Promotion Program Manager for the Health Promotions, Epidemiology, and Immunizations teams at the Panhandle Health District in Idaho, teaching as an MPH lecturer at Eastern Washington University for five years, and pursuing his DrPH at East Tennessee State University, where he founded an AI Interest Group and developed tools to support faculty, researchers, and community organizations.
Nick’s work includes building Jessie AI, a substance-use recovery chatbot for Recovery Resources TN; creating multi-platform AI research workflows; and developing custom tools for social media data extraction, qualitative analysis, and large-scale analytic review. His projects have helped organizations streamline complex workflows, reducing weeks of manual review to hours.
As the founder of Backyard-AI, Nick helps public health teams translate AI from a broad, abstract idea into practical workflows for communication, reporting, training, evidence synthesis, and program improvement. His approach emphasizes clarity, implementation, human review, and real-world usefulness.
Practical projects, not abstract AI talk
Nick’s work includes building AI-supported workflows for research, social media data extraction, qualitative analysis, large-scale analytic review, and resource navigation. He has also worked on Jessie AI, a substance-use recovery chatbot for Recovery Resources TN, and developed tools to support faculty, researchers, and community organizations.
The common thread across these projects is practicality: use AI to reduce manual burden, improve clarity, organize information, and support better workflows without removing human judgment from important decisions.
What matters here
Practicality
The work should be usable in the real world, not just interesting in theory.
Clarity
AI should make communication, reporting, and systems easier to understand, not more confusing.
Oversight
Human review, professional judgment, and accountability remain essential. Human-in-the-loop needs to be intentionally built into the design.
Mission fit
The best AI use cases support public service work rather than distract from it.
Teachability
A good workflow should be understandable enough for staff to use and improve after the engagement ends.
How Backyard-AI works
Backyard-AI focuses on specific, high-value use cases rather than broad promises. Every engagement starts by identifying a real task, understanding who does it, what slows it down, where errors matter, and where AI can provide support without replacing expert judgment.
The result is a practical form of AI adoption. Instead of asking teams to redesign everything, Backyard-AI helps them improve a workflow, train staff, add guardrails, and learn what works in their actual environment.
Want to explore a practical AI use case for your team?
Start with the Workflow Scorecard or book a readiness call to talk through your team, workflow, and next step.