Private AI guidance tool
Brand Guidance Chatbot
I built a brand-guidance prototype with a source-update path, sensitive-information guardrails, user testing, and escalation for out-of-scope questions.
Problem
What needed to change
Campus marketers needed faster access to brand guidance so they could answer policy and copy questions without manually searching the MarCom site or asking the same support questions repeatedly.
Users
Who the system serves
University marketers, campus communicators, and internal teams responsible for brand-aligned messaging.
Team context
Where I fit
Technical lead (AI workflow prototyping) · University of Arizona
Owned the prototype and led internal testing with team members and intended campus users.
Important technical decision
The implementation choice
Build a source update path and refuse or escalate sensitive and out-of-scope questions.
Tradeoff or limitation
Where the boundary sits
The prototype is useful for finding guidance but remains in user testing; it is not presented as a campus-wide production system.
Implementation
What I personally owned
- Owned the project from inception to prototype.
- Led internal testing with team members and intended campus users.
- Designed the source update, refusal, and escalation paths.
Result
Result and limitations
- Working prototype for brand and policy guidance.
- Prototype source update and rebuild process.
- Guardrails for sensitive information and out-of-scope answers.
- Internal testing workflow with team members and campus users.
- Team members use the prototype as an alternative to browsing the MarCom site for information.
- It remains a prototype in user testing; broader campus adoption is not established.
Technical scope