Today
Career centers are understaffed relative to enrollment, advice is generic and role-agnostic, and students don't find out they're missing a required skill or certification until it's too late to fix before graduation.
Ready to pilot
GradusIQ reads a student's real transcript and career goals, then tells them — with evidence, not platitudes — which roles fit, what's missing, and where the market is moving before they graduate into it.
First Place, Dallas AI Summer Program
The problem
Today
Career centers are understaffed relative to enrollment, advice is generic and role-agnostic, and students don't find out they're missing a required skill or certification until it's too late to fix before graduation.
With GradusIQ
A student's unified academic and career profile feeds four purpose-built AI features that turn transcripts and goals into a specific, evidence-grounded plan — regenerated every time new grades or job-market data lands.
The engine
FIT
Matches major, interests, and stated goals against federal occupational data and live DFW job postings to surface 3–5 roles with a specific "why this fits you" rationale — not a generic list of job titles.
GAP
Scores a student's current skills, coursework, and certifications against what their target role actually requires, then separates must-have gaps from nice-to-have ones with a path to close each.
SHIFT
Tracks how a student's target role family is evolving under AI adoption, surfaces adjacent paths worth considering, and coaches how to talk about AI fluency in interviews.
PCA
Finds the patterns hiding across a semester of scattered instructor feedback, so students see the theme instead of re-reading twelve separate comments.
Under the hood
A full security audit is already closed out — cross-student data exposure, public JSON leaks, and unkeyed rate limits are fixed.
A single schema handles multiple institutions' academic terms, courses, and career profiles, with row-level access control proven live in production — one student's data is never reachable from another's session.
Never stored, always calculated from raw grade records — so it's never stale and never duplicated.
Every feature — role matching, readiness scoring, market guidance, and chat — resolves from an authenticated session, not a static file or a guessable URL.
An autonomous research agent pulls current job-market signal in real time, so guidance reflects this month's market — not a dataset frozen at launch.
Who's building it
Founder · AI Engine & Product
Primary architect and builder of the AI engine, data layer, and frontend.
Founder · Business Development
Drives partnerships and institutional adoption for GradusIQ.
Founder · Operations & Strategy
Leads operations and strategic planning for GradusIQ.
What's next
Direct import and scraper work underway to ground course recommendations in real, current offerings.
Replacing mocked academic data with a real LMS connection, unlocking the Professor Comment Analyzer for real students.
One trigger that runs every feature together and keeps context across a student's sessions.
Extending the same readiness and guidance model earlier in a student's academic path.
Jordan Reyes, TAMU, 3.00 GPA — walk through FIT, GAP, SHIFT, and the Professor Comment Analyzer live.