01
Information asymmetry
Forums, consultants, rankings, and social feeds all tell partial stories. Families collect fragments when they really need a way to evaluate tradeoffs.
Lumni Command Center · Powered by GPT-5
Illuminate youradmissions route
From school lists and essays to timelines and submission, Lumni turns a complex application season into a clear plan calibrated by real admissions data.
Command Center
Schools · Essays · Timeline · Submit
Analysis ready
Fall 2026 · CS
Admissions Route Hub
MIT EECSDrafting 14%
Finish GT Why-Essay v2
Generate the first admissions route in 2 minutes
Move schools, essays, and timelines together
Keep human advisors for the decisions that matter
Trusted by 12,400+ families · 2,100+ Top-30 offers
Top-30 admits · 2026 calibrated
Partner schools · Historical admits
12,400+
Active families
2,100+
Top-30 admits
87%
Model calibration
3,000+
School dataset
MITStanfordHarvardPrincetonYaleColumbiaCaltechUChicagoUPennCornellBrownDukeJHUNorthwesternUCLAMITStanfordHarvardPrincetonYaleColumbiaCaltechUChicagoUPennCornellBrownDukeJHUNorthwesternUCLA
Why most families still take expensive wrong turns
Admissions should not remain an information war
The issue is not a lack of information. The issue is lacking a system that can compare signals, set priorities, and turn uncertainty into action.
Fragmented signal flow
Xiaohongshu
College Confidential
Reddit
1point3acres
US News
Official FAQ
Does MIT still care about AP Physics C?
Is summer school worth the spend?
How big is 1520 vs 1570 really?
Can I open with dialogue?
Are 3 recommendation letters enough?
More inputs, but no consistent frame for judgment
Decision · 03.27
Harvard College · Regular Decision
“After careful review, we are unable to offer you a place...”
01Why did 1570 still miss?
02Was the essay not sharp enough?
03Was the activity list too light?
04Or was it mostly variance?
02
School lists by intuition
Rankings dominate the conversation while fit, program dynamics, and probability drift get ignored. The list looks impressive but lacks strategy.
03
Essays lose the person
Template language and over-edited drafts flatten the applicant’s voice. Strong essay work should sharpen originality, not erase it.
04
Execution collapses late
Deadlines, recommendations, activity upgrades, and essay revisions stack up at once. Without a unified operating surface, anxiety peaks exactly when it hurts most.
An AI-native admissions workbench
Six capabilities, designed to behave like one system
Not a pile of tools. One coordinated workflow for school strategy, essays, planning, prediction, collaboration, and expert judgment.
Four steps, end to end
From “I want to apply” to “I got in”
Build judgment first, then execute. Each step clarifies what matters next instead of leaving the hardest choices for the final month.
Lumni dashboard
One surface for list strategy, essays, and pacing
School matrix · essay sprint · AI review
School list
Essay sprint
Team signals
SchoolTierProgress
MIT EECS
Reach
34%CMU CS
Reach
46%Georgia Tech
Target
71%UIUC CS+X
Target
82%Purdue ECE
Safety
93%AI Copilot
AI is checking overlap between MIT and CMU essays
Today’s push
✓Refine the profile
○Finish GT Why Essay
○Confirm Purdue submission
01
Build the profile
Capture grades, activities, goals, and context so the system can see where the applicant really stands.
02
Generate the matrix
Compare schools, probabilities, essay load, and timing on one decision surface rather than across scattered tabs.
03
Advance essays and collaboration
Use AI for structure, peers for pressure, and mentors for judgment until the drafts are strong for the right reasons.
04
Track submission and outcomes
Keep progress, reminders, and material status synchronized all the way through the actual offer cycle.
Real students · Real outcomes
Not louder marketing. Better delivery.
12,400+
Active students
2,100+
Top-30 admits
87%
Model calibration
3,000+
Schools tracked
“I thought the consultancy would be the sharpest part of the process. A month in, the AI list was simply better reasoned. MIT EA came through.”
L
Lin
MIT CS · Class of 2028
“The team layer changed everything. Four Econ applicants reviewed each other’s essays for weeks, and every one of us ended up beating our expected outcomes.”
W
Wang
UPenn Wharton · Class of 2028
“AI didn’t write for me. It pushed me until the story was finally mine. By draft seventeen, the Common App essay actually sounded like me.”
Z
Zhou
Stanford · Class of 2028
“From the parent side, this was the first time I could see the pace clearly. Not more anxiety. Just more clarity about what mattered each week.”
Z
Ms. Zhang
Parent perspective