01Visibility
Updates, not a black hole
Candidates hear from you at every step: application received, moved to the next stage, invited to a project or interview, and the final outcome. No more wondering if anyone opened their resume.
Everything hiring needs. In one place
One platform for campus and direct hiring, from first application to final offer.
What AI.Prof solves
A cleaner way to hire from universities.
Hiring from several universities usually means several contacts, spreadsheets and timelines. AI.Prof gives every university its own workspace and keeps your university drives and careers-page hiring in one place.
Beyond the resume. Into real skills.
AI.Prof matches candidates to your role and analyses their projects and code, giving you a clearer picture of what they can actually do.
University and direct hiring
Every university, plus your own careers page
Partner with as many universities as you like. Each university gets its own workspace where you run proper hiring drives alongside its placement office, while your own careers page keeps direct hiring going in the same account.
- Run hiring drives with each partner university
- Hire directly from your own careers page
- See everything together, or one university at a time
Hiring stages
Every stage of the hire, built in
From the first application to the final decision, the whole hire runs inside AI.Prof. Resumes are checked against your job description, GitHub work gets a real code review, shortlisted candidates build a project from your own brief, and your panel interviews only the people who have already proven they can do the job. No spreadsheets, no extra tools, no guesswork between stages.
- Resume and GitHub analysis, done for you
- Live projects built on your own brief
- Interviews and decisions with your own panel
- Use every stage, or only the ones a role needs
Your pipeline, your rules
Evaluate every candidate the same way
Choose the stages for each role, put them in your order and decide how much each one counts. Let candidates advance automatically when they clear your marks, or review every move yourself.
- Weights and pass and fail marks for each stage
- Automatic advancement, or manual review
- Stages lock once the first candidate applies, keeping it fair
Fraud Prevention
Catch Fraud Before It Costs You
One bad hire can cost months of salary, a missed deadline and your team's trust. AI.Prof checks what every candidate claims against what they can actually show, so inflated resumes, empty profiles and work a candidate can't explain surface long before anyone reaches an offer.
- Skills listed but never shown in real work are flagged
- Code is reviewed for real quality, not star counts
- Ask for a demo walkthrough of every live project
- Limit roles to a university's student email addresses
Notes at every stage
Every decision, with its reasons
Your team adds notes to each candidate at every stage, from resume review to the final decision. Everyone sees who wrote what and when, so handovers are easy and every hire or rejection has a clear record behind it.
- Notes on every stage, for every candidate
- Each note shows who wrote it and when
- Rejection and decision reasons stay with the candidate
- Pick up exactly where a teammate left off
Bulk actions
Move hundreds of candidates in a few clicks
Invite everyone who cleared a stage, or close out the rest, in one go. Preview exactly who will be included before anything is sent.
- See who qualifies, who is already in the stage and who fell short
- Edit the email subject and message before sending
- Invites and rejections send in the background while you keep working
Why AI.Prof
Built for teams who look past the resume.
AI.Prof replaces gut-feel screening with clear, consistent evaluation, and the final call always stays with your team.
AI scoring engine
Every candidate gets a clear, explainable score.
You decide what matters for each role. AI.Prof brings resume, GitHub, live project and interview scores together and ranks candidates on one comparable scale.
Resume
92
GitHub
78
Live Project
85
Interview
88
Per role config
You set the rules.
Weights, pass marks and stage order are all set by your hiring team. No two roles have to look alike.
Real code, not stars
We read the actual code.
Code quality, structure and fit to the role. AI.Prof reviews what candidates have actually built, not their star counts.
Latest commit · 2h ago+128 −34
TypeScript · 64%Python · 36%
University safe
Your scores stay yours.
Placement offices follow each student's stage and outcome, never your scores, analysis or notes.
What the university sees
PROTECTEDAnanya Rao / Live ProjectIn Review
Scores and notes never shared
University and direct
Hire from any university, or your own careers page.
Run drives with individual partner universities and keep direct hiring going on your own careers page, all in one account.
Riverside InstituteUniversity drive
Eastbrook UniversityUniversity drive
Your careers pageDirect hiring
Built for the whole team
Your team, your roles, your rules.
Create roles with any name and give each one exactly the permissions it needs.
Same access
for everyone
Hiring ManagerUniversity CoordinatorTech PanelObserverFull access
Roles that fit
your team
- Hiring ManagerEverything in hiringReady-made
- University CoordinatorBatches and rolesCustom
- Tech PanelInterviews and feedbackCustom
- ObserverView only
For candidates
A hiring experience candidates actually respect.
AI.Prof is built for employers, but it respects the people on the other side. Candidates get clear updates, a fair process and a real chance to show their work, not a keyword-filtering black box.
Candidate updates
EVERY STAGEApplication submitted
PASSEDAI analysis complete
PASSEDInterview scheduled
PASSEDFinal decision pending
02Fairness
One submission, evaluated fairly
A single unified application resume, GitHub, portfolio links submitted once. Every candidate is analyzed on the same evidence, the same way.
03Real work
A chance to show what they can build
Shortlisted candidates build a real project from your brief, with a clear deadline and a simple way to submit. Skills count, not just how a resume reads.
04Interviews
Interviews, clearly scheduled
Interview invites arrive with the time, the interviewer and a meeting link, and any change is sent to the candidate straight away.
Comparison
Traditional way vs AI powered automation
Traditional way
AI.Prof automation
VS
- Resume keyword screening
- Subjective, inconsistent scoring
- One size fits all evaluation
- Black box AI screening tools
- Claims taken at face value
- Shallow one off interviews
- No visibility into real code
- Same process for every role
- Reviewer hours per candidate
- Gut feel final decisions
- Evidence from resume, GitHub, projects
- Consistent, evidence backed scoring
- Company configured per role weighting
- Transparent, traceable scoring
- Verified against real shipped work
- Structured interviews with recorded feedback
- Deep code & architecture analysis
- Modular features per role's needs
- Minutes to triage a ranked shortlist
- Human decision, AI backed evidence
FAQs
Common Questions
What hiring teams ask before getting started.
Ready to hire the elite 1%?
Connect with universities and start assessing top talent today.
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