From campus to career.
Run your Atlas Placements on Auto-Pilot.
From campus to career. AI grades every student–drive fit with real reasons, and a policy engine enforces CGPA, backlog, and Dream-offer rules itself. Students import a résumé by OCR, officers shortlist and email a cohort in two clicks, offer letters generate as PDFs, and NIRF / AICTE / NBA reports export with a stated denominator, one click.
AI that turns students
into top candidates.
A graded match score, résumé OCR import, and an honest readiness score, every student sees exactly where they stand.
AI Match Score
Every student × drive is graded Best / Strong / Weak with the actual reasons, computed against the résumé and the JD and cached until either changes. Ineligible students get an honest 'not applicable', never a fake match.
CSE · CGPA 8.4 · 0 backlogs
38 open · JDs · CTC history
Skills overlap · 12 / 14 JD terms
React · Node · SQL
CGPA 8.4 ≥ cutoff 7.0
0 backlogs
History · 21 CSE hires in 3 yrs
TechNova
Interest · product SDE roles
profile survey
Compatibility · Ananya Sharma
38 drives scored · every drive, every student
TechNova Systems
Dream · ₹14.5 LPA
Infozen
Tier 1 · ₹8.0 LPA
Zenlabs
Super Dream · ₹28 LPA
AI Résumé Import
Drag in a PDF or a photo, OCR reads it and builds the placement profile through a field-by-field merge. Nothing auto-overwrites; the student approves every change.
Tailor my resume for TechNova · SDEJD attachedProjects reordered · JD relevance
top 3 first
Keywords · 18 / 21 matched
REST · CI/CD added
ATS-safe layout · single column
no tables
Facts verified from records
CGPA · certs
parsed as a recruiter bot
94 / 100
keywords
18 / 21
Placement Readiness Score
An honest composite of profile, résumé, training, and match coverage, each with its evidence and a clear 'what to do next'. No inflated number.
Company
₹12–15L · 3 seasons
Profile
CGPA 8.4 · 91% match
Market
SDE median ₹13.2L
Predicted CTC · TechNova
82% confidence
₹13.8 – 15.2 LPA
Offer received · ₹14.5 LPA
inside band · Δ ₹0.0 vs midpoint ₹14.5
Q1 · arrays
L2 · correct
Q2 · SQL joins
L3 · correct
Q3 · indexing
L4 · partial
difficulty adapts with performance
Q4 · L4
How would you index a table that updates its rows every few seconds?
Partial index on the hot rows, keep writes cheap…
Session feedback · 22 min
attempt 3 · +1.4 overall vs attempt 2
Communication
8.2 / 10
Technical depth
7.4 / 10
Confidence
7.9 / 10
Eligibility, Explained
The engine tells each student exactly why a drive is open or closed, 'CGPA 6.2 < 6.5', 'frozen, you hold a Dream offer', the same rules the admin enforces.
Run placement drives
like a machine.
Drive command center, instant eligibility filtering, and auto-advancing interview rounds, zero spreadsheets.
Drive Command Center
One view for everything, company details, JD, eligible students, registration status, interview rounds, and offers. The single source of truth.
TechNova · SDE-1
412 of 1,860
3 rounds · live
TechNova Systems · SDE-1
Dream · ₹14.5 LPA · JD v2 · Bengaluru
eligible
412
registered
386
shortlist
124
offers
34
Round 1 · aptitude
386 → 124
DoneRound 2 · technical
124 → 58
DoneRound 3 · HR
58 → 34
Offers outInstant Eligibility
Define criteria (CGPA, backlogs, attendance, department). AI filters thousands of students in seconds. Update criteria, list refreshes.
CGPA ≥ 7.0
backlogs = 0
attendance ≥ 75%
dept · CSE / IT / ECE
edit criteria → list refreshes
Eligible · TechNova drive
1,860 scanned · 2.1 s
Ananya Sharma
CSE · CGPA 8.4 · att. 91%
excluded · Karan Mehta · 1 active backlog
Rohan Gupta
ECE · CGPA 7.8 · att. 84%
Company Tiers
Super Dream (>25 LPA), Dream (10-25), Tier 1 (6-10), Tier 2 (3-6), Tier 3 (<3). Dream policy enforcement built in.
season 2025-26 · 88 companies
Super Dream
> 25 LPA
3 cos
Dream
10–25 LPA
TechNova ₹14.5L11 cos
Tier 1
6–10 LPA
24 cos
Tier 2
3–6 LPA
38 cos
Tier 3
< 3 LPA
12 cos
Ananya Sharma
holds Dream offer · ₹14.5 LPA
Tier 1 / 2 / 3 registrations
locked · 74 drives hidden
super dream · still eligible
386 appeared · closed
Round 2 · technical
124 auto-scheduled · invites sent
Ananya Sharma
Lab 2 · 10:40
Rohan Gupta
Lab 1 · 10:00
Priya Nair
Lab 3 · 11:20
Auto-Advancing Rounds
Company shortlists after Round 1 → selected students auto-scheduled for Round 2. No manual intervention.
From shortlist to
signed offer..
Shortlist a cohort, communicate in one click, generate the letter, and manage every offer under the Dream policy.
Shortlist → Communicate
Select a cohort or a saved shortlist and send a templated lifecycle email, interview invite, selection, rejection, in two clicks. Every send is logged per student × drive with opens and clicks.
availability windows
parallel capacity
10:00 – 17:00
Interview grid · TechNova R2 · Day 1
62 of 124 slots · solved in 4 s
10:00
10:40
11:20
Lab 1
Lab 2
Lab 3
AS · Ananya Sharma · lab 2 · 10:40
Selection Rounds
Aptitude → technical → HR with structured results per round; qualified students auto-advance to the next round. No spreadsheets.
problem solving
4.6
communication
4.4
4.5 / 5
problem solving
4.2
communication
4.0
4.1 / 5
Ananya Sharma · R2 feedback
2 evaluators · structured form
Round score
4.3 / 5
problem solving
4.6 / 4.2 → 4.4
communication
4.4 / 4.0 → 4.2
evaluator spread
0.4 · within tolerance
Generated Offer Letters
Accept an offer and a real PDF letter renders on institution letterhead with the salary breakdown and joining terms, one click, uploaded and attached.
interview floor · live
in progress · since 10:42
wrapping up · ~4 min
no physical crowding
Waiting room · TechNova R2
24 in queue · paced automatically
#5
Rohan Gupta
in room · Lab 1
#6
Priya Nair
up next · Lab 2
#7
Ananya Sharma
you · est 25 min
Infozen
Tier 1 · SDE
₹8.0 LPA
SupersededTechNova Systems
Dream · SDE-1
₹14.5 LPA
AcceptedOffer · TechNova Systems · ₹14,50,000
SDE-1 · Bengaluru · joining Jul 6, 2026
Base
₹9,20,000
Variable
₹1,80,000
Benefits & joining
₹3,50,000
Offer Management
Track every offer's CTC breakdown, role, location, and joining date; handle multiple offers per student with Dream-policy freezes enforced automatically.
Numbers that tell
your placement story.
Live statistics, salary analytics, statutory exports with stated denominators, and a recruiter portal, all generated automatically.
Offer Board
Live dashboard showing placement progress, students placed, average CTC, highest package, company-wise breakdown. Celebrate wins publicly.
Offer board · batch 2026
Live1,304 placed
of 1,860 eligible · 70.1%
Infozen
86
DataCurve
52
TechNova
34
Zenlabs
6
Salary Analytics
Average, true median, and highest CTC by department, year, and company. Trend analysis over multiple placement seasons.
Avg CTC · by department
batch 2026 · 1,304 offers counted
CSE
₹9.2L
ECE
₹7.1L
ME
₹5.2L
Civil
₹4.6L
Season trend · avg CTC
median ₹5.4 LPA · 2026
5.8
'24
6.3
'25
6.8
'26
+7.9% YoY
· 3 seasons compared
NIRF / AICTE / NBA Reports
One-click statutory exports, each dated, in the required format, with the denominator stated in the file. 'Not tracked' where a source genuinely doesn't exist, never a fabricated figure.
Export NIRF placement annexurebatch 2026Placed count · 1,304 verified
offer letters
Median salary · ₹5.4 LPA
NIRF definition
3-year table · 2024–26
auto-compiled
NAAC criterion 5.2 mapping
fields aligned
which companies hired the most this season?Best packages · dept
CSE · ₹9.2L
Repeat recruiters · 64 of 88
suggested · invite 3 more dream companies
Recruiter Portal & Relations
A token-authed portal where a recruiter sees only their own drives, shortlists, and results, plus a prospect → engaged → MoU → recurring relationship pipeline with follow-up reminders.
AI built in.
Not bolted on.
Every page in Atlas Placements carries a context-aware AI agent, not a generic chatbot, but a specialized assistant with real tools.
JD ↔ Résumé Matching
One JSON-only call grades each student against the drive JD and the OCR'd résumé, returning a verdict, score and the reasons, degrade-safe, never a fabricated 'best match'
Résumé OCR Extraction
Two-stage vision OCR reads a PDF or photo résumé into the placement profile, skills, certifications, expected-CTC range, for a comparative merge
Grounded Drafts
Per-page Aero tools draft the JD, drive announcement, recruiter email and offer letter, grounded in real records, shown as an artifact, nothing sent automatically
Explain-the-Stat
Ask why the placement rate is what it is and the assistant answers with the actual numerator and denominator, never a hand-wave
FAQ
Frequently asked questions.
Everything universities ask us about Atlas Placements — and how it fits into the rest of the WhiteBird suite.
What is Atlas Placements?
Atlas Placements takes students from campus to career, and is part of WhiteBird's Atlas division for campus operations. AI matches students to companies on skills, CGPA, and interest, eligibility filters run across thousands of records in seconds, interview rounds auto-advance from company shortlists, and NIRF and NAAC reports export with one click.
How does Atlas Placements use AI?
AI matches students to companies with compatibility scores based on skills, CGPA, interests, and historical placement data, builds ATS-compatible resumes tailored to specific job descriptions, and predicts likely CTC from company history and market benchmarks. Students can also practice with a mock interview AI that adapts difficulty and gives feedback on communication, technical depth, and confidence.
Does Atlas Placements integrate with our existing systems?
Atlas Placements shares one database with Atlas ERP, so eligibility criteria like CGPA, backlogs, and attendance filter against live student records with nothing to sync. It also connects natively to Atlas Alumni and Iris CRM on the same platform, and AI enrichment auto-fills company details like employee count, industry, and ratings from public sources.
How long does Atlas Placements take to deploy?
Deployment takes days to weeks — about 15 days — with pre-built modules and guided onboarding. Company tiers, eligibility criteria, and drive workflows are configurable from the admin side, so the placement cell runs its next season on the platform rather than on spreadsheets.
How does Atlas Placements manage placement drives?
A drive command center holds everything in one view — company details, JD, eligible students, registration status, interview rounds, and offers. Eligibility filters process thousands of student records in seconds, company tiers from Super Dream to Tier 3 enforce the Dream policy automatically, rounds auto-advance when companies shortlist, and AI schedules interview slots around student availability, room capacity, and panel constraints.
Can Atlas Placements generate NIRF and NAAC reports?
Yes, with one click — placement data exports in the exact formats required by NIRF rankings and NAAC accreditation, with no manual compilation. A live offer board tracks students placed, average CTC, highest package, and company-wise breakdowns, and salary analytics cover average, median, and highest CTC by department, year, and company across seasons.
Works seamlessly
with the rest of Whitebird.
Atlas Placements is part of the Whitebird platform. Data flows automatically between these connected apps. No integration work required.
See Atlas Placements in action.
A 30-minute walkthrough, tailored to your institution. We'll show you the exact workflows and answer any question.