Summer 2026Internship Showcase
Professional portrait of Yash Gudimalla
Business Analyst Intern · Summer 2026
About me

I’m Yash
Gudimalla.

During my internship with NA Application Sales Business Operations, I used AI and workflow design to improve data integrity, organizational planning, and customer relationship visibility.

Rutgers Business School

Rutgers–New BrunswickFinance + Computer Science · May 2027

Based inPrinceton, New Jersey
BasketballSoccerCarsPickleball
What I discovered

I expected assigned analysis. I found opportunities to redesign the work itself.

The organization was changing, managers had limited time, and several processes still required repetitive manual effort. That created room to take ownership and build practical AI workflows around real team needs.

What I expectedDashboards · KPIs · Excel analysis
My internship
Where I created valueAI workflows · Operational tools · Actionable insights
Reduce repetitive work so teams can spend more time on decisions that require human judgment.
Three projects · one theme

Choose where we start, or explore all three.

Each project begins with a real operational problem, shows what I built, and ends with the value or next opportunity.

01Sales · Leadership · Strategy
C-Suite Relationship Tracker

Turn relationship gaps into clear account actions.

I connected executive relationships, engagement history, account ownership, and follow-up in one usable tracker.

Problem

The data existed, but the next move was difficult to see.

Leaders needed a simple path from portfolio health to a specific customer, the right Territory Owner or FLM, and a concrete follow-up action.

RelationshipRed · 1 executive
EngagementNeeds attention
OwnershipTerritory Owner + FLM
ActionExecutive introduction
Refinement

I designed the tracker around decisions, not just reporting.

The experience moves from relationship health to account context, then ends with an owner, action, and status.

Executive SummaryManager ViewPriority AccountsAction Tracker
Priority accountAtlas Co.
Relationship · Red
OwnerNext actionStatus
A. PatelCFO introductionIn progress
J. KimExecutive briefingPlanned
M. DiazConfirm sponsorReview
Assign
Outcome

Relationship coverage became easier to understand and act on.

The pattern below is descriptive, not causal. It gives leadership a useful reason to prioritize relationship-building.

419Red120Yellow42Green

581 reporting customers

Average current SaaS spend per customer
$3.32MGreen8.1×$0.41MRed

This is a descriptive portfolio association. It does not establish causation.

Possible next feature

Find timely executive-engagement opportunities.

AI could search approved public events, identify relevant executives, match an attending sales representative, and recommend an action for human review.

Public eventIndustry SummitChicago · September
EXExecutive match
SRSales rep match
Human-reviewed introduction
02Data · Operations · Finance
Hospitality Data Integrity

Make 61,198 hotel records useful for account planning.

I built an AI-assisted validation workflow to identify hotel owners and operators at a scale that manual research could not support.

Problem

Critical owner and operator information was mostly missing.

Brands, management companies, and owners are often different organizations. Searching tens of thousands of records manually would have taken an unreasonable amount of time.

61,198hotel records
CoStar ID16,023
Management Company625
Owner / REIT1,815
Refinement

I combined AI research with controlled validation rules.

Confidence rules, source checks, review checkpoints, and workbook protections kept the process inside an approved framework. Weak evidence stayed unresolved instead of being guessed.

XHotel data · simplified demonstrationAI-assisted workflow
HotelCoStar IDManagement CompanyOwner / REIT
Harbor HotelEmpty10084EmptyNorthstar MgmtEmptyHarbor REIT
Riverfront InnEmpty10184EmptyRiver GroupEmptyBluewater LLC
Metro SuitesEmpty10284EmptyMetro LodgingEmptyMetro Capital
Cedar LodgeEmpty10384EmptyCedar OpsEmptyCedar Holdings
AI
1 Match reliable records→2 Research focused gaps→3 Validate evidence→4 Write approved values
Outcome

The same records became far more usable.

The final release made owner and operator information available for account planning without requiring someone to research roughly 45,000 incomplete rows by hand.

CoStar IDBefore 16,023→After 51,147
Management CompanyBefore 625→After 44,003
Owner / REITBefore 1,815→After 50,765
89.6%

had at least an owner or operator identified

54,827 of 61,198 scoped hotels
Validated release127,452

approved cell updates

My takeaway

AI was most useful when it accelerated repetitive work while preserving uncertainty whenever the evidence was weak.

How this could continue

Run the same validation before new hotel records enter the TDR, so owner and operator fields are handled during normal intake.

03Product · Engineering · Management
Org Chart Automation

Turn an approved hierarchy into an editable PowerPoint.

I transformed a repetitive quarterly process into an on-demand workflow built around real hierarchy, layout, and validation requirements.

Problem

Every quarterly refresh repeated the same manual effort.

Stakeholders had to interpret hierarchy data, rebuild PowerPoint layouts, reconcile counts, and correct formatting details. Small inconsistencies could send the work back for additional review.

Quarterly
refresh
Read hierarchy
Build slides
Check counts
Fix details
Refinement

The workflow applies reusable hierarchy and presentation rules.

It handles manager order, continuation pages, photos, counts, slide fit, and final validation, while keeping the PowerPoint fully editable.

Hierarchy.xlsxApproved source
1Maya ChenVP
2Jordan LeeDirector
3Sam RiveraDirector
4Alex MorganManager
Build
+ validateHierarchy rulesLayout rulesCount checks
PEditable org chart
MCMaya ChenVP
JLJordan Lee
SRSam Rivera

Fictional names shown. The real output remains editable for stakeholder review.

Potential capacity returned112–150

hours per quarterly cycle

Time that can be redirected toward planning, decision-making, and higher-value work.
Further development

Sonia connected the workflow to recurring Connections product demand.

Sonia, a Senior Director of Product Management for Connections, highlighted that users repeatedly ask to export org charts directly from the platform for presentations and offline work.

Current struggleUsers rely on screenshots or manually recreate hierarchy views.
→
Feature directionExport a selected hierarchy as PPTX, PDF, or XLSX.
→
What my work contributesTested logic for hierarchy depth, editable layout, page fit, and validation.

A practical next step would be evaluating the workflow with Sonia and other Connections product and development stakeholders. This is a proposed product opportunity, not a committed roadmap item.

What I learned

The tools improved as I learned to work between technical systems and business teams.

01?

Clarify earlier

Ask more stakeholder questions before building deeply, especially around definitions and exceptions.

02⌘

Build with guardrails

Use AI for speed while keeping source rules, validation, review, and human approval visible.

03↔

Translate the value

Explain technical workflows through the time, clarity, or decision they improve for a nontechnical user.

Where this points me nextSolutions EngineeringTechnology ConsultingProduct ManagementTechnical Business Analysis
Thank you

I want to keep building useful tools at the intersection of AI, business, and operations.

What would you like to explore next?

linkedin.com/in/yg13 ↗