Featured Build

Supplier Intelligence Copilot

AI-assisted supplier decision support

Supply Chain AI Live
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Operations · Supply Chain · AI

Parul Walkey

Project and product-minded professional with a foundation in industrial operations and supply chain, now building at the intersection of AI, analytics, and cross-functional execution. I turn complex business problems into structured workflows, data-driven decisions, and practical solutions.

Project & Product Execution Supply Chain & Operations AI Product Thinking Data & Analytics

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Featured AI Product

Supplier Intelligence Copilot

From supply-chain visibility to AI-assisted decision support.

This project is proof that I can take domain knowledge from supply chain, apply AI product thinking, define system boundaries, and use AI-assisted development to turn the concept into a working prototype.

I originally built a Supply Chain Health Monitor using SQL and Tableau to surface supplier quality, inventory, and lead-time signals. The dashboard answered “What is happening?” but an analyst still had to manually answer “Which supplier needs my attention, why, and what should I investigate next?”

I redesigned that workflow into an AI-assisted Supplier Intelligence Copilot. Supplier risk is calculated deterministically. AI is used for interpretation, evidence-grounded explanation, healthy-signal identification, and recommended investigation.

Data provides facts. Deterministic logic establishes risk. AI explains and synthesizes. Humans decide.
SQL Tableau JavaScript OpenAI API Structured Outputs Context Engineering Netlify Functions
Live Demo GitHub Tableau Case Study

Work

Industrial Operations & Supply Chain

Operations Engineer

Operations · Supply Chain · Project Execution

LINDE LSAS | Oct 2022 - Jun 2024

The experience gave me a practical foundation in operations, supply chain, analytics, improvement, and cross-functional execution in real operational environments.

01

Operations & Planning

Used historical production and demand data to support planning and operational decision-making across large-scale manufacturing operations.

02

Process Improvement

Identified performance gaps and supported process optimization initiatives that reduced waste, improved efficiency, and contributed to significant recurring cost savings.

03

Procurement & SAP

Supported procurement workflows through SAP S/4HANA, including purchase-order processing, material coordination, vendor interactions, and GR/IR activities.

04

Analytics & Decision Support

Built Excel and Power BI reporting workflows to improve KPI visibility and reduce manual reporting effort by approximately 40 to 50%.

05

Cross-Functional Project Execution

Coordinated work across operations, engineering, maintenance, procurement, and external stakeholders while tracking priorities, dependencies, risks, and deliverables.

The experience gave me a practical understanding of how data, supply chains, business constraints, technical teams, and project execution come together in real operational environments.

Project Lead

AI Product Discovery · Project Leadership

AnnieGuard, BWTech @ UMBC Maryland New Venture Program | Jan 2025 - May 2025

AnnieGuard was an AI-enabled healthcare venture exploring the use of a machine-learning API for sarcoma detection. I led a four-person team through the Maryland New Venture Program, working across customer discovery, product definition, prioritization, and project execution.

01

Discovery & Problem Validation

Conducted 30+ stakeholder and customer interviews to understand user needs, workflow challenges, adoption barriers, and assumptions around the proposed solution.

02

Product Thinking

Translated Voice-of-Customer insights into product requirements and priorities, helping refine the problem statement and shape the direction of the proposed AI-enabled solution.

03

Project Leadership

Led a four-person team across milestones, sprint planning, responsibilities, risks, dependencies, stakeholder communication, and final deliverables.

04

Execution & Outcome

Improved team execution cadence, reduced task slippage, and led the project through the final venture presentation, resulting in a Pitch Night win.

AnnieGuard taught me that a strong AI model is only one part of a successful product. User needs, workflow fit, trust, adoption, execution, and measurable value determine whether the technology becomes useful.

Selected Projects

Selected Projects

Projects connecting analytics, operational decision-making, and AI-assisted workflows.

Flagship AI Product · Supply Chain · Decision Support

Supplier Intelligence Copilot

Evolved an existing SQL/Tableau supply-chain analytics project into an AI-assisted supplier decision-support prototype.

Designed the user problem, deterministic supplier-risk logic, trusted model context, structured AI output, guardrails, human-review boundaries, and future roadmap. Supplier risk is calculated deterministically. AI is used for interpretation, evidence-grounded explanation, healthy-signal identification, and recommended investigation.

Live Demo GitHub Case Study

Supply Chain Analytics · SQL · Tableau

Supply Chain Health Monitor

Built the analytical foundation behind the Supplier Intelligence Copilot using a 100-SKU dataset covering supplier quality, inventory, lead-time behavior, logistics, and profitability.

Used SQL-based business logic and Tableau dashboards to surface understocking, supplier-quality exposure, and other operational signals.

Tableau GitHub

Approach

How I Approach Operational + AI Problems

01

Start with the workflow

Before choosing a technology, understand the user, decision, source of truth, and real point of friction.

02

Separate trusted logic from AI

Keep rules and calculations deterministic when consistency matters. Use AI where interpretation and synthesis create real value.

03

Design the controls

Define what information reaches the model, what it can do, what can fail, and which actions require human approval.

04

Measure the outcome

A convincing AI response is not enough. Measure business value, AI quality, adoption, accuracy, effort, and decision speed.

Skills

Skills Across AI, Operations, Data & Execution

AI & Product Systems

Context Engineering, Structured LLM Outputs, AI Guardrails, Human-in-the-Loop Design, RAG Concepts, Tool Calling, Agentic Workflow Concepts, AI Evaluation, Product Discovery, Jobs to Be Done, MVP Definition, Prioritization

Project & Product Execution

Requirements Definition, Prioritization, Scope, Milestones, Dependencies, RAID Management, Stakeholder Management, Cross-Functional Coordination, Agile, Scrum, Kanban, RACI, WBS, Earned Value Management

Supply Chain & Operations

Supplier Performance, Procurement, Inventory Management, Production Planning, Demand Planning, SAP S/4HANA MM, Vendor Coordination, Operations Excellence, Process Improvement

Data & Analytics

SQL, Tableau, Power BI, Advanced Excel, DAX, Python/Pandas familiarity, Data Visualization, KPI Design, Operational Analytics

SQL Tableau Power BI Advanced Excel DAX SAP S/4HANA MM Supplier Performance Procurement Inventory Management Production Planning Context Engineering Structured Outputs AI Guardrails Human-in-the-Loop Design Requirements Definition Prioritization RAID Management Stakeholder Management Product Discovery Lean Six Sigma
Illustration of dashboards, project milestones, and performance metrics

About

From industrial operations to AI-enabled problem solving.

My career started in industrial operations, where I worked with production data, procurement workflows, suppliers, process improvement, and cross-functional teams. That environment taught me to think in systems and understand how decisions affect cost, quality, timelines, and execution.

Graduate study in Engineering Management expanded that foundation into project management, analytics, strategy, and product-oriented problem solving.

More recently, I have been building deeper AI product and technical fluency. My focus is not simply on prompting models. I want to understand where AI belongs in a workflow, what data it should trust, what should remain deterministic, how outputs should be evaluated, and where human control is required.

My strength is connecting business and operational context with project structure, product thinking, data, and technical teams to turn ambiguous problems into practical, executable solutions.

Education

Bachelor's Degree

B.Tech, Chemical Engineering

VNIT Nagpur | 2018 - 2022

Master's Degree

Master of Engineering Management

University of Maryland, Baltimore County | Aug 2024 - May 2026

Certificates

Certification

Lean Six Sigma Green Belt

CSSC credential focused on structured process improvement.

Certification

Google Project Management Certificate

Project planning, stakeholder communication, agile delivery, and execution fundamentals.

Certification

Google AI Essentials

Practical AI concepts for productivity and business workflows.

In Progress

Certified Associate in Project Management

CAPM certification in progress.

Let's Connect

Building at the intersection of operations, supply chain, AI and execution.

I’m interested in teams working on complex operational problems where technology needs to translate into something people can actually use.

LinkedIn GitHub Email View Live AI Demo