More Calls. More Builds. The #BuildMoreWithBuildAgent Challenge is here!

[laurentapia]

More Calls. More Builds. The #BuildMoreWithBuildAgent Challenge is here!

Last year, you showed us what was possible with the power of Build Agent. The apps you created, the prompts you shared, and the ideas you brought to life using Build Agent inspired our Community of over one million practitioners. 

Now, with the Australia release, Build Agent is more powerful and more accessible than ever. And we're ready to do it all again. 

Introducing #BuildMoreWithBuildAgent: a two-week challenge inviting ServiceNow practitioners of all levels to create a new application or expand on an existing one using Build Agent. 

Whether you participated in the original #BuildWithBuildAgent challenge or you're picking up Build Agent for the first time, this is your chance to vibe code with ServiceNow and see just how fast you can build an amazing app. 

What is Build Agent? 

ServiceNow Build Agent is a smart AI tool that helps you build, edit, and deploy full-stack applications via a conversational interface. It writes the code, organizes your files, fixes errors as it goes, and takes care of both the core logic and the UI.  

Built natively on the ServiceNow AI Platform, it understands the context of your existing workflows, data, and systems so what it builds actually fits your environment. Just describe what you want to create, and Build Agent manages the entire build process. 

With the Australia release, you now have more room to build than ever before: 

• Customer instances include 100 free Build Agent calls per month
• Personal Developer Instances (PDIs) include 25 free calls per month

More calls mean more space to experiment. 

 Why Join the #BuildMoreWithBuildAgent Challenge? 

• Get hands-on with one of ServiceNow's most innovative AI tools and see what you can build with increased call availability.
• Inspire a Community of over one million practitioners.
• Earn recognition in the Community by sharing what you built. 

Attending CreatorCon 2026 during Knowledge? Six outstanding applications will be selected to win a gift card for exclusive swag at the K26 Store. Winners will be contacted directly before the event. 
 
Can't make it to Las Vegas? You can still participate and redeem your reward online. 

How to Participate

1. Set Up Your Instance: Request a free Personal Developer Instance at developer.servicenow.com to start building immediately. 

1. Build: Create a new application or edit an existing ServiceNow IDE app using natural language prompts.  

1. Document: Share your application on social media with a description, video, or infographic showcasing your app and share the prompts that brought it to life. Make sure you include #BuildMoreWithBuildAgent in your post! 

1. Share: Comment on this blog post with a link to your social post and a brief description of what you built. 

Build and submit before May 4 to be eligible for recognition and a chance to win a gift card for exclusive K26 Store swag, redeemable online or on-site at the event. 

Getting Started with Build Agent 

New to Build Agent? Check out our original #BuildWithBuildAgent Challenge blog here for a full walkthrough, helpful resources, and FAQs to get you up and running. We can't wait to see what you build. 

Request a Free PDI and Start Building 

Terms and Conditions   

No purchase is necessary. #BuildMoreWithBuildAgent Challenge is open only to individuals at least eighteen (18) years old at the time of entry. The Challenge begins April 14, 2026, at 10:00 a.m. Pacific Daylight Time ("PDT") and ends on May 4, 2026, at 11:59 p.m. PDT.   

Entrants must respond to the official forum with a 1) Screenshot, graphic, or video showing their app built using Build Agent or 2) a 300 minimum word description of the app they built with a screenshot using Build Agent AND entrants must post their video or blog into the ServiceNow Community Developer forum here AND share it on LinkedIn or Twitter with #BuildWithBuildAgent Challenge on their post AND the social media post will be linked to their forum post.    

The Submission must be your own, original work; The Submission must contain a relevant reason/response to the prompt of Build Agent; The Submission must meet the format and size requirements of the social platform used to enter; The Submission must conform with any applicable social media platform terms.   

The prize includes a gift card redeemable online or at Knowledge 2026. Approximate Retail Value (“ARV”): $50 USD.   

The ServiceNow Community reserves the right to access email data provided by the entrant in order to reach out to individuals who have completed the challenge. Entrants who have met the guidelines and have successfully completed the challenge will receive an email from ServiceNow with instructions on how to redeem the prize. International country restrictions will apply.   

Except where prohibited, participation in the Challenge constitutes each entrant's consent to use submission’s name, and photograph (including, without limitation, entrant’s Twitter and LinkedIn profile photo), voice, opinions and/or hometown and state for promotional purposes in any media, worldwide, without further payment or consideration. 

[neha_talha]

Hello @laurentapia ,

Successfully completed the #BuildMoreWithBuildAgent Challenge!

LinkedIn Post (Challenge Submission): Click to open Link

Built something beyond a tracking system — a decision-driven logistics intelligence platform.

Smart Logistics Optimizer & Delay Predictor
An AI-powered logistics application designed to:

✔ Optimize delivery routes for efficiency
✔ Predict shipment delays using risk scoring
✔ Identify high-risk shipments proactively
✔ Enable faster and smarter logistics decisions

What I Built

Intelligence Layer

• Shipment delay prediction based on distance and priority

• Risk scoring (Low / Medium / High)

• Identification of high-risk deliveries

Action Layer

• Auto-create tasks for high-risk shipments

• Trigger alerts and notifications

• Recommend actions like:

  • Assign priority handling

  • Choose alternate routes

  • Escalate critical deliveries

Optimization Layer

• Route efficiency insights

• Delay trend analysis

• Shipment performance monitoring

Experience

• Clean, modern dashboard

• Color-coded risk visualization (Green / Yellow / Red)

• Interactive charts showing:

  • Risk distribution

  • Shipment status

  • Delay trends

Designed to feel like a real-time logistics command center

Built entirely using natural language prompts with Build Agent

Prompt used:

Create a complete ServiceNow application named "Smart Logistics Optimizer & Delay Predictor".

Objective:
Build a decision-driven logistics system that optimizes delivery routes and predicts shipment delays.

Core Features:

• Shipment management with fields: pickup location, delivery location, distance, priority, and status

• Route optimization based on distance

• Delay prediction using risk levels (Low, Medium, High)

• Recommended actions based on risk

Business Logic:

• If distance is greater than 100, set risk as High

• If distance is between 50 and 100, set risk as Medium

• If priority is High, reduce risk level

• Assign recommended actions based on final risk level

Automation:

• Create a task automatically for high-risk shipments

• Send notification alerts for high-risk shipments

• Escalate critical shipments

Dashboard:

• Show total shipments

• Show high-risk shipments

• Display delay trends

• Display risk distribution

Demo Data:

• Generate 80 to 100 shipment records

• Ensure balanced distribution of risk levels and priorities

• Ensure dashboard is fully populated with meaningful insights

Goal:
Create a realistic, decision-driven logistics platform with automation, analytics, and a fully populated dashboard for demonstration.

 
Thank you, 
Neha Talha

[amlanpal]

I have build #GuardianUK: Transforming Workplace Compliance through Research & Anonymity!

GuardianUK is a zero-knowledge anonymous workplace compliance reporting system built on ServiceNow, designed for the United Kingdom. It allows workers across all UK regions and employment sectors to report compliance violations without revealing their identity, while providing leadership with research-backed risk intelligence powered by the Cambridge Centre for Business Research Labour Regulation Index.

This is what the #BuildWithBuildAgent challenge delivered with GuardianUK app.
1. 🗄️ Data Model — 4 Custom Tables
2. 🔒 Privacy & Security Engine — 3 Script Includes

3. 🔄 Flow Automation — Anonymous Intake Processing

4. 🤖 Scheduled Automation — 3 Jobs
5. 📊 Cambridge CBR-LRI Live Integration — 18 Variables
6. 🌐 Service Portal — Anonymous Intake & Leadership Dashboard
8. 🧪 ATF Test Framework — 5 Test Suites

9. 📚 Documentation — 16+ Guides

Happy Learning!!

Visit my LinkedIn Post here!

[sebastian_lim]

As part of the #BuildMoreWithBuildAgent Challenge, I used ServiceNow’s Build Agent to create an AI-powered Skills Intelligence & Internal Mobility Platform — built entirely from natural language prompts.

You can find my social post here on LinkedIn.

Last year, I focused on digitizing HR workflows. This time, I wanted to take it a step further and explore how GenAI can help organizations move towards a skills-based workforce, where talent decisions are driven by real capability data rather than static job descriptions.

The idea came from a common challenge many organizations face today: limited visibility into employee skills, fragmented training data, and underutilized internal talent. Employees often don’t know what roles they can grow into, managers lack insights into team capabilities, and HR teams struggle to identify skill gaps at scale.

To address this, I designed a unified platform that connects employee profiles, skills, roles, training, and internal opportunities into a single, intelligent system.

It includes:

👤Employee dashboard with skills profile, role match scoring, career path recommendations, and internal opportunities
👨‍💼Manager view with team skills heatmap and gap analysis to support better workforce planning
🏢HR analytics providing organization-wide insights into skill distribution, demand trends, and capability gaps
🤖AI assistant that helps employees understand what roles they can move into, what skills they are missing, and how to grow
🚀Skills Intelligence Launchpad for admins, offering a centralized control center with one-click access to dashboards, data, and APIs

What stood out most was how quickly this came together. With just prompts, Build Agent generated the data model, application logic, dashboards, and even sample data — transforming an idea into a working solution within minutes.

Beyond the technical build, this project also reflects how HR platforms are evolving — from systems of record into systems of intelligence that actively guide workforce decisions.

This build demonstrates how GenAI can move HR beyond process automation towards data-driven talent decisions, internal mobility enablement, and more personalized employee growth journeys.

[1__vipind]

🚨 Core Problem Statement:

"Organizations waste $1.3 trillion globally on food waste while employees struggle with poor nutrition choices and inconsistent cafeteria experiences across hybrid work models."

Solution -  Smart Cafeteria Planner 2.0 -An AI-powered platform reimagining how organisations manage food services across office, hybrid, and remote work environments.

Linkedin -https://www.linkedin.com/feed/update/urn:li:activity:7456261148921884673/

Smart cafeteria Planner 2.0 - https://dev199293.service-now.com/x_1344480_smart_ca_ai_demo_dashboard.do

[Aljo2]

Sharing my Build Agent experiment here: Stale Ticket Auto-Cleanup app 

I built a Stale Ticket Auto-Cleanup app to tackle inactive ITSM tickets using ServiceNow Build Agent within a PDI.

The app automates the lifecycle of stale tickets:
- Day 3 → Reminder
- Day 5 → Escalation
- Day 7 → Auto-resolution
- Day 10 → Closure with audit trail

This was also an experiment to test Build Agent’s limits within 10 prompts. It helped generate ~70–80% of the application (workflow, data model, initial UI), while the remaining work involved refining logic, handling edge cases, and making the solution production-safe.

Overall, it felt less like low-code and more like AI-assisted solution design.

[rajumunta]

Successfully completed the    #BuildWithBuildAgent   Challenge!

View my LinkedIn post here!  

AI CI Relationship Auditor - Automated CMDB Relationship Discovery with Now LLM

The Problem: CMDB Relationship Debt is Real

Every ServiceNow CMDB architect knows the pain — thousands of Configuration Items exist in the system but their relationships are incomplete, stale, or simply missing. Discovery tools capture CIs reliably, but relationship mapping still depends heavily on manual effort from engineers who understand the topology. The result? Service maps with gaps, impact analysis that misses upstream dependencies, and CSDM 4.0 compliance scores that never quite reach green. And without a strong foundational strong CMDB (3C’s) those gaps cascade into everything dependent/built upon it (ITSM/ITOM/ITAM etc.)

I set out to solve this few months back and was able to build a full working pipeline that achieved this with my own MCP Server integrated with my PDI and Groq llama-3.3-70b-versatile model on free tier. As part of this challenge, I used Build Agent to build this custom ServiceNow app that uses Now LLM native to do what the initial app version was doing. It is highly tedious process for us to be reading raw discovery logs and inferring the relationships hidden inside them.

The Solution: AI CI Relationship Auditor

App Scope: x_2033102_ai_ci_re Platform: ServiceNow Zurich Release (PDI) AI Engine: Now LLM (PDI-compatible fallback that simulates LLM behavior) Built with: ServiceNow Build Agent (Now IDE)

The AI CI Relationship Auditor is a scoped ServiceNow application that automates CMDB relationship discovery using a three-stage AI pipeline:

Stage 1 — CIAudLLMParser (LLM Extraction)

Takes raw discovery log text from the Log Staging table, builds a structured prompt containing the log content and a list of 2000 known CIs from the CMDB (ordered alphabetically to prioritize meaningful named CIs), and calls the Now LLM (PDI compatible fallback) analyses the log and returns a JSON array of inferred CI-to-CI relationships with confidence scores and evidence citations from the log text.
Stage 2 — CIAudIREValidator (Relationship Validation)

Each LLM-extracted candidate is validated: source and target CI names are resolved against cmdb_ci (exact match first, then CONTAINS fallback), the relationship type is mapped to a cmdb_rel_type sys_id, and duplicate checks are run against existing cmdb_rel_ci records. Invalid or duplicate candidates are logged and discarded.
Stage 3 — CIAudCMDBWriter (Confidence-Based Routing)

Validated candidates are routed by confidence tier:

• High (≥ 0.85): Automatically inserted into cmdb_rel_ci — no human intervention needed
• Medium (0.60–0.84): Staged in the Relationship Candidate table for human review
• Low (< 0.60): Written to the CI Audit Log with rejection reason

Build Agent in Action

I used Build Agent throughout the development of this app to accelerate scaffolding, prompt engineering, and pipeline logic. Key areas where Build Agent assisted:

Build Agent prompt — "Create a Script Include named CIAudLLMParser that calls an external REST API with a structured prompt and parses the JSON response"

Build Agent generating the confidence-tier routing logic in CIAudCMDBWriter

Build Agent dramatically reduced the time spent on boilerplate ServiceNow code — letting me focus on the CMDB architecture, prompt engineering, and validation logic that makes the app genuinely useful.

Real Results on My PDI

New relationships written to cmdb_rel_ci automatically — with ServiceNow Service Mapping correctly triggering layer recomputation on each insert, confirming the relationships are topologically sound.

Performance Analytics Dashboard

The app ships with a full CI Relationship Auditor Health Dashboard built in Analytics Hub (Next Experience) with 6 PA indicators:

• Candidates Extracted (7-day rolling)
• Auto-Written Relationships
• Pending Human Review
• Average Confidence Score
• Logs Processed (24h)
• Rejected Candidates

All indicators use Real Time collection against the AIAuditor.RelationshipCandidate Indicator Source for live data.

What's Included in the App Package

• 6 Script Includes: CIAudLLMParser, CIAudIREValidator, CIAudCMDBWriter, CIAudPipelineRunner, CIAudPASetup and CIAudDashboardAjax
• 3 Custom Tables: Log Staging, Relationship Candidate, CI Audit Log
• 6 PA Indicators + 1 Indicator Source + Health Dashboard
• 1 Business Rule (auto-populates confidence tier on staging)
• 2 UI Actions (Approve / Reject candidate)
• 6 System Properties (all scoped to x_2033102_ai_ci_re)

Why This Matters for CMDB Health

This app directly addresses two of the most common CMDB compliance failures in enterprise ServiceNow environments:

1. Missing relationships — the app surfaces them automatically from existing discovery data.
2. Stale topology — every pipeline run is logged and auditable, making drift visible over time

For any organization running CSDM 4.0, automated relationship discovery is the missing link between good CI population and a genuinely useful service model.

#ServiceNow    #BuildWithBuildAgent

Video Playlist of all 11 steps/Prompts using Build Agent 

AI CI Relationship Auditor Full Design Guide 

Buzz me for the full 34 page Design Guidance document!

[naveen kumar24]

HI Everyone

 Completed the #BuildMoreWithBuildAgent Challenge!

XML Manager Application - Complete Overview

🎯 Purpose

A ServiceNow application that allows users to upload, process, and manage XML files containing ServiceNow data exports (like incident records). The app can parse XML files, extract table records and field data, and automatically create or update records in the appropriate ServiceNow tables using the original sys_ids.

🏗️ Application Architecture

Frontend (React UI)

• Location: src/client/
• Main App: Modern React interface with professional styling
• Components:
• FileUpload.jsx - File upload with drag & drop + manual XML input
• XMLFileList.jsx - Interactive cards showing XML files with expand/collapse
• XMLService.js - Client-side service for API calls
• Features: Upload XML, view file details, process/revert/delete buttons

Backend (ServiceNow)

• XML File Table: x_1739441_xml_mana_xml_file - Stores uploaded XML files and processing status
• Script Include: XMLProcessor - Core XML parsing and record creation logic
• REST API: /api/x_1739441_xml_mana/xml_processor/ - Endpoints for process/revert operations
• UI Page: ServiceNow UI Page hosting the React application

📋 Core Features

1. XML File Management

• Upload XML files via file selection or direct text input
• Store original content for revert capability
• Track processing status (pending → processed/error/reverted)
• View detailed file information and XML content

1. Smart XML Processing

• Parses ServiceNow XML exports to find table elements (<incident>, <sys_journal_field>, etc.)
• Extracts sys_id and field values from each record
• Handles complex XML with display_value attributes and empty/self-closing tags
• Multi-table support - processes multiple record types in single XML file

1. Database Operations

• Insert/Update Logic: Uses sys_id as primary key
• If record exists → Updates with new field values
• If record doesn't exist → Creates new record with specific sys_id
• Field Type Handling: Correctly handles strings, numbers, booleans, dates, references
• Validation: Checks valid fields before setting values

1. User Interface

• Upload Section: Multiple ways to add XML content
• File Cards: Expandable cards showing file details, processing status, XML preview
• Action Buttons: Process, Revert, Delete with loading states
• Status Indicators: Visual indicators for pending/processed/error/reverted states
• Error Messages: Detailed feedback on processing results

🔧 Technical Implementation

Data Flow

1. Upload → XML stored in x_1739441_xml_mana_xml_file table
2. Process Click → React calls REST API endpoint
3. REST API → Calls XMLProcessor.processXMLFile()
4. XML Processing → Parses XML, extracts records, creates/updates in target tables
5. Status Update → XML file record updated with results
6. UI Refresh → Interface shows updated status and results

https://www.linkedin.com/posts/naveen-kumar-a88373151_buildmorewithbuildagent-buildmorewithbuildagen...

[Akshay Kanerkar]

🔗LinkedIn Post: Link

Project: Hospital Resource Utilization Analyzer

I created a Hospital Resource Utilization Analyzer using ServiceNow Build Agent to explore how resource usage can be monitored and optimized through data-driven insights.

🧠 Overview
The application is designed to track hospital resources such as beds, medical staff, and equipment across different departments. It evaluates how efficiently these resources are being used and highlights areas that require attention.

⚙️Key Capabilities
• Tracks resources across departments like ICU, Emergency, General Ward, and Radiology
• Calculates utilization percentage based on capacity and current usage
• Classifies resources into:

• Overutilized

• Optimal

• Underutilized
  • Identifies high-pressure areas and unused capacity
  • Generates alerts for resources that cross utilization thresholds

📊Dashboard Highlights
• KPI indicators for total, overutilized, optimal, and underutilized resources
• Visual charts for utilization distribution and department-wise analysis
• Lists showing critical resources and optimization opportunities
• Color-coded indicators for quick interpretation

⚡Automation
• Tasks/alerts created automatically for overutilized resources
• Underutilized resources highlighted for better allocation planning

📈Outcome
The application provides a clear and practical view of resource usage, helping identify bottlenecks and improve operational efficiency through better planning and decision-making.

Built entirely using natural language prompts with Build Agent.

🖱Prompt

Create a scoped application called "Hospital Resource Utilization Analyzer" with realistic demo data and a visually rich dashboard.

Demo Data Requirements:

- Generate at least 50–100 sample records across multiple resource types:
- Beds
- Medical Staff (Doctors/Nurses)
- Equipment (e.g., MRI, Ventilators)

- Ensure data variation:
- Different hospital departments (ICU, Emergency, General Ward, Radiology)
- Capacity range:
- Beds: 10 to 150
- Staff: 5 to 50
- Equipment: 2 to 20

- Utilization distribution:
- 20–30% Overutilized (>85%)
- 40–50% Optimal (60–85%)
- 20–30% Underutilized (<60%)

- Automatically calculate:
- Utilization percentage
- Utilization status (Overutilized, Optimal, Underutilized)
- Resource pressure level (Low, Medium, High)
- Suggested actions (e.g., “Allocate more staff”, “Redistribute load”, “Idle capacity available”)

- Ensure realistic mix:
- ICU and Emergency should show higher utilization
- General Ward and some equipment should show mixed utilization

Dashboard Enhancements:

Create a visually appealing dashboard with the following widgets:

1. KPI Indicators:
- Total Resources
- Overutilized Resources
- Optimal Resources
- Underutilized Resources

2. Charts:
- Pie Chart: Resource Utilization Status Distribution
- Bar Chart: Department vs Utilization %
- Bar Chart: Resource Type (Beds vs Staff vs Equipment)
- Trend Chart: Utilization over time (if possible)

3. Lists:
- Top 10 Overutilized Resources
- Underutilized Resources (Optimization Opportunities)

4. Visual Improvements:
- Use colors:
- Red = Overutilized
- Yellow = Optimal
- Blue = Underutilized
- Make dashboard clean, modern, and easy to interpret

Automation:

- If utilization > 85%, automatically create an alert/task
- If utilization < 50%, mark as optimization opportunity
- Add indicators or badges for quick visibility

Goal:

The dashboard should look fully populated, realistic, and insightful, demonstrating a real-world hospital resource monitoring system with meaningful analytics and actionable insights.

#BuildMoreWithBuildAgent

[Anjy Choudhary]

Hello Community,

I’m excited to share my submission for the #BuildMoreWithBuildAgent Challenge —
The Perinatal Sanctuary – A Fourth-Trimester Wellbeing Companion

This application is designed to support new mothers through the emotional, physical, and lifestyle changes that come after childbirth by combining daily self-reflection, AI-assisted wellbeing guidance, educational content, expert support, and safety escalation workflows.

🔹 Key Features:

Daily wellbeing check-ins across mood, anxiety, sleep, energy, bonding, recovery, and support
AI-assisted wellbeing reports based on check-in responses
Personalized article recommendations from a postpartum knowledge library
Expert support request creation and tracking
Role-based dashboards for Mothers, Experts, Moderators, and Admins
Clickable dashboard metrics linked to relevant records
Demo-ready support tickets, check-in history, and workflow data

🔹 Built Using Build Agent:

The application experience — including user flows, data structure, UI, workflows, dashboards, support tickets, knowledge content, and demo data — was created using natural language prompts with ServiceNow Build Agent.

🔹 Impact:

Helps mothers reflect on their daily wellbeing
Makes emotional and lifestyle patterns easier to understand
Connects users with relevant guidance and support
Enables timely human review for sensitive or high-risk signals
Shows how ServiceNow can be used to build people-centric applications beyond traditional enterprise workflows

It is designed as a supportive wellbeing companion focused on reflection, education, progress tracking, and human escalation when needed.

LinkedIn Post: ThePerinatalSanctuary

Looking forward to your feedback!

[VaishnaviD]

Hello @laurentapia ,

🚀 #BuildMoreWithBuildAgent Challenge Submission

Designed and implemented a Universal Request Management System on ServiceNow using Build Agent to eliminate siloed request handling across IT, HR, and Facilities and provide a unified, real-time operational view.

🔧 Architecture & Data Model
Implemented a parent-child architecture with a custom Universal Request table acting as the single source of truth
Designed related tables for Child Tasks and SLA Tracking to handle multi-department execution
Established relationships to ensure data normalization, traceability, and lifecycle consistency
⚙️ Workflow & Automation
Built event-driven flows using Flow Designer to:
Automatically generate department-specific tasks based on request type
Orchestrate approvals and notifications
Maintain parent-child synchronization (task updates roll up to the parent request)
Enabled end-to-end lifecycle automation from request initiation to closure
🤖 AI & Intelligence Layer
Integrated Build Agent capabilities for:
Intelligent assignment based on request category and historical patterns
Dynamic priority scoring using urgency indicators
Predictive SLA breach detection with confidence scoring
Shifted the system from reactive tracking to proactive decision-making
📊 Observability & Dashboarding
Developed a real-time dashboard with:
Request volume distribution across departments
Status funnel (Requested → Approved → In Progress → Closed)
Average fulfillment time and SLA compliance indicators
Drill-down capabilities for request and task-level visibility
Provided operational insights and bottleneck identification
🔐 Security & Governance
Implemented role-based ACLs for strict department-level data isolation
Enabled manager-level override for cross-functional visibility
Secured APIs and data access with granular permission controls
🔌 Integration & Extensibility
Exposed RESTful APIs for external integrations
Designed the solution to be scalable and extensible for additional departments or workflows
🎯 Outcome
This solution demonstrates how Build Agent can be leveraged to rapidly build intelligent, scalable, and event-driven enterprise workflows, enabling:

Unified request visibility
Faster fulfillment and reduced delays
Improved governance and operational efficiency

 LinkedIn Post: Click Here!!