• 3PL and Logistics
  • SaaS
  • Business Processes Automation
  • Analytic platform
  • API Integration

Custom Analytics & Automation Platform for Laundry Operations

We built a custom operations platform that turned fragmented business data into a more reliable base for analytics and workflow automation. The system unified information across orders, payments, customer activity, and daily workflows, giving the client better visibility and stronger support for payment matching and future automation.

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Overview

Quick overview: key aspects of our work - discover the essentials of our project

Industry

3PL & Logistics

Country

USA

Solution type

Operations analytics platform, data integration, workflow automation

Services

Custom web platform development, API integrations, BI setup, automation workflows

About the client

Understanding our client: specifics, challenges, and custom solutions

Our client operates in the laundry services sector, where day-to-day performance depends on clear visibility across orders, customers, pickup and delivery activity, payments, staff reporting, and machine performance. As the business grew, the team needed a more structured way to manage operational data, track performance, group customers, and support connected workflows.

Problem

Operational data was spread across several systems and sources. Core records were pulled from the client’s laundry operations platform, transaction details came from payment processing, automated updates flowed in from connected systems, and additional reports arrived through emailed files. This made operational reporting harder to maintain, increased manual work around payment matching and updates, and reduced the team’s ability to support customer grouping, repeat-order analysis, and consistent operational visibility.

Solution

We delivered the platform in two stages. First, we built a secure setup for data access, analytics, and reporting. This included API connection to the client’s core laundry operations platform, automated database creation, and separate analytics access for each account. That first stage gave the client a controlled way to store and review operational data without cross-account exposure.
In the second stage, we expanded it into a broader operations system with a connected data and reporting layer. The platform brought customer, order, transaction, machine, and event data into one structured view, processed real-time updates, handled emailed operational reports, and supported self-hosted dashboards. This gave the client better payment visibility, stronger customer grouping, and a clearer path to future automation through connected tools and read-only API access.

Key features

Project features overview: essential enhancements and strategic solutions

  • feature

    Centralized Operational Data

    The system brought customer, order, transaction, machine, and event data into one structured view, replacing fragmented records with a more reliable source of operational data.

  • feature

    Operational Dashboards and Reporting

    We created self-hosted dashboards and reporting tools for tracking orders, customer activity, historical performance, and day-to-day trends, giving the team a clearer view of performance in one place.

  • feature

    Pickup & Delivery Performance Monitoring

    The system gave the team clearer visibility into pickup and delivery activity, route performance, and on-time execution, making daily monitoring more consistent and easier to review.

  • feature

    Connected Operational Workflows

    The platform linked reporting, order data, and related workflows, helping the team manage day-to-day processes in a more coordinated way.

Result

Performance Showcase: Unveiling the Results of Our Collaborative Endeavors

The project replaced fragmented reporting and disconnected updates with a more reliable analytics and performance-tracking setup. The client gained clearer visibility across orders, payments, customer activity, and day-to-day workflows, along with better payment visibility, stronger customer grouping, and a clearer path to future automation.

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