Custom SAP-Like Web Application for Conveyor Operations Management (Built by an AI Pod)

About the Client

Our client is a UK-based manufacturing company with established production operations and internal process-management needs across conveyor-related workflows.

Before the project, the company ran its business processes on a combination of SAP and Google Sheets. SAP covered part of the operational functionality, while several important workflows were still managed in spreadsheets. The result was process fragmentation, limited visibility, manual effort, and additional operational overhead.

Challenge

The client needed to modernize business-critical operational workflows that lived outside SAP, in Google Sheets. These spreadsheet-based processes were difficult to scale and govern, creating inefficiencies for the teams responsible for conveyor operations.

The brief came with three defining requirements:

Replace fragmented spreadsheet workflows. Build and validate a custom, SAP-like web application to move core conveyor processes from Google Sheets to a structured web system, while partially covering selected SAP-adjacent processes.
Keep the business running during migration. The application had to integrate with both SAP and the client’s legacy Google Sheets environment, supporting continuity throughout the transition rather than forcing a hard cutover.
Deliver fast, with a leaner model. Rather than standing up a traditional team — frontend and backend engineers, QA, a PM, a BA, an architect, and DevOps — the MVP had to be delivered faster using an AI-native delivery model.

Solution We Delivered

We delivered a custom, SAP-like web application MVP that replaces the client’s Google Sheets-based conveyor management workflows and partially covers selected SAP-adjacent processes.

Delivery by a Single AI Pod

The project was delivered by one AI Pod (4 specialists) in place of a traditional nine-person team. The Pod brought together:

two AI-enabled engineers covering frontend, backend, and QA;
one PM/BA covering requirements, scope, coordination, and delivery alignment;
and one DevOps/Architect covering architecture, infrastructure, deployment, and technical governance.

An AI-Native Engineering Workflow

To orchestrate delivery, we set up an AI-native engineering workflow built on MCP, reusable prompt libraries, and specialized subagents — the operating layer that lets a compact team work at the pace the brief required.

An AI-Enabled SDLC with Human-in-the-Loop Validation

We implemented an AI-enabled SDLC using GitHub SpecKit, Claude Code, multi-agent development, and human-in-the-loop validation. This let the team move from structured requirements to working implementation faster, while every generated output stayed reviewed and controlled by experienced specialists.

Integration with SAP and Legacy Google Sheets

The application was built to integrate with both SAP and the client’s legacy Google Sheets environment, so the business kept running on its existing data while core workflows moved into the new system.

End-to-End Ownership

The AI Pod took ownership of delivery end-to-end — from requirements clarification and solution design through implementation, QA, deployment, and release support. The client used a single compact delivery unit rather than coordinating multiple roles across a traditional software team.

Client’s Results

MVP Delivered in 3 Months, Not 8

The client received a working MVP in three months instead of the estimated eight — a 63% reduction against the traditional timeline.

One AI Pod in Place of a Nine-Person Team

Delivery was handled by a single AI Pod of four specialists rather than a traditional nine-person team — a 56% smaller delivery team for the same scope.

Reduced Spreadsheet Dependency

Core conveyor workflows moved out of Google Sheets and into a structured, governable web system, cutting the fragmentation and manual overhead the client started with.

SAP Integration and Business Continuity

Integration with both SAP and the legacy Google Sheets environment kept the business running throughout migration, avoiding a disruptive hard cutover.

A Scalable Foundation

The MVP provides the client with a scalable foundation for extending SAP-like functionality as more processes move away from spreadsheets.

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