Back office ops · Production

Augment Code reduces Codem Inc.'s legacy migration time by over 50%

The problem

Codem Inc. faced time-consuming, resource-intensive legacy application modernizations — systems 10–15 years old, monolithic, undocumented, and unfamiliar to any current engineer — with typical semi-complex migrations taking two to three months.

First attempt

Codem had tried other AI coding tools before Augment but found them too shallow — they lacked the depth of codebase understanding needed for complex legacy migrations.

Workflow diagram · grounded in source
1
Legacy codebase received
trigger
“A lot of these applications are 10-15 years old, sometimes older, and they're very monolithic. There's no microservices; they're not containerized, and that definitely makes it very challenging”
2
Deep codebase analysis
ai_action
“The biggest difference is that it's not like your typical AI coding assistant; it goes much, much deeper. Nothing has come close to what Augment does to fully understand what's actually behind the codebase”
3
Automated code translation
ai_action
“streamlined the migration of a custom eCommerce platform to Shopify using Augment's automated code translation and integration capabilities”
4
AI POC development
ai_action
“The platform allowed Codem to quickly develop sophisticated AI proof-of-concepts for clients, including machine learning models for customer behavior prediction and natural language processing for enhanced search functionality”
5
QA and testing
validation
“We spend 20-30% of the entire project in the QA phase and in the testing phases. That part of the time frame has significantly come down”
6
Modernized architecture delivered
output
“Now we can offer these migrations for a fraction of the price than it was costing before”
Reported outcome

With Augment, Codem cut a typical semi-complex e-commerce migration from two to three months to under six weeks (over 50% faster), transitioned three legacy logistics apps to microservices with 50% time savings, significantly shortened QA cycles, and can offer migrations at a fraction of the previous cost.

Reported metrics
Migration time reductionover 50%
E-commerce stack migration durationless than six weeks
Logistics app migration time reduction50%
Migration cost for clientsfraction of the price
Show all 6 reported metrics
migration time reductionover 50%
e-commerce stack migration durationless than six weeks
logistics app migration time reduction50%
migration cost for clientsfraction of the price
QA phase durationsignificantly come down
AI POC implementation timewithin weeks
Reported stack
Augment CodeShopify
Source
https://www.augmentcode.com/customers/codem
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

With Augment, Codem cut a typical semi-complex e-commerce migration from two to three months to under six weeks (over 50% faster), transitioned three legacy logistics apps to microservices with 50% time savings, signi…

What tools did this team use?

Augment Code, Shopify.

What results were reported?

Migration time reduction: over 50%; E-commerce stack migration duration: less than six weeks; Logistics app migration time reduction: 50%; Migration cost for clients: fraction of the price (source-reported, not independently verified).

What failed first in this deployment?

Codem had tried other AI coding tools before Augment but found them too shallow — they lacked the depth of codebase understanding needed for complex legacy migrations.

How is this back office ops AI workflow structured?

Legacy codebase received → Deep codebase analysis → Automated code translation → AI POC development → QA and testing → Modernized architecture delivered.

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