Workflow automation
Cut down repetitive collecting, sorting, and sending.
Core business
AI Solutions
Requirements, design, build, and operations run as one continuous flow. We measure success by a system that actually runs, not by a delivery date.
What we build
We start with the work that eats up your team's time.
Data collection
Gather scattered data on a fixed schedule.
AI agents
Connect internal documents and systems so they can answer.
Web services
From a validation MVP to a production product.
Internal systems
Move internal work off spreadsheets and messengers.
Dashboards & alerting
Turn accumulated data into screens and notifications.
A service we run ourselves
We built and operate a service that collects sellers' daily sales, revenue, and ad spend from the marketplaces they sell on (Naver, Coupang, Ably, and others) and delivers it through a web dashboard and KakaoTalk notifications. More than 50 sellers use it, and it is now in its third year of operation. The development services above are built on what we learned running its collection, reporting, and alerting in production.
When to call us
If you deal with any of these every day, there is room to automate.
- Repetitive cleanup work. Collecting, copying, and sending never stops.
- Scattered data. Sales, costs, and inquiries all live in different places.
- The same questions, again. People keep answering what is already in the documents.
- Getting by on spreadsheets and chat. File versions and history keep getting tangled.
How we work
You can start without a written spec.
Requirements
Start with the hours you want back.
Design
Set the structure first, then split the scope.
Build & verify
Only what has been verified reaches real users.
Operate & maintain
We stay on after launch to run it.
Before you outsource
Development projects tend to go wrong for the same reasons. Check the scope, the records, and the test environment first.
"Our vendor is hard to communicate with."
When progress isn't recorded, answers come late too.
"Too many bugs, and the service keeps going down."
Shipping straight to production without a test environment makes problems bigger.
"Our developer just quit."
A project without records is hard to hand over.
"The project stalled halfway."
When scope and effort don't match, projects stop midway.
Here is what we check.
How we build
Design comes first
We set the structure before writing code.
Separate dev and production
New features are verified separately before going live.
History kept in writing
We record why decisions were made and what changed.
Code review
A second pair of eyes before every release.
Frequently asked questions
What kind of work can we hand over?
Repetitive workflow automation, data collection, AI agents, web services, and internal systems.
Do we need a detailed plan first?
No. We look at the problem with you and define the scope together.
How are timeline and cost decided?
We estimate after the scope is defined. We usually start small with a minimum viable product (MVP) that holds only the core features, keeping upfront cost low, then expand from the features people actually use.
Can you also run the system after it's built?
Yes. The form of the operations contract depends on the project.
Do we have to change the tools we use now?
By default, no. We start by cutting the repetitive work between the tools you already use.
How do you handle our data and account credentials?
We access only what is needed. Data constraints are built into the design.
Does it have to use AI?
No. If rules are enough for the job, we don't add AI.
Experience that carries into training
The standards we learn running systems carry over into what we teach.
See AI Education →Get started
Tell us what is eating up your time
Send us a short note about the work that keeps people tied up. We will review what can be built and get back to you.
info@sundaylager.com