DATA COLLECTION
People still pull data from multiple services by hand.
DATA & REPORTINGAUTOMATION
Gather scattered data
and turn it into what you need.
We collect and organize data spread across services and documents, then automate the metrics and reports you need — from recurring collection and cleanup to calculation, visualization, report generation, and delivery.
OVERVIEW
Spend less time gathering data,
more time using it.
Teams constantly create data across many services.
When sales, inquiries, marketing, product usage, projects, surveys, reviews, and ops data live in different places, people end up hunting, copying, and cleaning by hand.
DATA & REPORTING connects that repetitive work into one data flow — pull what you need, clean by rules, calculate key metrics, and deliver as a Dashboard or Report.
PROBLEMS
Work we can automate.
DATA CLEANING
Formats differ and cleanup happens every time.
RECURRING REPORT
Weekly or monthly reports are rebuilt repeatedly.
METRIC TRACKING
Sales, users, inquiries, and conversion need ongoing tracking.
MULTIPLE SOURCES
Data is scattered across spreadsheets, forms, and databases.
REPORT DELIVERY
Finished reports must reach owners on a schedule.
BEFORE / AFTER
Manual reporting vs
automated DATA & REPORTING
01
MANUAL
- 01
Copy data from each service
- 02
Paste into spreadsheets
- 03
Calculate metrics by hand
- 04
Rebuild the report every cycle
02
AUTOMATED
- 01
Collect from sources automatically
- 02
Clean data on defined rules
- 03
Calculate metrics automatically
- 04
Deliver reports and dashboards on schedule
CAPABILITIES
We build the data flow you need.
DATA COLLECTION
Pull required data from multiple sources.
DATA CLEANING
Clean duplicates, empty values, and format gaps by defined rules.
DATA TRANSFORM
Transform raw data into shapes ready for analysis and reporting.
METRIC CALCULATION
Calculate metrics like revenue, growth, conversion, and users.
AUTOMATED REPORT
Generate reports on weekly, monthly, or other cadences.
DASHBOARD
Build a dashboard that keeps key metrics visible in one place.
AI SUMMARY
When needed, summarize data or customer feedback with AI.
REPORT DELIVERY
Deliver results to email, spreadsheets, dashboards, or other destinations.
USE CASES
Systems we can build.
Buildable examples
SALES REPORT
Auto-collect sales data into daily, weekly, or monthly reports.
MARKETING REPORT
Organize ads and marketing data to compare channel performance.
CUSTOMER REPORT
Organize inquiries and feedback to spot recurring issues and requests.
REVIEW REPORT
Collect product reviews and summarize themes, issues, and rating trends.
PRODUCT REPORT
Organize user and product data into core product metrics.
OPERATIONS REPORT
Collect ops data into recurring operational status reports.
EXECUTIVE SUMMARY
Summarize multiple sources into decision-ready key metrics.
AI FEEDBACK SUMMARY
Classify and summarize large text feedback into core opinions.
EXAMPLE WORKFLOW
How data becomes a report
COLLECT
Pull from spreadsheets, databases, and APIs.
We design connections and collection schedules together.
CLEAN
Fix duplicates, gaps, and format mismatches.
Data is normalized to your defined rules.
PROCESS
Run required calculations and transforms.
Shape data for the metrics you need.
ANALYZE
Extract key metrics and needed insights.
Compare trends and spot anomalies.
REPORT
Generate a dashboard or report.
Built in a form your team can use immediately.
DELIVER
Send results by email or to a chosen destination.
Delivered automatically on schedule.
DATA SOURCES
Connect the data you already use.
- Google Sheets
- Excel / CSV
- Forms
- Database
- Website Data
- App Data
- Analytics
- CRM
- E-commerce Data
- Marketing Data
- Customer Feedback
- Reviews
- External API
Actual connectivity depends on each service’s API and data-access method.
OUTPUT
Reports carry only what you need.
Depending on the project, reports can include items like these. Content is not identical across projects — it follows your goals.
Dashboards are not automatically included — they are added by project scope.
AI REPORTING
Organize meaning, not just numbers.
When needed, AI can summarize large text and data into forms people can review quickly.
Review theme summaries
Recurring complaint detection
Positive feedback grouping
Customer request classification
Period-over-period explanations
Report summary drafts
AI analysis and summaries are for reference. Important decisions may still require checking the source data.
PROJECT SCOPE
A way to understand project complexity.
These are reference levels for quoting — not fixed packages.
01BASIC REPORT AUTOMATION
- One or a few data sources
- Basic cleanup
- Core metrics
- Scheduled report
- Simple delivery
02MULTI-SOURCE REPORTING
- Multiple sources
- Data consolidation
- Multiple metrics
- Automated reports
- Conditional processing
03CUSTOM DATA SYSTEM
- Multi-system integration
- Custom database
- Web dashboard
- Advanced metrics
- AI analysis
- Custom automation
PROJECT COST
Custom quote per project.
Access permissions, APIs, data quality, and required features can change the schedule.
Simple Report Automation
Multiple Data Sources
Custom Dashboard / Complex Data System
DATA & REPORTING
From ₩500,000
Final quotes are set after reviewing your current data environment and required features.
What shapes the quote
- Number of data sourcesConnectors and inputs
- Data volume and structureVolume, schema, quality
- API integrationExternal and internal APIs
- Cleanup complexityETL and normalization depth
- Number of metricsKPIs and derived fields
- Automation workflowCollection and refresh jobs
- Dashboard needViews and chart scope
- AI featuresSummaries, classification, insight
PROCESS
We start with the data structure.
DISCOVERY
Confirm what data you manage and where it lives.
DATA AUDIT
Review formats, access methods, and quality.
METRICS
Define the metrics and report purpose that matter.
ARCHITECTURE
Design collect → process → store → report.
BUILD
Implement the automation pipeline and report/dashboard.
TEST
Validate calculations and outputs with real data.
LAUNCH
Set up scheduled runs and delivery.
HANDOFF
Hand off ops guidance and basic management notes.
DELIVERABLES
What you receive after the project
Depending on scope, we provide the deliverables you need from the list below. Not every project includes every item.
Data Collection Flow
Data Cleaning Rules
Metric Definition
Automation Workflow
Report Template
Automated Report
Dashboard
Scheduled Reporting
AI Summary
Data Export
Basic Documentation
Ops guidance
WHO IT'S FOR
Who it's for
- 01
Teams rebuilding weekly or monthly reports
- 02
Data scattered across multiple services
- 03
Manual spreadsheet collection to cut down
- 04
Teams that want key metrics in one place
FAQ
Questions, answered
Spreadsheets, CSV, databases, analytics, forms, and external APIs are common. Actual connectivity depends on each service’s access method and API.
Yes. We review the current structure, then define cleanup and automation scope.
Depending on scope, we can build scheduled processing and delivery.
Yes. Metrics, refresh method, and user context are scoped separately when needed.
Yes — for example classifying and summarizing reviews, inquiries, and survey text.
We start by reviewing current data quality. Heavy cleanup may be scoped as additional work.
It depends on the source and API. Real-time processing is not guaranteed for every system.
Yes — source changes, automation edits, and feature additions can be scoped separately.
START A PROJECT
Automate the reports
you still build by hand.
Tell us the data you use and the reports you repeat. We’ll outline how collection, cleanup, and delivery can connect — and what the project scope looks like.