Reports and spreadsheets
We organize data, generate summaries, merge information, and reduce manual copying.
The person behind MorenaTech
Process automation,no no-code black boxes.
MorenaTech helps companies turn manual, repetitive processes into solutions that can be checked, maintained, and developed. Behind that approach is the experience of an automation tester and the practice of building tools around a real client problem.
Michał Chlewicki
founder and developer of MorenaTech
My name is Michał Chlewicki and I am the technical person behind MorenaTech. I have worked in testing and automation since 2011. For eight years I worked for one of the largest technology companies in the world: Intel.
That experience taught me to look at technology practically: a solution should not only work, it should also be testable, maintainable, and ready to grow.
Approach
Automation starts with the process
We do not start by asking which tool to use. We start by asking which part of the company’s work repeats so often that it should stop being manual.
data is copied between systems, spreadsheets, or email
reports, documents, or PDFs are created manually after the fact
the team keeps track of statuses, attachments, deadlines, or notifications by hand
the company has a process that works only because someone keeps watching it all the time
Good automation is not a technology show. It is a piece of process that works predictably, can be checked, and can grow when the company grows or changes its way of working.
What we do
We help companies automate concrete parts of daily work
We automate data, documents, spreadsheets, email, reports, leads, and the flow of information between tools. First the process, then the technology.
Documents and PDFs
We automate protocols, reports, offers, and summaries built from forms, spreadsheets, or application data.
Email and communication
We create message templates, notifications, statuses, and sending workflows that do not need constant manual supervision.
Leads and company data
We automate collecting, sorting, filtering, and preparing data for the next step instead of leaving the company with a chaotic export in a spreadsheet.
Internal processes
We build tools for statuses, checklists, activity history, attachments, customer data, and a simple flow of information.
Without no-code
Simple does not mean random
No-code can be useful for quickly testing an idea. The problem starts when a company wants to build a repeatable, maintainable process on top of it and fit it to real client data.
At MorenaTech, automations are built technically. That gives more control over logic, data, integrations, tests, and future development.
If the company has a simple problem, the solution can also be simple. But simplicity should not mean a black box that nobody understands or can fix.
Solution examples
From process to a working tool
Each example is described in business terms, but the Tech block also shows what actually works underneath. No imaginary features added for effect.
Mobile Service Protocol
Problem
Service companies often have to gather photos, notes, customer data, and protocol details manually after the work is done.
Result
The application organizes the visit, attachments, status, and PDF document, leaving a clear record after every job.
Tech
Web application, protocol forms, checklists, photos and attachments, PDF generation, file archiving, statuses, email events, change history, automated tests, and deployment options tailored to the client’s process.
Lead automation vs Instant Data Scraper
Problem
Instant Data Scraper helps collect data, but the export alone does not solve the full process of acquiring and handling leads.
Result
Lead automation closes the next steps: data quality, deduplication, statuses, message templates, dry-run mode, and control over repeated contact.
Tech
Python, lead search and storage, profile and region configuration, filtering, deduplication, contact statuses, message templates, variables in message content, dry-run mode, manual approval before sending, protection against repeated outreach to marked companies, and room to grow with SQLite, a web panel, CRM/API integrations, and an audit log.
AI content creator
Problem
For expert articles and editorial materials, generating text alone is not enough. The source, claim verification, and the final human decision still matter.
Result
An editorial pipeline moves the material from sources to publication candidate, with Polish screening, risk control, and final human approval.
Tech
Python, CLI, staged pipeline: ingest, process, cross-check, verify-sources, source-report, analyzer, reanalyze, review approve/reject, final prepare, final draft, final candidate, final accept. SQLite source_checks, Markdown with front matter, publication statuses, RSS ingest, Polish screening after retrieval, final candidate workflow, editorial card and claim ledger, no auto-publishing, local Git repo, validation through py_compile and CLI command tests.
Contact
Do you have a process that takes too much time?
Describe what is still manual: what has to be copied, checked, generated, sent, or cleaned up. We will check whether it can be automated in a sensible way.
Write to me