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Tag: Fintech | Financial logging | Solo founders | Tax-aware reporting
Every quarter, we used to spend a lot of time moving expenses from quick notes into a spreadsheet, checking figures, and filing our VAT return with the tax authority. Once we missed a deadline; the notice arrived before we had fully registered that the quarter had closed.
We built Balanzer because we needed it ourselves.
Balanzer is a financial logger for solo founders. Capture income and expenses as they happen—much like jotting in a notes app—so monthly and quarterly summaries are there when you need them, with less repetitive consolidation before each filing period.
For founders operating in the Netherlands, Balanzer includes VAT quarter deadlines, email reminders ahead of those dates, and reports that separate net amounts, VAT, and gross totals in a way that aligns with online tax filing.
We are solo founders who built Balanzer for our own rhythm first—a place to log as we go so month-ends and filing seasons feel less frantic. Some of us pair it with an accountant; others keep the books end to end. Either way, we hope it gives you the same thing we wanted: a clear, friendly trail from everyday entries to the moment you need the numbers.
Log today. Report when it matters.
Tag: Community | Expat & diaspora orientation | Q&A
Our story. AskLucy began as a vision — a dream, really — that we carried since 2016: a place where people landing somewhere new could find honest, practical orientation without having to stumble through every dead end first. A decade later, in 2026, we finally brought it to life. Ten years from first spark to launch: for us, that is a dream come true.
Fifty Lemons is the tagline we use on AskLucy — it stands for the practical lessons we wish we’d had when we were new in a country and figuring things out from scratch.
When we arrived, simple things often took longer than they needed to: where to register, how housing really works, what childcare and schools expect, when insurance kicks in, or even that free help exists for taxes and paperwork if you know where to look. Much of that only clicked after a friend, colleague, or chance conversation pointed us in the right direction. Friends in other places — Belgium, for example — describe the same maze of forms and deadlines, just with different offices and URLs.
AskLucy is our way of paying that forward: curated questions and answers (published as Lucy), with links to official and reputable sources so you can verify. We started with a small, concrete set of reference links as an MVP; the product is not tied to one country, and we hope contributors will add orientation for more places over time. It is orientation, not legal, tax, or immigration advice — always double-check official sites for where you live.
Tag: Science & AI | Community | Knowledge Digest
At kofiyatech, we have deep respect for the universities and research teams that advance science — and we want their stories easier to follow in everyday language, for the curious, the professional, and the dreamer alike.
Jefouree is our contribution to the community. Each week, we hand-pick the most fascinating breakthroughs in science, AI, health, and data — and bring them to you in plain, human language. No jargon. No overwhelm. Just the discoveries that matter, told the way a brilliant friend would tell them over coffee.
Named after the traditional road in the Gurage community in Ethiopia that connects households and serves as a hub for shared life, Jefouree is your weekly path to staying connected to the world of knowledge — quietly, warmly, and at your own pace.
Tag: Fintech | Financial Services | Exchange Rates
We are excited to announce that SendGursha is now live!
What is SendGursha?
SendGursha is a web application designed to help diaspora abroad send money smarter. It provides real-time exchange rate comparisons across multiple providers, helping users make informed decisions when sending money to Ethiopia and other destinations.
Key Features
- Real-time Exchange Rates: View today's exchange rates from multiple providers
- Historical Data: Logged-in users can access historical rates to track trends over time
- Provider Comparison: Compare rates, fees, and transfer costs across different providers
- Calculator Tool: Calculate the effective amount received when sending money, including transfer fees
- Mobile App Links: Direct links to provider mobile applications for easy access
Try It Now
Visit SendGursha to compare exchange rates and find the best options for sending money: SendGursha
Log in to access historical rates and track exchange rate trends over time. New users can register to unlock additional features.
Tag: DHS AI/ML Toolkit
Try Storyteller on PyPI
We are excited to announce that STORYTELLER is now available for testing on PyPI!
STORYTELLER is a Python package that makes it easier to explore and work with Demographic and Health Survey (DHS) datasets. It provides simple commands for launching a web-based data explorer, running predefined queries, and exporting cleaned datasets for further analysis.
What You Can Do
- Start an interactive Datasette web app to browse DHS databases.
- Run predefined queries and export datasets in ready-to-use formats.
- Enable full-text search (FTS) on DHS variable tables.
- Export cleaned data to CSV and reproducible metadata to JSON.
How to Install
pip install storyteller-dhs
Learn More
Check out the project on PyPI: https://pypi.org/project/storyteller-dhs/
Curious about how we are using DHS data with AI/ML? Visit our DHS AI/ML Toolkit.
We are still in the early stages of this project, and your feedback will be invaluable. Please try it out and let us know your experience!
Tag: DHS AI/ML Toolkit | Database conversion | Open Source | Contribute | Python
We are excited to announce the release of our new project: DHS-To-Database-dhs2CSVTables-simplified! This open-source tool is designed to simplify the conversion of raw Demographic and Health Surveys (DHS) data into a format suitable for database storage in CSVTables format.
What is DHS-To-Database-dhs2CSVTables-simplified?
Our project serves as a convenient wrapper around the existing DHS-To-Database tool developed by Harry Gibson. While the original tool is powerful, we recognized the need for a more accessible and user-friendly way to handle DHS data conversions.
Key Features
- User-Friendly Wrapper: Provides an easy-to-use interface for converting raw DHS data.
- Supports Python 3.8 and Above: Ensure compatibility with modern Python environments.
- Simplified Usage: Designed for seamless interaction with raw DHS data.
- CSV to SQLite Conversion (New in v0.2.0): Now supports converting relational CSV tables to a SQLite database using the
csvs-to-sqlitecommand-line tool.
For detailed documentation and to get started, please visit our GitHub repository: DHS-To-Database-dhs2CSVTables-simplified.
A special thanks to Harry Gibson for his foundational work on the DHS-To-Database tool.
Tag: WebApp Framework
We are thrilled to announce the official launch of NIGATWA1087, a powerful web application boilerplate framework designed to accelerate your development journey.
NIGATWA1087 empowers you to:
- Hit the ground running: Skip repetitive setup tasks with a comprehensive boilerplate structure, ready to customize
- Build with confidence: Leverage the time-tested foundation used in our own projects like kofiyatechapps
- Build a robust dashboard like FLOWER: Leverage NIGATWA1087's foundation to create complex and data-rich dashboards like FLOWER
- Focus on what matters: Streamline user management with built-in user authentication, registration, and secure password recovery
- Empower your users: Equip administrators with tools to support and manage your webapp effectively
- Handle the unexpected: Ensure a seamless user experience with error handling for incorrect URLs
- Deploy where you need: Choose between AWS cloud deployment with Amazon RDS database or local development environment with either SQLite or PostgreSQL database
Tag: DHS AI/ML Toolkit | Algorithm
Building on the success of KILIMA TULIP AI, we are excited to introduce our latest initiative. This project, rooted in Explainable AI (XAI), focuses on child survival risk analysis using Bayesian statistics. By employing transparent and interpretable Bayesian methods, we aim to provide not just insights but a clear understanding of the factors influencing child survival.
For those eager to explore the CIAO BAYESIAN results and insights, you can access them conveniently through our user-friendly FLOWER Dashboard.
Stay tuned as we embark on this journey at the intersection of data-driven discovery and transparent AI solutions.
Tag: DHS AI/ML Toolkit | Dashboard
Welcome to the FLOWER Dashboard, your gateway to exploring child survival risk insights powered by the KILIMA TULIP AI model. With the FLOWER Dashboard, you can customize your analysis by selecting a specific country, feature group, and risk factor.
Our AI-driven predictions provide valuable insights into child survival risk. These insights empower you to allocate resources effectively, develop targeted interventions, and contribute to research efforts.
Get started today by visiting the FLOWER Dashboard and making data-driven decisions to improve child well-being.
Tag: DHS AI/ML Toolkit | Deep Learning | Africa
Welcome to KILIMA TULIP AI, a project dedicated to predicting under-five (U5) child survival risk in Africa using Deep Learning AI techniques. This project builds upon the success of our previous DEEP MINTILO AI project, where we achieved a remarkable above 90% accuracy in predicting child survival risk for under-five children in Ethiopia.
With KILIMA TULIP AI, we have achieved an even more remarkable performance of 95% accuracy in predicting child survival outcomes across five African countries: Ethiopia, Ghana, Uganda, South Africa, and Zimbabwe.
Our team at kofiyatech is thrilled to present this groundbreaking technology. Join us in our mission to make a positive impact on the well-being of under-five children.
Tag: DHS AI/ML Toolkit | Deep Learning | Ethiopia
Welcome to DEEP MINTILO AI, a project dedicated to predicting under-five (U5) child survival risk in Ethiopia using Deep Learning AI techniques. This project is an extension of our MINTILO AI initiative and aims to leverage the power of neural networks to improve child survival rates.
With DEEP MINTILO AI, we have achieved remarkable performance gains, surpassing 90% accuracy in predicting child survival outcomes.
Our team at kofiyatech is excited to offer you a demo of this cutting-edge technology. Reach out to us to learn more about the implementation and the potential impact on child well-being.
Tag: DHS AI/ML Toolkit | Algorithm | Contribute | Open Source | Python
An open source project dedicated to utilizing Python and machine learning techniques to provide insights for policy makers in eradicating child mortality. By analyzing data from DHS surveys, MINTILO AI identifies risk factors associated with child survival.
This project relies on the DHS AI WebApp platform as its data source. To access and contribute to MINTILO AI, visit the GitHub repository: GitHub - MINTILO AI.
For more information and to contribute, please feel free to reach out to us.
Tag: DHS AI/ML Toolkit | Algorithm | Contribute | Open Source | R
An open source project that utilizes classical survival analysis methods in R, including Kaplan-Meier and Cox regression techniques. Its primary objective is to enable researchers and graduate students to collaborate and identify risk factors related to child survival in children under-five years old.
This project relies on the DHS AI WebApp platform as its input source. You can access the project on GitHub: GitHub - WATOTO SURVIVAL.
For more information and to contribute, please feel free to contact us.
Tag: DHS AI/ML Toolkit | WebApp | AI Initiative for Public Health and Tropical Medicine
The DHS AI WebApp is a user-friendly, SQLite-based database repository specifically designed for DHS survey data. It serves as a powerful resource for Data Science projects, providing researchers, data analysts, and graduate students with easy-to-use querying capabilities tailored to their specific research subjects.
Our project initiative aims to promote the use of data science and machine learning techniques with DHS survey data. It was inspired by a study published by Bitew, et al (2020) that highlighted the untapped potential of utilizing these methods.
We are committed to supporting researchers interested in machine learning and data science. Through our project, we provide valuable resources, guidance, and assistance to help researchers explore the vast opportunities offered by DHS survey data.