Technology
Technology
Tools at the service of business. We choose stack for reliability, maintainability and clarity. If a technology doesn't add value, it's not included.
Who it's for
Typical situations
- "I need to know what stack to use for my project."
- "I want to understand which technologies really add value."
- "I'm offered new technologies but don't know if I need them."
- "I need a maintainable and scalable stack."
- "I want proven tools, not experimental ones."
- "I need technical clarity without fluff."
What you get
- Proven stack: reliable and maintainable tools.
- Technical clarity: why we choose each technology.
- Practical approach: tools that solve real problems.
- No fluff: we don't add technology for the sake of it.
- Solid foundation: scalable and maintainable stack.
Stack technological
1
Backend & APIs
Django (Python) for robust APIs, business logic and data management. PostgreSQL/MySQL for relational databases. FastAPI for lightweight APIs when applicable. Celery/RQ for asynchronous tasks. Proven, maintainable and scalable stack.
Stack: Django, FastAPI, PostgreSQL, MySQL, Celery, RQ
2
Frontend & Web
Next.js (React) for speed, technical SEO and user experience. Tailwind CSS for consistent design. TypeScript when it adds clarity. Modern, fast and optimized stack for production.
Stack: Next.js, React, Tailwind CSS, TypeScript
3
Data & Analytics
Python (Pandas, NumPy) for data analysis and transformation. SQL for complex queries and modeling. Scikit-learn for models when they add value. Jupyter for exploration. Lightweight pipelines, validations and KPI definition.
Stack: Python, Pandas, SQL, Scikit-learn, Jupyter
4
Scraping & Extraction
Requests for APIs and HTTP. Scrapy for large projects. Playwright/Selenium for complex JavaScript websites. Anti-blocking, proxy rotation and browser simulation. Normalization, deduplication and change control.
Stack: Requests, Scrapy, Playwright, Selenium
5
Dashboards & Visualization
Metabase and Superset for autonomous dashboards. Plotly for interactive visualizations. Internal APIs for integration. Panels that read fast: hierarchy, context and actions. Less "pretty screens", more decision.
Stack: Metabase, Superset, Plotly, Internal APIs
6
Automation & Flows
Python for scripts and automations. Zapier/Make for quick integrations when applicable. Django/Flask for internal APIs. Queue systems for scheduled tasks. Validations, logs, traceability and automatic alerts.
Stack: Python, Zapier, Make, Django, Flask, Celery
Stack ≠ value. Value = working system
If you want, we talk about it with context and I tell you what technology I would use and why. No fluff, just tools that solve real problems.
TO PROBLEMS,SOLUTIONS.
No endless meetings. No wasting time. No fluff.
You tell me the problem and we solve it. Direct, clear and working.