Python
Web apps, data pipelines and AI features, built in the language they all share.
Python is the language of data and AI, and a very productive one for web back ends. We build Django and FastAPI apps, automate the work your team does by hand, and put machine learning into products people use every day.

from fastapi import FastAPIfrom .models import Order, NewOrderapp = FastAPI()@app.post("/orders", status_code=201)async def create_order(body: NewOrder) -> Order: order = await Order.create(**body.model_dump()) await notify_kitchen(order) return order- 1991First released
- 500K+Open-source packages on PyPI
- 3Web frameworks we build with
- 450+Clients we’ve built for
What we build with Python
From a quick prototype to production systems that crunch data every hour of the day.
Python vs. other languages for data and AI
Why most data and AI work happens in Python, and where we take extra care.
Libraries for AI and data
PyTorch, pandas and most AI SDKs are Python-firstTime to a working prototype
Compact, readable code gets ideas running fastReadability for new developers
Easy to hand over and easy to reviewRaw execution speed
Hot paths go to NumPy, async I/O or compiled code
Key things to know about Python
Python is an open-source, general-purpose language first released in 1991. It is known for readable code, and it has a package for almost everything: web, data, science, automation and AI.
For web work we use Django when a project needs an admin panel and lots of built-in features, and FastAPI for fast, typed APIs. Both are mature and widely used.
Python is the default language for machine learning and data science, so it’s the natural choice when your product needs AI features, forecasting or heavy data processing next to a normal web app.
- Spotify
- Netflix
- Dropbox
- YouTube
- Spotify
- Netflix
- Dropbox
- YouTube
- Spotify
- Netflix
- Dropbox
- YouTube
How a Python project runs
Four stages. For AI and data work, we check the data before promising results.
- 01
Define the goal
What should the software do, and how will we know it works? For data projects, we look at the data you have first.
- 02
Prototype
A small working version, often in a couple of weeks, to test the riskiest idea before building everything else.
- 03
Build in sprints
Two-week sprints, tests on every change, and a staging environment you can try whenever you like.
- 04
Deploy and improve
Production release with monitoring. For ML features, we track accuracy after launch and retrain when needed.
Our Python tech stack
The frameworks and libraries we reach for on most Python projects.
- WebPython · Django · FastAPI · Flask
- Data & AIpandas · NumPy · PyTorch · scikit-learn
- DatabasePostgreSQL · Redis · MongoDB
- Testing & jobspytest · Celery · Jupyter
- DevOpsDocker · Kubernetes · AWS
- Python
- Django
- FastAPI
- Flask
- pandas
- NumPy
- PyTorch
- scikit-learn
- PostgreSQL
- Redis
- MongoDB
- pytest
- Celery
- Jupyter
- Docker
- Kubernetes
- AWS
We’ve built software for your industry
Generic software rarely fits complex industries. We take time to understand the regulatory environment, user behavior, and operational realities of your space before writing a single line of code.
- Agriculture
- Fintech
- Healthcare
- Education
- eCommerce
- Hospitality
- Entertainment
- Government
- Real Estate
- Business
- Logistics
- Tech & IT
- Non-Profit
- Automotive
- Travel & Tourism
Working with Zentury has been a game-changer for our business. Their AI solutions have revolutionized our operations, enabling us to automate repetitive tasks and make data-driven decisions with ease. We couldn’t be happier with the results.
Partnering with Zentury has transformed our business. Their AI solutions have streamlined our operations by automating routine tasks and empowering us to make smarter, data-driven decisions. The results have exceeded our expectations.
Python questions
What is Python used for?
Web back ends, APIs, data processing, automation, and above all machine learning and AI. Instagram’s back end, Spotify’s data systems and most modern AI tools are built with Python.
Django or FastAPI?
Django for full web apps that need accounts, an admin panel and lots of built-in features. FastAPI for fast, typed APIs and AI services. Many projects use both.
Can you add AI to our existing product?
Yes. We connect your app to models like OpenAI’s or open-source ones, or train our own on your data, and build the feature around it, whether that’s search, summaries, recommendations or forecasts.
Is Python fast enough for production?
Yes, for almost all web and data work. The heavy maths runs in optimised libraries written in C, and we use async code and caching to keep APIs quick.
How long does a Python project take?
An automation or prototype can take 2–4 weeks. A full web app or AI feature typically takes 8–16 weeks. You get a timeline after a short discovery call.
Let’s build
Let’s Build Something That Works
Have an idea you’re ready to move on? A problem your current technology isn’t solving? Our team is based in Austin, Texas, and works with businesses all over the world. Reach out — the first conversation is free, and you’ll leave with clarity, not a sales pitch.
- 5900 Balcones Drive STE 100, Austin, Texas 78731


















