Technology
Python Development Services
For backend logic, data processing and automation where Python really is the better tool.
Tell us what the backend needs to doWhat this is
Python sits next to Node.js in our backend toolkit, and the workload decides which one we use, not habit. Python is strong at data processing and scripting, and it has the deepest ecosystem for AI and automation work. That covers document extraction, data pipelines, and backend services where those libraries count for more than sharing a language with the frontend.
Where Python is a good fit
Data processing and reporting pipelines that pull together or reshape data from several sources
AI and automation workflows such as document extraction, classification and calls to language model APIs
Backend APIs on FastAPI, where Python's libraries are the deciding factor
Scripts and internal tooling for data cleanup, migrations or one-off automation jobs
Where it’s probably not
A backend that has to share code or types closely with a React/Next.js frontend. Node.js keeps that in one language and is usually the better default
High-concurrency, I/O-heavy services like live chat or real-time status updates, where Node's event loop tends to fit better
Projects where the client's team can only maintain JavaScript. Matching their stack can matter more than a technical edge
What we build with Python
Backend APIs
FastAPI services, chosen when Python's data and ML libraries are part of the reason to use it.
Data pipelines & reporting
Automated collection, cleaning and reshaping of data from several sources into a report people can use.
AI & automation workflows
Document extraction, classification and workflow automation built on language model APIs, with a human review step wherever accuracy matters.
Scripting & internal tooling
One-off and recurring scripts for migrations, cleanup or scheduled internal jobs.
Common questions
Do you use Python or Node.js for backend work?
Depends on the job. Node.js is the default when there's a React or Next.js frontend and the work is mostly APIs and integrations. Python comes in for data processing, reporting pipelines and AI-related work, where its ecosystem tips the balance. We'll tell you straight which one suits your project.
Can Python handle a production business API?
Yes, especially with FastAPI, which is quick and well suited to typed, documented APIs. We use it when Python's wider ecosystem, meaning the data libraries and ML integrations, is relevant to the project.
Do you build AI features with Python?
Often. Document processing and data extraction lean heavily on Python's libraries. Picking the language is a separate decision from picking the AI model or provider, and we scope that per task.
Ready to talk about your project?
Tell us what you’re trying to build. We’ll reply within one business day with honest thoughts — not a sales pitch.
Tell us what the backend needs to do