Python Development Services
Python is our default backend language for anything AI-adjacent — data pipelines, ML models, and APIs that need to talk to LLMs — because the ecosystem is built for it. We build backend systems, APIs and data pipelines in Django and FastAPI, with a natural path to adding AI features since our AI team works in the same language.
The right default for AI-adjacent backends
Python isn't the fastest language at runtime, but it has the deepest ecosystem for data processing, machine learning, and LLM tooling (LangChain, Pandas, scikit-learn) of any mainstream language. For backends that need to eventually call an LLM, run a prediction model, or process large datasets, building in Python from day one avoids a painful rewrite later.
Django
Batteries-included framework for content-heavy or admin-heavy applications, built fast with less boilerplate.
FastAPI
High-performance async APIs, ideal for AI-integrated backends and services needing low latency.
Data pipelines
ETL jobs, scheduled processing, and data transformation using Pandas and standard Python tooling.
How we build in Python
Framework fit
Choose Django or FastAPI based on whether you need an admin panel and ORM-heavy CRUD, or a lean async API.
Architecture & data model
Design the database schema and service boundaries before writing business logic.
Build & test
Development with test coverage on core business logic, not just a demo that works once.
Deploy & monitor
Containerized deployment with logging and monitoring from day one.
What we build in Python
Backend APIs & admin systems
Django-based systems with a built-in admin panel for content and data management.
EnterpriseAI-integrated backends
FastAPI services that call LLMs, run ML models, or power RAG pipelines with low latency.
SaaSData processing & analytics
Scheduled ETL jobs and data pipelines feeding dashboards or downstream ML models.
RetailFMCGTools we build with
Why build in Python
Direct path to adding AI features later, since our AI team works in the same ecosystem.
Django's admin panel saves significant build time on internal tools and content management.
FastAPI's async support handles high-concurrency workloads without a framework rewrite.
The largest available ecosystem for data processing and ML libraries.
Frequently asked questions
Django vs FastAPI — which should I choose?
Can Python be used for AI applications?
Can you modernize an existing Python application?
How much does Python development cost?
How long does Python development take?
Is Python fast enough for production workloads?
Explore related Development services
Need a Python backend that's ready for AI?
Tell us what you're building — we'll recommend Django or FastAPI based on the real requirements.
Start Your Project