Python development for
backends, data pipelines & automation.
Python is our choice for backend-heavy applications, data processing, and automation systems. Django for full-featured SaaS, FastAPI for high-performance APIs, Celery for task queues.
Python for the backend problems that need real engineering
Python's versatility and library ecosystem make it ideal for backend-heavy applications, especially those with data processing, automation, or AI integration requirements.
Django & FastAPI Applications
Django for full-featured web applications, auth, admin, ORM, forms. FastAPI for high-performance API services where speed and automatic OpenAPI docs matter.
Data Processing & ETL
Pipelines that extract, transform, and load data from multiple sources. Scheduled batch jobs, event-driven processing, and reporting infrastructure at scale.
Automation & Task Queues
Process automation with Celery and Redis, document processing, API integrations, report generation, and complex workflow orchestration that runs reliably in the background.
AI Integration Backends
Python is the native language of the AI ecosystem. We build backends that integrate with OpenAI, Anthropic, and open-source LLMs, wrapping AI capabilities into production-ready APIs.
The right tool for data-heavy and integration-first projects
Python isn't always the fastest runtime, but for backend applications where developer velocity, data handling, and AI integration matter, it's hard to beat.
Readable, maintainable code
Python enforces readability. Code one developer writes, another can understand without significant ramp-up. For applications with long maintenance tails, that pays off continuously.
Library ecosystem built for data
NumPy, Pandas, Celery, SQLAlchemy, Pydantic, Boto3, Python has mature libraries for almost every problem category. We pick the right ones and don't build what already exists.
Native AI/ML ecosystem
OpenAI, LangChain, Hugging Face, LlamaIndex, all Python-first. For projects with AI integration requirements, Python removes a significant translation layer.
Strong for integration work
Most enterprise systems have Python SDKs. For projects primarily connecting existing systems, Python is often faster to deliver than alternatives.
When should you choose Python?
Python isn't always the fastest runtime, so here's the honest tradeoff we walk clients through.
Python makes sense when
- Your project involves data processing, ETL, or CPU-bound work
- You need AI/LLM integration, the ecosystem is Python-first
- You want a mature, batteries-included framework like Django for a SaaS build
Consider alternatives when
- Your app is I/O-bound with many concurrent requests, Node.js has an edge there
- You need a lightweight, high-performance API service, FastAPI vs Django is its own tradeoff to weigh
- Your team already has deep expertise in another backend stack
Hire a Python Developer
Skip the full build. Get a vetted Python developer working inside your existing team, on your stand-ups and your roadmap.
Hire a Python Developer →Built by AI-native engineers, so your Python backend is ready for agents and LLM features
We design the API surface, auth, and event model so language-model features and AI agents can consume your Python backend safely later, rather than bolting them on after. It is how our own products, Tully AI and Mebag, were built.
Typed schemas, scoped tokens, and predictable errors so an AI agent can call your Python API without surprises.
Retrieval endpoints and event streams that feed a vector store without a nightly export job.
A managed Python layer in front of OpenAI, Anthropic, or Gemini with rate limits, caching, and fallbacks.
Shipped with prompt versioning, evals, and guardrails. See how we build AI →
Common questions about Python development
Straight answers on stack fit, working in your codebase, cost, and how we start.
Django or FastAPI, which do you use?
Depends on what you're building. Django for full-featured applications where you want batteries included, auth, admin panel, ORM, forms. FastAPI for high-performance API services or microservices where speed and automatic OpenAPI documentation matter. We'll recommend the right one.
Can you build a SaaS product with Python?
Yes. Django is a mature, proven framework for SaaS products, auth, admin, ORM, and forms built in, with Stripe billing, team management, and role-based access layered on top. It's a solid choice, especially for founders and teams with Python expertise.
Do you build data pipelines and ETL systems?
Yes, Pandas for transformation, Celery for task queuing, PostgreSQL or cloud data warehouses for storage. We build data processing infrastructure, not ML model development.
How does Python performance compare to Node.js?
For I/O-bound work (handling many concurrent HTTP requests), Node.js has an edge. For CPU-bound work (data processing, complex calculations), Python performs well with proper architecture. For most SaaS and API applications, the performance difference is not the deciding factor, project fit and team expertise matter more.
Hire Python Developers
Need Python engineers embedded in your team rather than a full project handoff? Our Python Developers join your existing workflow (your tools, your stand-ups, your roadmap) while we handle employment, payroll, and HR. Add one developer or a full team, scale up before a release and back down after, and keep everything they build.
Need a Python development team?
Django, FastAPI, data pipelines.
Tell us what you're building. We'll give you a straight answer on whether Python is the right tool and what it'll take to ship it.