Python — the leading language for data and AI
Python has the largest ecosystem for data processing, machine learning and AI development. With Django and FastAPI we build scalable web APIs and backends – from simple REST services to complex data platforms with Celery, Redis and PostgreSQL.
For AI applications Python is the practical default: PyTorch, scikit-learn, LangChain and Hugging Face run natively in Python. As a Python agency from Germany we deliver backends, REST APIs, ETL pipelines and AI backends – from architecture through implementation to production on AWS, Azure or your own servers.
Python development complements our custom software development and AI solutions for business. Technology overview: Python – stack details on our technology page.
Project references
Selected case studies from our project work
Documented examples with transparent evidence types — browse matching references or open the full case study.
Our Python services
Django applications
Django is the batteries-included framework for full web apps: ORM models, built-in admin, Django REST Framework for APIs and Channels for real-time features. We deliver clean app design, custom user models, Celery for background jobs and pytest-django test suites. Deployment via Docker on AWS ECS, Kubernetes or classic VPS setups.
FastAPI backends and microservices
FastAPI is our choice for high-performance APIs: async/await, automatic OpenAPI docs, Pydantic validation and strong throughput. We build FastAPI for ML inference, LLM integrations, microservices and performance-critical components – containerised on Kubernetes with CI/CD.
ETL pipelines and data processing
Python is the standard for ETL: extract from APIs, databases, CSV/Excel or ERP, transform and load into warehouses. We use Pandas, Polars, SQLAlchemy and Airflow – alongside database & BI and automation.
AI and ML integration
Python backs AI services: LangChain and LlamaIndex for RAG, OpenAI and Anthropic API integration, FastAPI inference and vector databases (pgvector, Chroma). See AI agents and AI chatbot agency.
Django & FastAPI
Scalable web apps and high-performance APIs – Django ORM, DRF and async FastAPI.
ETL & data processing
Pandas, Polars, Airflow and SQLAlchemy – robust ETL for integration and BI.
AI & ML backends
LangChain, FastAPI inference and RAG – AI integration for production environments.
Deployment & DevOps
Docker, Kubernetes, AWS ECS and CI/CD – Python apps deployed for production.
Python in practice: from prototype to production
Moving from prototype to production starts with explicit acceptance criteria. We verify representative data, critical business paths, restart behaviour and operating ownership before users or connected systems move to the new service.
Runtime, error rate and resource consumption are measured against the agreed load profile. Thresholds and release rules remain project-specific rather than generic promises.
- Acceptance: reproduce critical business and data paths
- Operations: define alerts, restart procedures and escalation paths
- Handover: document runbooks, access and responsibilities
- Release: agree the cutover window and rollback plan
- Evidence: record results and known limitations in the acceptance report
- Measurement: capture comparable baseline and production metrics
We build Python backends that scale and stay maintainable. After a free discovery call you get a transparent fixed-price quote – or start in the project check.
Define the Python assignment and operational handover
Django applications, FastAPI backends, data pipelines and AI integrations have different operating profiles. We first clarify sources, volume, refresh timing, interfaces and owners. Use machine learning development for ML-specific delivery and data analytics for decision-focused analysis.
Handover includes source code, reproducible dependencies, tests, deployment configuration, data-flow documentation and runbooks. We present a project as Python evidence only when its Python contribution is confirmed. For language-model connections, LLM integration serves the more precise intent.
