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Python Development From Application Layer to AI Pipeline

We build and modernize Python applications across web frameworks, AI pipelines, and data services so one team covers your full stack.
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Trusted and top rated tech team

When Python does three jobs, but your team knows only one.

Your team writes Python for web applications. But the language now powers your AI pipelines, your data infrastructure, and your async services too. Django still serves your product, but LangChain orchestrates your LLM calls, FastAPI handles your internal APIs, and Celery runs your background jobs. Most teams are strong in one of these areas and patching the rest together. Curotec engineers work across all of them.

Our capabilities include:

Who we support

We build and modernize Python applications for teams running web platforms, AI features, and data infrastructure where the language touches every layer of the stack.

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SaaS Teams Bridging Their App and AI Stack

Your Django or FastAPI application runs your product but your AI features live in separate scripts and notebooks. You need engineers who can connect your web application to your LLM pipelines, vector databases, and model serving with shared code, shared deployments, and shared ownership.

Companies Outgrowing Their Django App

Your Django application has grown for years and every release gets slower. Views handle business logic, tests are sparse, and there's no API layer for your mobile app or frontend. You need incremental refactoring toward service boundaries, type safety, and modern patterns without a full rewrite.

Engineering Leads Building Data Pipelines

Your team processes data from multiple sources but pipelines are fragile scripts that break silently. You need reliable ETL workflows with proper error handling, scheduling, and monitoring that your engineers can maintain and extend.

Ways to engage

We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.

Staff Augmentation

Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.

Retainer Services

Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.

Project Engagement

Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.

We'll spec out a custom engagement model for you

Invested in creating success and defining new standards

At Curotec, it is more than just the solutions we build. We value relationships between our people and our clients — that partnership is why CEOs, CTOs, and CMOs turn to Curotec.
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Replatforming a clinical decision support tool used by physicians globally

Why choose Curotec for Python development?

Python touches every layer of your stack now — web framework, AI orchestration, data processing, and async services. Most agencies specialize in one slice. Our engineers work across Django, FastAPI, LangChain, and your data infrastructure because we’ve built production applications where all of those run in the same codebase. When your AI pipeline needs to talk to your web application, we don’t hand that off to a different team.

1

Extraordinary people, exceptional outcomes

Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration. 

2

Deep technical expertise

We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.

3

Balancing innovation with practicality

We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.

4

Flexibility in our approach

We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.

How we build Python applications for production

Django & FastAPI Development

Build web applications and API services with Django for full-stack products and FastAPI for high-performance async endpoints.

LLM Pipeline Orchestration

Connect your application to AI providers using LangChain, LlamaIndex, and custom orchestration built in the same Python codebase.

Data Pipelines & ETL

Ingest, transform, and load data from multiple sources with scheduled workflows, error handling, and monitoring your team can maintain.

Async Services & Task Queues

Run background jobs, scheduled tasks, and event-driven workflows with Celery and async Python so your application stays responsive.

Modernization & Type Safety

Migrate older Python codebases to modern patterns with Pydantic validation, type hints, structured project layouts, and current tooling.

Testing & Deployment

Configure pytest suites, CI pipelines, and containerized deploys so every change is validated and shipped through the same path.

The stack behind our Python builds

Web Frameworks & API Development

Our engineers build web apps and APIs with frameworks tailored to your product’s performance, complexity, and scaling needs.

  • Django – Full-stack framework with ORM, admin interface, auth, and middleware for content-heavy applications and SaaS platforms
  • FastAPI – Async-first API framework with automatic OpenAPI docs, Pydantic validation, and native type hint support for high-throughput services
  • Django REST Framework – API toolkit that extends Django with serializers, viewsets, and authentication for building RESTful endpoints
  • Pydantic – Data validation library using Python type hints that enforces schema correctness across API inputs, configs, and model outputs
  • uvicorn – ASGI server for running FastAPI and other async frameworks with high concurrency and low-latency request handling
  • Gunicorn – WSGI server for Django deployments with worker management, process monitoring, and production-ready configuration

AI & LLM Orchestration

We connect your Python application to AI providers and orchestration frameworks that manage prompts, retrieval, and generation.

  • LangChain – Framework for chaining prompts, managing memory, and building RAG pipelines with retrieval and generation steps
  • LlamaIndex – Indexing and query framework that connects LLMs to external data sources with chunking, retrievers, and response synthesis
  • CrewAI – Multi-agent orchestration where specialized AI agents collaborate on complex tasks with role-based delegation
  • OpenAI SDK – Python client for GPT-5 and embedding models with function calling, structured output, and streaming support
  • Anthropic SDK – Python client for Claude models with long-context conversations, tool use, and message batching for production workloads
  • Instructor – Structured output extraction from LLMs with Pydantic validation for type-safe responses in production pipelines

Data Processing & Analytics

Curotec builds data pipelines and analytics infrastructure with libraries that handle ingestion, transformation, and analysis at scale.

  • Pandas – Tabular data manipulation and analysis with DataFrames for cleaning, merging, aggregating, and exporting structured datasets
  • NumPy – Numerical computing with multi-dimensional arrays, linear algebra, and statistical operations for scientific workloads
  • Apache Airflow – Workflow orchestration for scheduling, monitoring, and managing ETL pipelines with dependency-aware task execution
  • Polars – High-performance DataFrame library with lazy evaluation and multi-threaded execution for datasets that outgrow Pandas
  • SQLAlchemy – ORM and SQL toolkit for building database queries, managing connections, and mapping models across PostgreSQL, MySQL, and SQLite
  • Celery – Distributed task queue for background jobs, scheduled workflows, and async processing backed by Redis or RabbitMQ

ML Frameworks & Model Training

Our developers train, fine-tune, and deploy models using frameworks that integrate directly with the Python codebases we build and maintain.

  • PyTorch – Deep learning framework for building and training neural networks across NLP, computer vision, and custom architectures
  • TensorFlow – End-to-end ML platform with production serving, distributed training, and mobile deployment through TensorFlow Lite
  • Hugging Face Transformers – Pre-trained models for text classification, summarization, entity recognition, and embedding generation with fine-tuning
  • Scikit-Learn – Classical ML library for regression, classification, clustering, and feature engineering on structured datasets
  • XGBoost – Gradient boosting for tabular data problems including fraud detection, churn prediction, and demand forecasting
  • MLflow – Experiment tracking, model versioning, and deployment management that brings reproducibility to our ML training pipelines

Testing & Code Quality

Our engineers validate every layer with testing tools configured for Python’s type system, async behavior, and framework conventions.

  • pytest – Our default testing framework with fixtures, parametrize, and plugin support for Django, FastAPI, and async test suites
  • mypy – Static type checker that enforces type hints across the codebase, catching errors before runtime in CI pipelines
  • Ruff – Fast Python linter and formatter that replaces flake8, isort, and black with a single Rust-based tool
  • Playwright – End-to-end browser specs for validating web application flows across Django and FastAPI frontends
  • Coverage.py – Code coverage measurement that identifies untested paths and integrates with CI to enforce minimum thresholds
  • pre-commit – Git hooks that run linting, type checks, and formatting on every commit before code reaches the shared repository

Deployment & Infrastructure

Curotec deploys containerized Python applications with tools that ensure consistent builds and environments across stages.

  • Docker – Containerized builds with multi-stage Dockerfiles that produce minimal production images for any hosting environment
  • Kubernetes – Orchestrated deployments with horizontal scaling, readiness probes, and Helm charts for repeatable Python service releases
  • AWS – Deployment on EC2, ECS, Lambda, and SageMaker with CloudFront CDN, S3 static assets, and managed database integration
  • Terraform – Infrastructure-as-code provisioning for compute, networking, databases, and environment-specific configuration
  • uv – Modern Python package manager that replaces pip, venv, and pyenv with a single fast tool for dependency and version management
  • GitHub Actions – CI workflows that run tests, type checks, linting, and deployment steps on every pull request before merge

FAQs about our Python development services

Python owns the AI ecosystem. LangChain, PyTorch, Hugging Face, and every major LLM SDK are Python-first. Building AI in another language means fighting the tooling instead of using it. Our engineers build your AI pipeline and your web application in the same language and the same repo.

Django for full-stack products that need admin interfaces, ORM, auth, and templating out of the box. FastAPI for high-performance API services where async, speed, and type safety matter most. We often run both in the same architecture for different jobs.

Yes. We add type hints, Pydantic validation, modern project structure, and current tooling incrementally. Your application stays live throughout. No six-month rewrite that gambles production stability on a single deploy.

We build the orchestration layer in the same Python codebase your application runs in. LLM calls, vector search, and retrieval pipelines integrate with your existing auth, database, and deployment infrastructure instead of running as a separate system.

Every engagement includes pytest coverage, type checking with mypy, and CI integration. We configure testing as part of the development workflow, not as a separate phase. Code that ships without automated validation doesn’t ship.

We work inside your repo, follow your branching conventions, and match your team’s patterns. The goal is a codebase your engineers maintain and extend after our engagement ends, not a dependency on us to keep it running.

Ready to have a conversation?

We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.

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