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Redian Software
Web Development expertise

Python — for web, data and AI/ML

Python development for web and AI/ML — Django, FastAPI, PyTorch, LangChain, scikit-learn. Production Python at scale, paired with Postgres, Celery, OpenTelemetry.

Hire Python engineers See our work
CMMI Level 3 Appraised ISO Certified 200+ enterprises 5 regional hubs 9+ years of delivery
Python delivery, in numbers

Proof, not promises.

Real benchmarks from production engagements.

  • Web + Data + AI

    One language

    Django, FastAPI, PyTorch, LangChain

  • Typed

    FastAPI default

    Pydantic + mypy for type safety

  • Production ML

    Specialty

    Same engineers, model to API

  • Async

    Modern Python

    asyncio, async DB drivers

What we deliver

The capabilities our Python engineers ship.

Production patterns from real engagements — not a stack-marketing checklist.

  • 01

    Django applications

    Django 5+ with PostgreSQL, batteries-included for content, admin, auth, ORM. Django REST Framework for APIs.

  • 02

    FastAPI APIs

    Typed APIs with Pydantic models, async-by-default, OpenAPI auto-generation. Best-in-class developer experience.

  • 03

    AI/ML pipelines

    PyTorch, TensorFlow, scikit-learn, LangChain, LlamaIndex. See our [AI/ML expertise](/expertise/ai-ml) for depth.

  • 04

    Data engineering

    Airflow DAGs, dbt models, Spark jobs, Pandas pipelines, data warehouse loading into BigQuery/Snowflake.

  • 05

    Background jobs

    Celery + Redis for queue workers, Celery Beat for scheduled tasks, async background tasks in FastAPI.

  • 06

    Modernisation

    Python 2 → 3, monolith → microservices, Flask → FastAPI, sync → async migrations.

Who hires us for Python

Where this stack fits best.

We've seen the patterns — match yours against the list to find the closest fit to your situation.

  • AI/ML-heavy companies

    Companies where ML is the product or a critical infrastructure layer.

  • Data engineering teams

    Organisations needing data pipelines, ETL, warehouse loading.

  • SaaS startups

    Founders preferring Django's batteries-included approach for fast time-to-market.

  • Enterprise APIs

    Companies adopting FastAPI for typed, async API services.

  • Research teams going to production

    Research/ML teams whose prototypes need productionising.

How we engage

From brief to production.

Transparent, milestone-driven, with clear owners and timeframes at every stage.

  1. 01Week 1

    Architecture

    Framework selection (Django/FastAPI/Flask), data layer, async strategy, deployment plan.

  2. 02Weeks 2–8

    Build

    Two-week iteration cycles, working software each Friday, MLflow/observability live from week 1.

  3. 03Weeks 8–10

    Hardening

    Performance, security, mypy type-checking, pytest coverage, observability.

  4. 04Week 11

    Production

    Container deployment, hypercare, monitoring.

Python in depth

Inside our Python practice.

The long-form view of how we approach Python engagements.

Python everywhere

Python is uniquely positioned across three high-value domains: web applications, data engineering and AI/ML. We deliver Python production code across all three, with the same engineers who can switch from a Django API to a FastAPI ML serving layer to a PyTorch model training pipeline.

What we deliver

  • Web — Django for batteries-included apps, FastAPI for typed APIs, Flask where simplicity matters
  • Data engineering — Airflow, dbt, Spark, Pandas pipelines
  • AI/ML — PyTorch, TensorFlow, scikit-learn, LangChain, LlamaIndex
  • Async — asyncio, FastAPI, Celery for background jobs
  • Testing — pytest, hypothesis, factory-boy

Where Python fits best

When you need one language across the web layer, the data layer and the ML layer. Or when the team's strength is Python and the productivity payoff outweighs other considerations.

Why Redian for Python

What makes our Python practice different.

Independent reasons clients pick us over freelancers, agencies and large consultancies.

  • Typed Python

    Pydantic, mypy, dataclasses. We don't write untyped Python in 2026.

  • Web + ML unified

    Same engineers across the web layer, the data layer and the ML layer. No handoff overhead.

  • Production discipline

    MLflow, OpenTelemetry, Sentry, structured logs. ML in production has special needs we don't skip.

  • Modern Python only

    Python 3.11+, async by default, modern packaging (uv/poetry), modern tooling (ruff, mypy).

Tech & tools

The Python stack we ship on.

Production tooling — not just languages on a CV.

  • Python 3.12+
  • Django 5+
  • FastAPI
  • Flask
  • Pydantic
  • SQLAlchemy
  • Django ORM
  • Celery
  • Airflow
  • dbt
  • Spark
  • Pandas
  • NumPy
  • PyTorch
  • TensorFlow
  • scikit-learn
  • LangChain
  • LlamaIndex
  • pytest
  • mypy
  • ruff
  • uv
  • Poetry
  • PostgreSQL
  • Redis
  • MongoDB
  • Snowflake
  • BigQuery
  • MLflow
  • Docker
  • Kubernetes
Frequently asked questions

Everything you wanted to ask before the call.

Don't see your question? Ask us directly →

Django vs FastAPI — which should we pick?

Django for batteries-included web apps with admin, ORM, auth, templates. FastAPI for typed APIs, async-by-default, microservices, and when you don't need Django's web layer. Often both — Django for admin + content, FastAPI for high-throughput APIs.

Can your Python team also do AI/ML?

Yes — that's the point of having a Python practice. Same engineers across web (Django/FastAPI), data (Airflow/dbt/Pandas) and ML (PyTorch/scikit-learn/LangChain). See our [AI/ML expertise](/expertise/ai-ml) for depth.

Do you do async Python at scale?

Yes — FastAPI by default for new APIs, async SQLAlchemy / Tortoise for DB, asyncio + aiohttp for I/O-heavy services. We've shipped async Python at production scale across BFSI and AI/ML workloads.

Engage Redian

Ready to ship with Python?

Tell us the role, the seniority and the time-zone overlap you need — a senior engineer will send three pre-vetted profiles within a week.

Hire Python engineers All expertise