Development
Python development
Python backends, data pipelines and AI services in FastAPI and Django that hold up under real traffic.
In short
We build Python backends with FastAPI and Django: APIs that wrap LLMs and agents, document and OCR pipelines, scraping and ETL jobs, and real services made from your data team's notebooks. A new service is typically designed in a week and live with monitoring and alerts by week seven.
Python for the parts where AI and data live.
Python is where AI and data engineering happen, so it's at the core of most of our AI work. We build FastAPI services that wrap models and agents, Django applications for data-heavy products, and pipelines that clean, enrich and move data where it needs to be.
We write modern, typed Python with Pydantic validation, async where it helps, tests and containerised deployments, so your AI backend is as dependable as the rest of your stack.
Typical projects include LLM and agent backends, document processing and OCR pipelines, scraping and enrichment, analytics APIs and integrations with ML models your data team already built.
Is this for you?
You'll get the most out of this if
- You need a backend for an AI agent or LLM feature
- Your data team built models in notebooks that now need to become real services
- You process documents, PDFs or images at volume
- You need reliable scraping, enrichment or ETL jobs
- You want a Django admin-backed internal tool quickly
Deliverables
What you walk away with
- 01
Python services you can deploy
FastAPI or Django services with typed models, auth, rate limiting and OpenAPI docs.
- 02
AI backends
Agent and RAG services with streaming, tool calling, evals and observability built in.
- 03
Data pipelines
Scheduled and event-driven jobs with validation, retries and clear lineage.
- 04
Containerised deployment
Docker images and infrastructure as code for AWS, GCP, Azure or your own servers.
Timeline
How the project runs
Typical timings for a first live version. We confirm yours in writing after discovery.
Week 1
Design
Architecture, data flow and the interfaces other systems will use.
Weeks 2 to 6
Build
Services and pipelines with tests, shipped to staging continuously.
Week 7
Go live
Deployment, monitoring, alerting and load testing.
Ongoing
Run
Model upgrades, performance tuning and new features.
Usual stackPython, FastAPI, Django, Pydantic, Celery, Pandas, LangGraph, LlamaIndex, PostgreSQL, Redis, Docker, AWS, GCP
Why a small studio
The person who scopes your project is the one who builds it, and the one who picks up when it breaks at 2am.
- The founder is on your project
- Hussain leads every build himself. You won't brief an account manager who briefs a developer who briefs someone else.
- Three people, the output of ten
- We build with Claude, Codex and our own agent tooling every day. A small senior team now covers what used to need a department.
- We stay after launch
- Evals before every release, a log of each AI decision, cost limits and someone on call. Month six matters more to us than demo day.
- Your repo, your cloud
- The code sits in your GitHub and runs in your AWS, GCP or Azure account from the first commit, on tools your next hire already knows.
- Projects shipped
- 115
- since 2014
- Clients served
- 53
- US, UK, EU, Middle East, APAC
- Average rating
- 5.0
- 113 of 113 rated jobs
- Years shipping software
- 18
- the founder, since 2008
Case studies
Where we've done this before
- AI platform · 2025
Venture-backed startup, New York
An AI platform where non-coders build businesses
A New York startup backs people who want to start a business but don't write code. Founders describe what they want and the platform builds it with them: the product, the site and the AI agent that talks to their customers. We lead engineering, making it hold up for thousands of founders at once.
- Founders on the platform
- 10,000+
- Founders on the platform
- Building at any time
- ~1,000
- Building at any time
- Venture-backed
- Funded
- Venture-backed
- AI agents · 2026
Our own product
Altrun: an AI assistant that turns messages into actions
Altrun watches the channels people actually use (Telegram, email, Instagram DMs and the browser) and turns what comes in into scheduled, personalised actions. It sorts, summarises, researches, drafts and schedules, and it learns to write the way its user does.
- Channels in one agent
- 4
- Channels in one agent
- Typed tools
- 5
- Typed tools
- Status, 2026
- Beta
- Status, 2026
FAQ
Questions people ask
FastAPI or Django?
FastAPI for APIs and AI services, where speed and async matter. Django when you need an admin panel, ORM-heavy features and a full web app quickly.
Can you productionise our data scientists' notebooks?
Yes. We turn notebook code into tested, versioned services and pipelines, keeping your data team's logic intact.
Do you use Python for machine learning beyond LLMs?
Yes, for classification, recommendation and computer vision tasks with scikit-learn, PyTorch and hosted models, though we'll always check whether an LLM or a simpler rule does the job first.
Keep exploring
Goes well with
- AI agentsAgents that read what comes in, decide what to do and do it, with a person in the loop where it matters.
- LLM & ChatGPT integrationGPT, Claude or Gemini inside your product, answering from your own data, with guardrails you can explain to legal.
- Node.jsAPIs, real-time systems and integrations in Node.js and TypeScript that stay fast under load.
Start here
Let's scope yours.
Send a few lines about the workflow or product. You'll hear back from Hussain within a working day with questions, a rough shape and a ballpark.