Python,
Django to ML.
Django, FastAPI, Celery, Pydantic — and pytorch/transformers for the AI side. Senior Python engineers, comfortable in monoliths and microservices, scientific stack fluent.
Python
engineering services.
Django, FastAPI, Celery, Pydantic — and pytorch/transformers for the AI side. Senior Python engineers, comfortable in monoliths and microservices, scientific stack fluent.
Django apps
Django 5, DRF, htmx — full-stack Python at scale, Postgres-backed, async where it pays.
FastAPI services
FastAPI + Pydantic — typed, async-native APIs that auto-document themselves.
AI & ML services
PyTorch, transformers, LangChain, LlamaIndex — Python is the language AI lives in, we ship it in production.
Data engineering
Airflow, Prefect, dbt — pipelines that survive contact with real data.
Background processing
Celery, RQ, Dramatiq — workers that retry properly, schedule properly, observe properly.
Scientific computing
NumPy / SciPy / Pandas at scale, Numba and Cython when raw Python isn't enough.
How we build
production Python services.
Same engineers from kickoff to handover. Weekly demos. No staff augmentation, no offshore rotation.
Consultation
Transparency from the start. We discuss the plan, build a precise deployment roadmap, and at each stage encourage you to participate.
UI / UX design
A talented design team creates an accurate user-journey map. User-friendly interfaces built on extensive research — Material 3 done right.
Reliable engineering
A decade of backend, data and ML engineering. Python services and pipelines built for production from day one.
Six steps to ship
a Python service.
From a fuzzy idea to a Play Store-live product, with a checkpoint at every stage.
User research
1 – 2 weeksUser Research Mastery — define user roles, set expectations, conduct up to 10 impactful interviews. Insights become a guaranteed roadmap.
Product scope
1 weekCompelling user stories crafted with stakeholders. Clarity, collaboration and adaptability converge to transform vision into software.
Design
2 – 3 weeksRobust UI designs for visual appeal or efficient UX prototypes for real user insights. Transform your vision into a user-centric reality.
Development
6 – 14 weeksAgile development transforms the process into a dynamic, customer-driven journey. Iterative approach, rapid sprints, change embraced seamlessly.
QA
1 – 2 weeksRigorous testing in staging. Each step a precision move toward a seamless user experience. QA engineers act as continuous guardians.
Deployment
1 weekPlanning, version control, testing, cutting-edge strategies like canary releases. Trouble-free installations with continuous monitoring.
The actual
Python stack.
What goes into a Magora Python service — FastAPI or Django, typed all the way down, evals and tests as a first-class citizen.
- Python 3.12
- SQL
- TypeScript (clients)
- C (extensions)
- FastAPI
- Django REST
- Flask
- LangChain
- Clean Architecture
- DDD
- CQRS
- Event-driven
- Dependency Injector
- Lagom
- FastAPI Depends
- Constructor injection
- asyncio
- Celery
- Redis Queue
- Dramatiq
- PostgreSQL · SQLAlchemy
- Alembic
- Redis
- S3 · Parquet
- OAuth2
- FastAPI Users
- Django Auth
- JWT
- PyTorch · Transformers
- Pandas · NumPy
- pgvector
- pytest · Hypothesis
What clients
say.
Pulled from independently-verified Clutch reviews — 60+ of them, 4.9 average.
FastAPI service with proper async + Pydantic. We can run it on a Raspberry Pi if we have to.
Django models drove the data architecture. Two years on, we still haven't fought the framework.
LangChain + custom retrievers + evals in CI — production LLM code, not a Jupyter demo.
Python services
we've shipped.
Four from the wider portfolio — Python services powering ML pipelines, APIs and data products today.
Empath AI
FastAPI backend for RAG clinician copilot — Python, pgvector, evals.
See case study → Enterprise · PythonKMA 9x9 AI
AI classification engine — Python ML pipelines for enterprise workflows.
See case study → MedTech · PythonFocalyx
ML-driven prostate cancer platform — Python model training and serving.
See case study → Maritime · DataVessel Performance Solutions
Web app + data pipelines for vessel performance — Python ETL.
See case study →The honest
questions.
Magora is a London-based software development company that provides mobile, web and AI product development, and helps businesses ship bespoke solutions backed by 15 years of delivery.
Our senior Product Owners and Project Managers dive into your business goals during Discovery to create a product vision that gives end users a seamless experience.
Top-notch mobile, web and AI developers plus QA engineers deliver high-quality code at any complexity, and our UI/UX design team ensures the experience meets the strictest guidelines.
Typical day rates in London run £30–£90 per hour. Our 2026 paid pricing (GBP):
- Free working prototype + written analysis from a senior Product Owner before any paid engagement — no commitment, no charge.
- Product Discovery: from £3,000.
- Startup MVP: from £10,000.
- Full production mobile or web project: from £30,000.
- AI development, bespoke enterprise software and CRM platforms: scoped after Discovery.
We transfer full ownership of source code, designs and IP to the client on payment.
Yes. Magora has a dedicated AI & ML practice delivering LLM-powered applications, retrieval-augmented generation (RAG) pipelines, AI agents, deep learning models, fine-tuned open-source models, and integrations with OpenAI, Anthropic and Google Gemini APIs. See also our take on generative AI and Apple Intelligence on iOS.
Engagements range from short proofs of concept to multi-month production builds. All work is discovery-led, GDPR-compliant, with full ownership of code and data delivered to the client.
Magora Systems is headquartered in London, United Kingdom, at Office 4.01, 4th Floor, The Tea Building, 56 Shoreditch High Street, London E1 6JJ.
Legal entity is Thinking Fish Ltd (UK Companies House 03637036), founded in 2010. We also operate a US presence at 17001 Collins Ave, Sunny Isles Beach, FL 33160.
Finance (FinTech), healthcare and pharma, hospitality and tourism, real estate, transport and logistics, e-commerce and retail, education, automotive, construction and IT/telecom.
Past clients include AstraZeneca, Grant Thornton, Toyota, Unilever and Cisco. See full case studies.
Yes. As a UK-based developer, Magora delivers GDPR-compliant systems by default: data-minimisation review during discovery, consent flows, data-subject-access tooling, encrypted-at-rest storage, audit logging, and EU/UK data-residency options on AWS and GCP.
For AI projects Magora also runs an EU AI Act readiness review before deployment.
Yes — to stay among cutting-edge technologies and keep up with changing demand, the product needs constant maintenance. During the maintenance period we analyse all incoming inquiries, evaluate severity and: fix defects, form a Product Backlog from low-medium defects and user feedback, plan and propose enhancements that add value, update libraries and tweak based on API changes to maintain stability, and monitor the code stage for critical security updates. Same team also handles legacy software modernisation if your stack needs lifting.
IPR in bespoke software shall, without prejudice to our rights in pre-existing IPR, be transferred to you on payment of the requested amount relating to such work. Where you have provided us with third-party materials, it is solely your responsibility to ensure those materials may be used as directed without infringing any IPR, laws or regulations.
Need Python
engineers now?
30-minute call with a senior Android architect. We'll review your stack, scope and team needs — and tell you what we'd actually build if it were us.