SaaS analytics startup
A small analytics team needed a FastAPI service handling asynchronous report generation moved off a single VPS onto a properly containerised deployment with a Postgres replica for read-heavy queries.
Django & Python Development
Programming Services
Django & Python development means APIs, data pipelines and AI-adjacent services built in Django, FastAPI or Flask, and deployed on VPS or GPU infrastructure we operate. We handle the deployment, the PostgreSQL and Redis setup around it, and the ongoing patching, so your team can stay focused on the application logic.
- Django, FastAPI and Flask, deployed and operated by us
- VPS and GPU plans for data and AI-adjacent workloads
- Async migrations and dependency upgrades included
- VPS 1–8h/month; GPU servers 10h/monthIncluded hours
- EUR; applicable taxes itemised on the invoiceBilling
- English-language supportSupport
01
What we build
We build REST and async APIs in Django or FastAPI, background job pipelines with Celery or arq, and lighter internal tools in Flask where a full framework is overkill. Where the application touches embeddings or retrieval, we wire it into ChromaDB or Qdrant on the same infrastructure, so search and inference stay close to the data instead of crossing a public network. Deployment goes through Docker images we build and version, not a manual script run by hand each time.
- REST and async APIs in Django or FastAPI
- Background jobs and scheduled tasks with Celery or arq
- RAG and embeddings services wired to ChromaDB or Qdrant
- PostgreSQL and Redis configured alongside the application
02
Where it runs
Python services run on VPS plans with Docker, giving you root access and a repeatable deployment pipeline rather than a shared PaaS with opaque limits. Workloads that train or serve models move to GPU servers built on NVIDIA RTX PRO 4000 or RTX PRO 6000 hardware, alongside the rest of your stack, so data does not need to leave your own infrastructure to reach an inference endpoint.
03
Compliance and data protection
Teams building SaaS or data products on Django or FastAPI generally need to demonstrate GDPR compliance to enterprise customers and to their own compliance function, which is why a clear data processing agreement matters. We provide a data processing agreement under Article 28 and standard contractual clauses on request for procurement reviews. Invoicing runs in EUR with applicable taxes itemised on the invoice.
04
How the included hours get used
Django and Python clients typically spend their monthly hours on async migrations from a synchronous codebase, dependency upgrades ahead of a Python end-of-life date, packaging and containerisation of a project that started as a local script, and deployment of a new service once it's ready. You request the work from the client panel, propose a deadline, and hours that go past the monthly quota are accepted and billed separately, without blocking the work.
How we work
Request from the panel
You raise a request under Programming Services describing the Django, FastAPI or Flask work and a deadline that fits your roadmap.
Scope and timeline
We confirm the framework and infrastructure decisions, estimate the hours against your monthly quota, and flag anything outside it upfront.
Delivery
We build or migrate the service, run it against a staging copy of your data where possible, and deploy once you approve the result.
Handover
You get the repository, the Docker configuration and a short document covering environment variables, migrations and how to roll back.
Use cases
Legal-tech firm
A document-review product needed a RAG pipeline built in Python against Qdrant, running on a GPU server, so that client documents stayed inside a controlled environment during embedding and search.
Public sector supplier
A Django back-office serving several public bodies needed its dependency chain upgraded ahead of an unsupported Python version, with the migration scheduled around a procurement deadline.
Technology stack
- Python 3.12
- Django
- FastAPI
- Flask
- PostgreSQL
- Redis
- Celery
- Docker
- ChromaDB
Every subscription includes monthly DevOps, CyberSecurity and Programming hours: 1 h from the cPanel Advanced plan up, 1–8 h on VPS, 5–10 h on dedicated servers depending on the plan, and 10 h on GPU servers. Hours are requested from your client panel, don't roll over to the next month, and anything above the quota is accepted and billed separately.
Frequently asked questions
Django or FastAPI — which should we use?
Django suits applications that need an admin panel, an ORM and authentication out of the box, such as most back-office and SaaS products. FastAPI fits leaner, async-first APIs and services that sit in front of a data pipeline or a model. We can advise once we know the shape of the workload.
Can you deploy Django with PostgreSQL and Redis on a VPS?
Yes, that's our default setup: Django behind Gunicorn or Uvicorn, PostgreSQL for the primary database, Redis for caching and session storage, all in Docker containers on a VPS, with the deployment scripted rather than done by hand each time.
Do you support GPU hosting for Python AI workloads?
Yes, on NVIDIA RTX PRO 4000 and RTX PRO 6000 servers. GPU plans include 10 included hours a month, which typically cover model deployment, inference-endpoint setup and pipeline tuning.
Can Python run on shared cPanel hosting?
Not comfortably for Django, FastAPI or anything running background workers. Python applications need process control and root access that shared hosting doesn't give you, so we deploy them on VPS or GPU plans with Docker instead.
What does an async migration involve?
We identify the blocking calls in your existing Django or Flask code, move the relevant views or tasks to async equivalents (or to FastAPI where that's the better fit), and test the migration against real request patterns before switching production over.
Talk to us about your Django or Python project
Tell us what's running and what needs building. We'll scope it against your plan's included hours and give you a realistic delivery date.