SaaS analytics startup in Bristol
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 in the UK 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.
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.
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, in the same Frankfurt facility as the rest of your stack, so data does not need to leave the EU to reach an inference endpoint.
UK teams building SaaS or data products on Django or FastAPI generally need to demonstrate EU or UK data residency to enterprise customers and to their own compliance function, and our Frankfurt data centre satisfies that without routing traffic outside Europe. Invoicing runs in EUR with UK VAT at 20% shown as a separate line, and our GDPR data processing agreement is available on request for procurement reviews.
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.
You raise a request under Programming Services describing the Django, FastAPI or Flask work and a deadline that fits your roadmap.
We confirm the framework and infrastructure decisions, estimate the hours against your monthly quota, and flag anything outside it upfront.
We build or migrate the service, run it against a staging copy of your data where possible, and deploy once you approve the result.
You get the repository, the Docker configuration and a short document covering environment variables, migrations and how to roll back.
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.
A document-review product needed a RAG pipeline built in Python against Qdrant, running on a GPU server, so that client documents never left the EU during embedding or search.
A Django back-office serving several local authorities needed its dependency chain upgraded ahead of an unsupported Python version, with the migration scheduled around a G-Cloud procurement deadline.
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.
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.
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.
Yes, on NVIDIA RTX PRO 4000 and RTX PRO 6000 servers in our Frankfurt facility. GPU plans include 10 included hours a month, which typically cover model deployment, inference-endpoint setup and pipeline tuning.
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.
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.
Yes. The data centre in Frankfurt is inside the EU, and GPU-based AI workloads stay on the same infrastructure, so embeddings, documents and inference requests do not need to cross into a non-EU region.
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.