Technology Services · Python
Python development for data-driven, AI-ready applications
From APIs that serve machine learning models in production to full-stack platforms with complex data models, Dreams Technologies builds Python systems that hold up past the prototype stage. Headquartered in London with a world-class engineering team in India, delivering for clients across the UK, US, Europe, the Middle East, and Asia for over a decade.
What we build
Python solutions we deliver.
Python and Django sit alongside our Node.js and React practices in the stack we list across our own published case studies — not a one-off capability we build up for your project.
Expert Team & Proven Experience
10+ years in the industry, with 500+ happy clients worldwide.
AI & Machine Learning Backends
Python is still the default language teams reach for when machine learning meets production. We build the API layer around your models — wrapping PyTorch, TensorFlow, or scikit-learn with FastAPI for clean, concurrent inference and built-in request validation.
Data Engineering & Analytics Pipelines
Using Pandas, NumPy, and Polars, we build the pipelines that turn raw, messy data into something your team can act on — ETL jobs, scheduled reporting, and transformations that feed dashboards reliably.
Full-Stack Web Platforms
When your product needs built-in authentication, an admin interface, and a relational data model, Django remains the strongest choice — especially for content-heavy platforms and applications in regulated industries.
High-Throughput APIs & Microservices
For API-first products, FastAPI’s async-first design lets a single service handle many concurrent requests while waiting on databases or external calls — a strong fit for mobile backends and integrations that need to scale efficiently.
Workflow Automation & Internal Tooling
Python’s standard library and ecosystem make it well-suited to internal tools — scripts and services that automate repetitive, manual processes across finance, ops, and reporting.
Legacy System Modernization with Python
Older Python 2 codebases and aging Django installs don’t always need a rewrite. We assess, upgrade dependency by dependency, and modernize the architecture incrementally — keeping the system running throughout.
Our approach
A decade of Python delivery, led from the UK
Building and shipping complex software since 2013, across 500+ clients in the UK, US, Europe, Japan, the Middle East, and Asia — we’ve already solved most of the classic Python production problems before they cost you time and money. Our London team manages everything client-facing, from discovery through delivery sign-off, while our engineering team in India handles the deep technical work: senior oversight without the cost of a fully Western dev team.
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Choosing a framework
Django, FastAPI, or Flask — based on your project, not habit
Django, FastAPI, and Flask solve different problems. We pick the framework that fits your data model, team, and performance needs — and tell you which one that is before we start building. We also take over existing Python and Django codebases just as often as we start new ones: older Python 2 systems and aging Django installs don’t always need a rewrite, so we assess the codebase, upgrade dependency by dependency, and modernize the architecture incrementally — keeping the system running throughout, rather than recommending an unnecessary rewrite.
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Governance & process
Compliance, cloud infrastructure, and a clear delivery process
GDPR, HIPAA, and SOC 2 controls — encryption, role-based access control, and audit logging — are designed in from the first architecture decision, not patched in later. The backend behind your app is built by an AWS and Microsoft Azure certified partner, giving direct platform support and deep cloud expertise on every deployment. We start with 1–2 weeks of discovery and architecture planning, move into 1–3 weeks of prototype and technical validation, build the full system across data layer, services, and integrations in sprints with weekly progress reports, and follow every launch with a controlled rollout and 90 days of active monitoring, alerting, and performance tuning based on real usage data.
Book a discovery callBy the numbers
A decade of proven Python delivery.
10+
Years of proven success
500+
Happy clients worldwide
20+
Products we have built
250+
Technical team members
Technologies we work with
- Python 3.14
- Django
- FastAPI
- Flask
- Pandas
- PyTorch
- PostgreSQL
- Redis
- AWS
- Kubernetes
FAQ
Frequently asked questions
What we hear most often about Python projects — framework choice, AI/ML integration, and what happens after launch.
What kinds of Python projects do you take on?
AI/ML backends, data engineering pipelines, full-stack Django platforms, high-throughput FastAPI services, workflow automation, and legacy Python/Django modernization. Our experience spans retail, healthcare, hospitality, and service-based businesses.
Which Python framework will you use for our project?
It depends on what you’re building. Django for full-stack platforms that need an admin panel and a relational data model out of the box. FastAPI for API-first products or anything serving ML models at scale. Flask when you need a lightweight, minimal-footprint service.
Is Python fast enough for our use case?
For I/O-bound work — APIs, web apps, data pipelines — yes, especially with FastAPI’s async support. For genuinely CPU-bound, latency-critical workloads, we’ll tell you honestly if a hybrid approach makes more sense.
Can Python power our AI/ML features directly?
Yes — Python remains the default language for machine learning. We build the FastAPI or Django layer around models built with PyTorch, TensorFlow, or scikit-learn, handling validation, concurrency, and monitoring around the model itself.
Can you work with our existing Python or Django codebase?
Yes. We regularly take over existing Python codebases — auditing dependencies, identifying outdated packages, and modernizing incrementally rather than recommending an unnecessary rewrite.
What happens after the application is launched?
We include 90 days of post-launch support covering monitoring, bug fixes, and performance tuning. After that, we offer optional retainers for feature development and Python version upgrades.
Ready to build a Python backend that scales with your data?
If you have a system in mind — or a model that needs a production-grade API around it — start with a conversation. We’ll tell you what’s feasible, what it will take, and which framework actually fits.