Django, FastAPI and Flask builds from teams who also ship the models. When your product needs AI, the data pipeline and the app are designed together.
Trusted by teams worldwide
Six service lines covering products, services and the data infrastructure underneath them.
Honest engineering judgement across the Python stack, backed by our AI and API teams.
Python is our primary language for AI work: model serving, LLM integration and ML pipelines are daily work, not a stretch assignment.
Real production experience across Django, FastAPI and Flask means we recommend the right tool, not our favorite one.
Production Airflow and Celery pipelines processing real data volumes, not a toy ETL script.
Django's battle-tested security defaults and careful FastAPI/Flask configuration, not an afterthought before launch.
Pytest coverage for critical paths, so future changes don't silently break existing functionality.
Your idea and model architecture are legally protected before any technical conversation begins.
One call and a look at your codebase tells you where the bottleneck really is, what is worth refactoring and a fixed budget. Often it is not what the team assumes.
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A process that keeps data and application work in step, rather than integrating them at the end.
We map the domain, data sources and scale expectations, then agree a fixed quote.
Schema, service boundaries and pipeline design settled before feature work.
Application and data work built in parallel sprints with weekly demos.
Automated tests, load testing and a security review before release.
Deploy with CI/CD, monitoring and ongoing support.
The same team ships the model and the app around it.
Django, FastAPI and Flask, chosen per use case rather than per habit.
Suites that run on every push, so releases stay predictable.
Typical time from discovery to production.
Real products, real users, real numbers, across health, mobility, delivery and education.
Mood tracking, guided sessions and personalised wellness plans in a warm, calming experience.
Live driver tracking, surge-aware fare estimation and multi-payment support in a fast, reliable app.
Live order tracking, smart dispatch and route optimisation that cut delivery times across 200+ restaurants.
Coach matching, personalised study plans and adaptive progress tracking for 10K+ students.
Six workloads where Python is the right call, and where we have shipped it.
Model-backed features inside real products.
Pipelines that feed reporting and models.
Numerical work that has to be exactly right.
Clinical and operational analytics.
Pricing, demand and recommendations.
Sensor data turned into decisions.
“Appther built our student competition app exactly the way we envisioned it: easy registration, smooth judging, and real-time results that keep participants engaged.”
“Building a mental health app means every detail has to be handled with care, and Appther got that from day one. The product feels warm, simple, and genuinely helpful.”
“Appther exceeded every expectation, on time and on budget, and the final product has been instrumental in scaling our business. A rare engineering partner.”
“Implementing an ERP across our operations felt daunting at first, but Appther made the transition seamless. Every department now works off a single source of truth.”
Field notes from real builds. No hype, just what worked and what didn't.
What each is genuinely better at, and what the benchmarks hide.
Profiling results from real Python performance work.
Getting a model into production before you buy the tooling.
A clear breakdown of what drives cost, and how to scope it.
Walk away from one call with a framework recommendation, an architecture direction, a realistic budget range and a timeline. No pitch deck, no obligation.
Tell us what you are building and what data it depends on. No sales pitch, just a straight answer on approach, scope, timeline and cost. Prefer email? Use our contact page.
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