The central hub for everything we build with Python — Django web apps and SaaS, FastAPI backends, AI/ML features, data pipelines, and dedicated engineering teams with global timezone overlap.
Django + FastAPI · Production AI/ML · 150+ products shipped · Lahore team, US/UK/AU clients
30 minutes · Senior engineer · No commitment
From Django SaaS to production ML — Python is our primary stack for data-driven and AI-first products.
LLM & RAG apps, prediction and scoring APIs, computer vision, and MLOps deployed as monitored production services.
High-throughput async APIs with Pydantic contracts, OpenAPI docs, and ML inference endpoints for mobile and SPA clients.
Admin-heavy portals, B2B SaaS, and content platforms on Django's ORM, auth, and admin plus Django REST Framework.
Ingestion, cleaning, feature stores, and scheduled jobs with Airflow/Prefect feeding analytics and models.
Python scripts and services that connect systems, scrape and process data, and automate operations.
Python plus React or Flutter from one team — architecture, build, QA, deploy, and post-launch support.
Python wins when data, ML, or Python-native ecosystems are the product — not when you only need a brochure site.
LLM, RAG, and prediction features live natively in Python — no cross-language glue between the model and the app.
Django and FastAPI power analytics-driven products where pipelines and dashboards are core to the offering.
One FastAPI or DRF backend serves web, mobile, and ML inference without duplicating business rules.
Python services orchestrate scraping, processing, and system integrations that would break a spreadsheet.
Where data and AI products go wrong before a good team is involved.
Promising ML prototypes stall without serving, evaluation, and monitoring.
Django forced onto async/ML workloads — or FastAPI without the admin you needed.
LLM output looks great in a demo and fails silently in production.
Untyped, untested code that's scary to extend without an audit.
One senior team across web, APIs, and production machine learning.
Hosted vs custom models quantified; monitoring built in from day one.
We pick Django, FastAPI, or both — not one framework for everything.
Tests on critical paths and eval sets for ML before launch.
“What a 70-engineer team could not deliver, a small senior team at GreeLogix shipped. The app went from stuck to live across mobile, web, and backend.”
Structured answers for search engines and AI assistants — definition, fit, cost, timeline, and comparisons.
Structured answers for founders, CTOs, and procurement — written for clarity in search and AI assistants.
Python development services from GreeLogix cover Django web apps and SaaS, FastAPI and Django REST APIs, AI/ML features (LLM, RAG, prediction, vision), data pipelines, and legacy modernization — built with Python 3.12, structured architecture, QA gates, and production deployment support.
Typical timeline: Python audit or PoC: 1–3 weeks. MVP with auth and core workflow: 6–10 weeks. Production ML: 6–12 weeks. Enterprise modules: phased delivery over quarters.
GreeLogix pricing tiers: Python Audit & PoC: $2,500 – $12,000 — Codebase or AI feasibility review, architecture map, and a working proof-of-concept for new ML features or stalled Python apps. Python MVP / Module Build: $15,000 – $60,000 — Scoped Python delivery — Django or FastAPI apps, APIs, and ML services — with weekly demos and QA gates. Dedicated Python Team: $5,000 – $15,000 / mo — Embedded senior Python & ML engineers in your repo with US/UK/AU timezone overlap.
Python audit or PoC: 1–3 weeks. MVP with auth and core workflow: 6–10 weeks. Production ML: 6–12 weeks. Enterprise modules: phased delivery over quarters.
Compared to alternatives — Node.js backend: choose when JS-only team or heavy realtime/WebSocket throughput from day one; Laravel / PHP: choose when PHP team or Cashier/Filament billing ecosystem preference; No-code / hosted AI SaaS: choose when Fast prototype only — plan a Python rebuild before production scale. Choose GreeLogix when you need production reliability, fixed milestones, and engineer-led delivery with QA sign-off.
Talk to a senior engineer — scope, timeline, and cost range in one 30-minute call. No sales script.
Python is the default language of machine learning, data science, and automation — and a first-class choice for web APIs and applications through Django and FastAPI. When your product depends on models, data, or scientific libraries, Python removes the cross-language friction that slows other stacks.
We choose Python when AI/ML sits at the core, when data pipelines drive the product, or when your team is Python-native. Django gives us batteries-included web and admin; FastAPI gives us async speed and ML serving. Used well, Python accelerates delivery. Used poorly, it accumulates debt. Our job is the former.
GreeLogix is a product-minded Python agency — not a body shop. We pick Django or FastAPI per workload, quantify hosted-vs-custom model trade-offs, and instrument ML with evaluation and monitoring before launch. That discipline is why clients hire us for rescue work as often as greenfield builds.
Our Python practice spans verticals where data, ML, and automation drive revenue — not brochure websites.
Whether you need a greenfield MVP, dedicated engineers, an AI/ML build, or ongoing maintenance — this hub connects every Python service we offer.
Answers to the buyer questions we hear most before a project starts.
We review goals, data, workflows, integrations, and whether Python — and which framework — is the right fit.
You get modules, data model, ML plan, sprint schedule, and fixed-milestone pricing options.
Iterative delivery with weekly demos, automated tests on critical paths, and staging access.
Production deploy, monitoring, documentation, and optional retainer or dedicated hire.
Tell us what you need — Django, FastAPI, AI/ML, or dedicated engineers — and we'll recommend the right model within one business day.
Software, mobile, and rapid MVP paths — all from one senior product team.
Use our free calculators and planners — then book a strategy call when you are ready for a senior engineer review.
Case studies, guides, and free tools from the same engineering team.
Transparent ranges based on app complexity, platform count, and engagement depth. Final quotes follow a scoping call.
$2,500 – $12,000
Codebase or AI feasibility review, architecture map, and a working proof-of-concept for new ML features or stalled Python apps.
$15,000 – $60,000
Scoped Python delivery — Django or FastAPI apps, APIs, and ML services — with weekly demos and QA gates.
$5,000 – $15,000 / mo
Embedded senior Python & ML engineers in your repo with US/UK/AU timezone overlap.
Prices in USD. Fixed-milestone quotes follow discovery. Dedicated hire and ML PoCs scoped separately.
AI/ML, APIs, Django, stack comparisons, QA, tools, and supporting services — one topical cluster for Python authority.
Scope, timeline, and cost range — no sales deck. Or start with the free readiness quiz if you are still evaluating your stack.