$ cat services/python-ai.md
Python AI integration, by a named engineer
Agencies sell you a bench. I'm Aditya Kumar - Tech Lead @ MM Nova Tech, 9+ years of shipped systems - and I build AI features into existing Python backends with my own hands. The terminal assistant on this site's homepage runs on the same patterns I ship to clients.
AI features inside your Python backend
Chat assistants, retrieval-augmented generation over your own data, document-extraction pipelines, and agents - built into your existing FastAPI or Django app with LangChain or direct provider SDKs. Fits your existing models, tasks (Celery), and data layer. No parallel system.
Production concerns handled, not demoed
Rate limiting, spend caps, prompt caching, streaming, failure modes, and evals. The difference between an AI demo and an AI feature is everything that happens when the API is slow, wrong, or down.
Full-stack delivery
9+ years shipping backend systems for real businesses, from data model to deployed feature. Python where the data and ML-adjacent work lives - one person, no handoffs.
Who this is for
A good fit
- You run a PHP or Node product and need a Python AI service alongside it, with a clean boundary between them.
- You have document pipelines, embeddings, or batch scoring that belong in Python and nowhere else.
- You want the integration and cost model designed by someone who has shipped the rest of your stack.
Not a fit
- Your whole product is Python and you want a lead Python engineer. I will tell you honestly on the call - that is not the shape of work I take.
- You need model training or research. I integrate models; I do not train them.
- You want a data science hire. This is engineering.
How an engagement works
- 01
30-minute call
You describe the workflow that hurts. I tell you honestly whether AI helps - sometimes the answer is a queue and a cron job, and I'll say so.
- 02
Fixed-scope audit
One week. I review your Python codebase, identify the 2-3 highest-ROI AI integrations, and deliver a build-ready spec with cost and latency estimates. Fixed quote up front.
- 03
Build
I implement the spec - tested, rate-limited, spend-capped, deployed. You own the code; nothing is locked to me.
The offer: AI Integration Audit
One week, fixed price, quoted on the call. You get a build-ready spec naming the 2-3 AI integrations with the highest ROI for your Python app - with cost, latency, and risk spelled out.If the honest answer is “AI doesn't help here,” you'll get that in writing instead, and it costs you the call.
Proof, not promises
Read the field notes - end-to-end build walkthroughs of real projects - or the AI engineering series on Dev.to.
- AskAditya - a public LLM endpoint that cannot run up a bill →
The widget in the corner of this page. Four gates before the model, a $10 hard cap, and every number citing the file it lives in.