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Flagship · GovTech
India Post — grievance system

Pan-India, awarded via GeM (Nov 2025).

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Flagship · GovTech
India Post — grievance system

Pan-India, awarded via GeM (Nov 2025).

Read →
Global delivery
India · Belgium · UK

Three offices, three time zones.

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Python developers for backend, data and AI teams.

Add senior Python engineers who build Django and FastAPI services, data pipelines and LLM-powered features — working in your codebase and sprints, onboarded in days.

Clients

  • Cushman & Wakefield
  • Pacific Group
  • DLF Group
  • Barbeque Nation
  • The Coffee Bean & Tea Leaf

Selected projects

A selection of the software Mindrops has designed and engineered for clients.

AI · ML

AI-Based Product Development

Mindrops built four production ML products in Python: predictive maintenance, computer-vision body measurement, multi-channel attribution and deep-learning manpower forecasting.

25% lower maintenance cost, 20% fewer sales returns, 15% more sales and 90% better forecasting accuracy for the respective clients.

Total post offices1,65,000The largest postal network in the world

Government · GovTech

India Post — Grievance Redressal

An AI-automated platform on Mindrops’ LazyMonkey foundation that categorises, prioritises, routes and auto-responds to every grievance, with one SLA-tracked record for central and regional teams.

Awarded via GeM (Nov 2025), it auto-triages thousands of grievances a day for a network of 1.5 lakh+ post offices.

Cafés in India50+outlets across India, served by the systems we builtBrewing since 1963

AI · Food & Beverage

BeanBot — The Coffee Bean & Tea Leaf

An embeddable AI chat assistant grounded in live catalogue and store data, with an “Order Now” action on every product and a no-code admin console for content and pricing.

Live across 50+ outlets in India, handling about 10,000 conversations a month and around 50 orders a day.

What Python developers build

Hiring Python developers through Mindrops adds senior Python engineers to your team for backend services in Django or FastAPI, data processing with Pandas and Celery, and AI features built on OpenAI and other LLMs. You interview a shortlist within about 48 hours, onboard in days, and own all code and IP.

Django & FastAPI services

Backends, admin tools and async APIs with typed request models, authentication and tests.

LLM & AI features

Retrieval-augmented generation, structured extraction and assistants on OpenAI and other LLMs, with human review where accuracy matters.

Data pipelines

Ingestion, transformation and validation with Pandas and SQL, scheduled and retried through Celery workers.

Machine learning in production

Trained models packaged behind APIs, versioned and monitored once they are live.

Document processing

OCR plus LLM extraction for invoices, receipts and forms — the approach behind Mindrops’ own Caelum AI.

Integrations & automation

Services that move data between APIs, databases and spreadsheets on a schedule, with logs you can audit.

Teams that hire Python developers

Teams adding AI to a product

Product teams that need retrieval-augmented search, document extraction or an LLM assistant wired into an existing application.

Data-heavy operations

Businesses whose reporting, reconciliation or imports run on fragile scripts and need proper pipelines, scheduling and validation.

Django and FastAPI product backends

Companies running a Python backend that needs new features, endpoints or performance work from senior engineers.

Data science teams short of engineers

Teams whose models work in notebooks but need engineers to package, serve and monitor them in production.

Why hire Python developers from Mindrops

Production AI built in Python
Mindrops built and shipped four production AI products in Python, including predictive maintenance and demand forecasting, on TensorFlow, Keras and PyTorch.
LLM experience from shipped systems
Our LLM work comes from products in use, such as the Caelum AI document engine and AI-assisted invoice capture with human-in-the-loop review built for a client.
Data and AI as everyday work
Python developers come from a company that also delivers data engineering and generative AI projects, so pipeline and model problems are familiar ground.
Careful with your data
NDAs, least-privilege access to datasets and a secure SDLC apply from day one — important when engineers touch customer or financial data.
Python skills and tooling
Core Python skills
Python · Django · FastAPI · Flask · REST
Ecosystem & tooling
PostgreSQL · Pandas · Celery · OpenAI / LLMs

Client reviews

Extra capacity for software and cloud

A Mindrops team working alongside the client’s own engineers on software development and cloud-based projects, brought in to add reliable delivery capacity.

From the client’s review

“Mindrops handled complex requirements with ease and added value throughout the project.”
Harsh BihaniHead of Technology, Qzaark IndiaRead full review on Sortlist

Fintech lending platform

A customer app, vendor app and admin panel from one team, with KYC, CIBIL credit checks and automated loan approvals.

From the client’s review

“Fintech projects have a lot of layers and it was good to work with a team that understood the credit and lending side of things.”
Shyam AryaDirector, Insto Fin Private LimitedRead full review on Sortlist

Food delivery ecosystem

Customer, restaurant-partner and rider apps, an admin panel and a marketing website for a pure-vegetarian delivery service, built from scratch.

From the client’s review

“The customer app, restaurant app, and rider app all feel like they belong to the same ecosystem rather than being built separately and assembled later.”
Jatin AggrawalCo-Founder, Vezito Private Ltd.Read full review on Sortlist

Pet care marketplace

One platform replacing scattered tools for pet food ordering, walker bookings, vet consultations and adoption listings, with customer features and a vendor management backend.

From the client’s review

“The vendor and admin management setup stood out most, since it needed to handle walkers, trainers, cafés, and diagnostic labs within one consistent system.”
Vikas ShokeenDirector, Petinfy (JAVI Services LLP)Read full review on Sortlist

Warehouse operations platform

A field app and web admin panel connecting material records, site expenses and reporting across warehouse locations.

From the client’s review

“Reporting that used to take a full day of compiling sheets is now a filtered download from the admin panel.”
Amit AgarwalDirector, Footprint WarehousingRead full review on Clutch

Recruitment & candidate management

A recruitment platform with candidate registration, applications, admit cards and a central admin dashboard.

From the client’s review

“They designed it to handle high concurrent traffic during active recruitment drives, which was critical for us.”
AnujDirector, NIA Aviation Services Pvt. Ltd.Read full review on GoodFirms

More client reviews

How hiring Python developers works

  1. 01 — Brief

    Frame the Python work

    We capture whether the role is backend, data or AI-focused, plus your frameworks, libraries, seniority and engagement model.

  2. 02 — Shortlist

    Meet matched candidates

    Within ~48 hours you receive vetted Python engineers whose experience fits that focus: Django or FastAPI, pipelines, or LLM work.

  3. 03 — Onboard

    Scoped data access

    After your interview and choice, the engineer joins your repo and sprints within days, with data and environment access granted on least privilege.

  4. 04 — Scale

    Adjust capacity to the roadmap

    Add engineers for a data migration or AI feature, then scale back month to month once it ships.

Frequently asked questions

What kind of work do your Python developers do?
Three main areas: backend services in Django, FastAPI or Flask; data pipelines with Pandas, SQL and Celery; and AI features built on OpenAI and other LLMs. Tell us which focus you need and the shortlist reflects it.
Can a Python developer add LLM features to our existing product?
Yes. Typical work includes retrieval-augmented search over your documents, structured data extraction and assistants, integrated into your application with human review where accuracy matters.
Do your Python developers have production machine-learning experience?
Mindrops has shipped production machine learning in Python, including predictive maintenance and demand forecasting; see the AI product case study. Depth varies by engineer, so state the level you need in your brief.
How soon can a Python developer start?
Most clients see a shortlist within about 48 hours and onboard their chosen engineer within days, after interviewing the candidates themselves.
How can we engage Python developers?
As individual engineers in your team (staff augmentation), as part of a dedicated team, or on fixed-price or time & materials terms for scoped work. See engagement models.
Who owns the code, pipelines and models?
You do. Source code, pipelines, models, documentation and all other IP built for you belong to you.

Contact us

Tell us whether the role is backend, data or AI-focused, your frameworks and the seniority you need. We reply within one business day.

Book a call

An engineer will respond within one business day.

Have a defined scope? Get a quote

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