Core Service

AI Application Development

Practical Machine Learning for Real Products

The Strategic Advantage

Why AI Application Development?.

The gap between AI hype and what founders actually need is massive. You probably don't need to train a 100-billion parameter foundation model from scratch. You likely need a robust classification endpoint, intelligent data extraction, or a perfectly prompted RAG (Retrieval-Augmented Generation) pipeline.

I focus on practical AI. Whether it's integrating the OpenAI API to summarize complex reports, or training a custom scikit-learn model for a specific classification task, I build AI features that ship to production and actually drive revenue.

I've built and deployed a Fake News Detection System achieving 94% accuracy using TF-IDF and LSTM, wrapped in a FastAPI endpoint. That's real AI in production, not just a ChatGPT wrapper.

Key Benefits

  • Custom NLP Models: Text classification, sentiment analysis, and intelligent routing.
  • LLM Integration: Securely integrate GPT-4 or Claude with your proprietary database (RAG).
  • Predictive Analytics: Turn your existing data into actionable business forecasts.
  • Production Serving: ML models deployed efficiently via FastAPI and Docker.
  • Cost Optimization: Knowing when to use a cheap open-source model vs an expensive API.

Comprehensive Solutions

My Offerings.

🧠

LLM & RAG

Connect Large Language Models to your private data for accurate, hallucination-free answers.

📊

Predictive ML

Custom models using scikit-learn or TensorFlow for regression and classification.

API Deployment

Wrap Python machine learning models into highly concurrent REST APIs.

Modern Tools

My Tech Stack.

Pythonscikit-learnTensorFlowFastAPIOpenAI APILangChainDocker

Proven Experience

Real Projects.

See how I've implemented these technologies in real-world production environments.

Technical Comparison

LLM APIs vs Training Custom Models.

CriteriaOpenAI/Claude APICustom Model Training
Time to MarketDays/WeeksMonths/Years
CostLow (Pay per token)Extremely High (GPU Compute)
Use CaseText, Logic, ChatHighly proprietary data patterns
MaintenanceManaged by ProviderRequires MLOps team

How I Work

Development Process.

01
Discovery
02
Proposal
03
Build
04
QA
05
Launch

What Clients Say

Real feedback from real projects.

"Nimesh built the GymTaar Flutter app from scratch — gym management, member tracking, trainer scheduling, the works. We had it on the App Store in about 10 weeks. Clean code, zero hand-holding required, and he flagged a database design issue in week two that would've caused us real pain later. Would hire again without hesitation."
RA

Rajin Acharya

Founder, GymTaar (Nepal)

"We needed the BabalCloud platform built fast and built right. Nimesh delivered a Next.js frontend with a Django backend that's been running in production for over a year with no major issues. What stood out was the communication — weekly updates, no surprises, and he pushed back on a couple of feature requests that would've added weeks of scope for no real user benefit."
AB

Anupam Bista

Founder, BabalCloud (Nepal)

"Our Insuretech Nepal website needed to handle a lot of dynamic content and load fast on mobile. Nimesh sorted out the architecture properly from the start — server-side rendering, proper SEO setup, and it scored well on Core Web Vitals on launch day. He works like someone who's done this before, not like someone learning on your project."
SS

Suman Silwal

CEO, Insuretech Nepal

Common Inquiries

Frequently Asked Questions.

Can you integrate ChatGPT into my app?

Yes, I integrate OpenAI's GPT-4 API (along with Claude or Gemini) into applications, typically using a RAG architecture so the AI can answer questions based on your specific company data.

How long does it take to train a model?

If we are fine-tuning an existing model or using traditional ML (like Random Forests), it can take a few weeks. Training deep neural networks from scratch takes significantly longer.

What data do I need?

For custom ML, you need clean, labeled data. If you don't have data, we usually start with an LLM API approach, or build the application to start collecting the necessary data first.

Is AI development expensive?

Integrating an existing API (like OpenAI) is very affordable—features start around $1,500. Building custom data pipelines and training bespoke models is more expensive, starting around $4,000.

Where do you host the AI models?

For custom models, I wrap them in FastAPI and deploy them via Docker to AWS EC2 or DigitalOcean Droplets, ensuring they scale properly under load.

Investment

Transparent pricing — no surprises. All prices in USD.

Fixed Price

From $500

Defined scope, milestones, and delivery date. Ideal for well-specified projects where the requirements won't change.

Most popular

Hourly Rate

$25–$45 / hr

Flexible for ongoing work, iterations, or evolving requirements. Billed weekly with time reports.

Retainer

From $800 / mo

Dedicated hours each month. Priority availability. Best for long-term product partnerships.

Free 30-min consultation included with every inquiry. Contact me for a tailored estimate.

Get In Touch

Start Your Project.

Start Your Project

Ready to turn your ideas into reality? Fill out the form below with your project details, and I will get back to you within 24 hours with a free consultation and quote.

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Need a Developer?

I'm based in Kathmandu and available for freelance projects worldwide. Let's build something that works.

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