You will get custom machine learning models and AI solutions for your business


Project details
I deliver not just machine learning models but end-to-end solutions that are scalable, optimized, and business-ready. My expertise in fine-tuning LLMs, NLP tasks, and deep learning ensures innovative and impactful results. With a proven track record of handling complex AI projects, I stand out by offering a collaborative and client-focused approach to problem-solving.
Machine Learning Tools
Amazon SageMaker, Azure Machine Learning, ChatGPT, GitHub Copilot, NLTK, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, Tableau, TensorFlowWhat's included
| Service Tiers |
Starter
$100
|
Standard
$400
|
Advanced
$800
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 1 | 1 | 1 |
Number of Scenarios | 2 | 2 | 2 |
Number of Graphs/Charts | 2 | 4 | 5 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$100
Additional Model Variation
(+ 3 Days)
+$100
Data Source Connectivity
(+ 2 Days)
+$100Frequently asked questions
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LL
Lucas L.
Jun 22, 2025
Python Flask script developer
About Pritesh
Forward Deployed AI Engineer | LLM Integration | Agentic AI Developer
Surat, India - 3:27 am local time
I embed with teams to integrate LLMs and agentic systems into existing production environments, not standalone demos.
Recent results:
- Rebuilt a legacy MS Access system into a full-stack Django + Next.js application for a Canadian power utility, with zero data integrity loss
- Integrated an LLM into an existing communication workflow, cutting review time 15%
Built a fully local multi-agent system for internal HR/accounting queries — all inference on client infrastructure, zero external API calls, for sensitive data
- Delivered client-facing ML integration (auth + REST API) that led to a $500K contract
Fine-tuned 7–13B parameter models (LLaMA, Falcon) with 4–8 bit quantization, cutting compute cost 30%
Stack: Python, FastAPI/Django, Next.js, PyTorch/Transformers, vector search (Pinecone, ChromaDB), AWS/GCP/Azure.
6+ years shipping software, the last 2+ focused on deploying AI into environments that already exist. I learn your codebase and constraints first, then build — not the other way around.
Send me a message with what you're working with and I'll tell you honestly whether I'm a fit.
Steps for completing your project
After purchasing the project, send requirements so Pritesh can start the project.
Delivery time starts when Pritesh receives requirements from you.
Pritesh works on your project following the steps below.
Revisions may occur after the delivery date.
Client Provides Requirements
Share your project goals, data, and any specific preferences.
Initial Review and Plan
I review your requirements and propose the best machine learning approach, tools, and timeline.