You will get a fine-tuned LLM trained on your data for your use case
Project details
Generic AI models don't know your domain, your tone, or your formats. I fine-tune language models on your data so they respond like a trained member of your team consistently, at lower cost per request, and under your control.
WHAT I DELIVER:
• Honest scoping first: if prompt engineering solves it cheaper, I'll tell you (that's the Starter tier)
• Dataset preparation: cleaning, formatting, and structuring your examples for training
• LoRA/QLoRA or full fine-tuning on open-source models (Llama, Mistral, Qwen) or provider fine-tuning APIs
• Rigorous evaluation against the base model, you see measurable improvement, not vibes
• Deployment-ready output: model weights, inference code, and documentation
WHY ME:
I'm an AI engineer with 12+ years in ML and data engineering. I run a B2B platform delivering AI systems for enterprise workflows, and model training and tuning is part of what I ship to production with the MLOps discipline (evals, versioning, monitoring) that separates working models from demos.
Not sure if you need fine-tuning or just better prompting? Message me with your use case I'll give you a straight answer before you spend anything.
WHAT I DELIVER:
• Honest scoping first: if prompt engineering solves it cheaper, I'll tell you (that's the Starter tier)
• Dataset preparation: cleaning, formatting, and structuring your examples for training
• LoRA/QLoRA or full fine-tuning on open-source models (Llama, Mistral, Qwen) or provider fine-tuning APIs
• Rigorous evaluation against the base model, you see measurable improvement, not vibes
• Deployment-ready output: model weights, inference code, and documentation
WHY ME:
I'm an AI engineer with 12+ years in ML and data engineering. I run a B2B platform delivering AI systems for enterprise workflows, and model training and tuning is part of what I ship to production with the MLOps discipline (evals, versioning, monitoring) that separates working models from demos.
Not sure if you need fine-tuning or just better prompting? Message me with your use case I'll give you a straight answer before you spend anything.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Enhanced Classification, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, NVIDIA AI Platform, PyTorch, TensorFlowAI Models
BERT, BLOOM, Dolly, GPT-4, GPT-Neo, LLaMA, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$900
|
Standard
$2,500
|
Advanced
$4,000
|
|---|---|---|---|
| Delivery Time | 12 days | 21 days | 45 days |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | ||
Model Documentation | |||
Model Monitoring | - | - | |
Model Testing & Optimization | |||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | - | ||
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
Optional add-ons
You can add these on the next page.
extra training dataset prep
+$400
Hosted inference endpoint setup
+$500
30 days extended support
+$400Frequently asked questions
About Reza
AI Engineer | Agentic AI, RAG, LLM Fine-tuning | Python, Azure ML
Toronto, Canada - 6:54 pm local time
At bluemouse.ai, I design, train, and deploy intelligent systems that handle real-world automation at scale. My focus: Agentic AI, RAG, fine-tuning, and computer vision applications that drive measurable business outcomes.
Technical Expertise:
✅ Agentic AI & Orchestration – Agent design, tool integration, multi-step reasoning, and production deployment
✅ RAG Systems – Vector databases, semantic search, context retrieval, and hybrid search strategies
✅ LLM Fine-tuning & Training – LoRA, QLoRA, full fine-tuning, and custom instruction optimization
✅ Prompt Engineering – Few-shot learning, chain-of-thought design, and systematic prompt optimization
✅ Computer Vision – Object detection, image classification, segmentation, and vision-language models
✅ Data Stack – SQL, Python, PySpark; Azure Databricks, Synapse; distributed computing
✅ ML Operations – Model evaluation, validation frameworks, deployment pipelines, monitoring
Whether building custom fine-tuned models, designing agentic workflows, or deploying computer vision systems, I deliver solutions grounded in both technical rigor and business value.
Explore bluemouse.ai – See agentic AI in action.
Steps for completing your project
After purchasing the project, send requirements so Reza can start the project.
Delivery time starts when Reza receives requirements from you.
Reza works on your project following the steps below.
Revisions may occur after the delivery date.
Use case & data review
We define the task, success metrics, and whether fine-tuning is genuinely the right tool. I review your data for quality and volume.
Dataset preparation
I clean, format, and split your data into training and evaluation sets.