You will get a custom AI RAG trained on your company documents to answer questions!
Project details
Stop losing hours answering the same questions. I'll build you a production-grade AI RAG that knows your business, trained on your documents, policies, product docs, or knowledge base using Retrieval-Augmented Generation (RAG).
Unlike generic chatbots, a RAG system retrieves answers directly from YOUR content. Responses are accurate, current, and grounded in your data, with source citations, no made-up answers about your business.
WHAT I'LL BUILD:
• Document ingestion pipeline (PDF, Word, web pages, databases)
• Vector database with semantic search (Pinecone, Qdrant, or pgvector)
• LLM integration (OpenAI, Anthropic Claude, or open-source models)
• Clean chat interface deployable on your website or internal tools
• Prompt engineering tuned to your tone and use case
WHY ME:
I'm an AI engineer with 12+ years in machine learning and data engineering. I run a B2B platform delivering AI agents for enterprise workflows. RAG systems are what I ship to production every day, not a side experiment.
Not sure which tier fits your use case? Message me before ordering and I'll point you to the right one usually within a few hours.
Unlike generic chatbots, a RAG system retrieves answers directly from YOUR content. Responses are accurate, current, and grounded in your data, with source citations, no made-up answers about your business.
WHAT I'LL BUILD:
• Document ingestion pipeline (PDF, Word, web pages, databases)
• Vector database with semantic search (Pinecone, Qdrant, or pgvector)
• LLM integration (OpenAI, Anthropic Claude, or open-source models)
• Clean chat interface deployable on your website or internal tools
• Prompt engineering tuned to your tone and use case
WHY ME:
I'm an AI engineer with 12+ years in machine learning and data engineering. I run a B2B platform delivering AI agents for enterprise workflows. RAG systems are what I ship to production every day, not a side experiment.
Not sure which tier fits your use case? Message me before ordering and I'll point you to the right one usually within a few hours.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation SystemAI Tools
Amazon SageMaker, Azure Machine Learning, deeplearn.js, Deeplearning4j, Keras, MLflow, Open Neural Network Exchange, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$499
|
Standard
$1,200
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | - |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Extra data source integration
+$150Frequently asked questions
About Reza
AI Engineer | Agentic AI, RAG, LLM Fine-tuning | Python, Azure ML
Toronto, Canada - 11:02 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.
Kickoff & document review
I review your documents and use case, confirm scope, and recommend the best LLM and architecture for your needs.
Ingestion pipeline & vector database
I build the document processing pipeline and set up semantic search over your content.