You will get I will build an AI Agent or LLM application for your business
Project details
You will receive a professionally engineered LLM solution tailored to a clearly defined business workflow. Depending on the selected package, the scope may include document-based RAG, agent and tool-calling workflows, LLM/API integration, evaluation, and deployment guidance.
I focus on production-minded implementation: clear architecture, grounded responses, predictable agent behavior, observability, cost and latency awareness, and maintainable code-not just a demo prompt.
Typical deliverables may include:
• Solution architecture and technical plan
• Implementation of the agreed LLM, RAG, or agent workflow
• Integrations included in the selected package
• Representative testing and evaluation
• Source code, setup instructions, and handoff documentation
The project begins after the required information and representative test cases are provided. Model/API usage, cloud hosting, paid third-party services, extensive UI development, and features outside the selected package are not included unless explicitly added to the scope.
Please message me before purchasing if your project involves sensitive data, regulatory compliance, legacy systems, or a complex production deployment.
I focus on production-minded implementation: clear architecture, grounded responses, predictable agent behavior, observability, cost and latency awareness, and maintainable code-not just a demo prompt.
Typical deliverables may include:
• Solution architecture and technical plan
• Implementation of the agreed LLM, RAG, or agent workflow
• Integrations included in the selected package
• Representative testing and evaluation
• Source code, setup instructions, and handoff documentation
The project begins after the required information and representative test cases are provided. Model/API usage, cloud hosting, paid third-party services, extensive UI development, and features outside the selected package are not included unless explicitly added to the scope.
Please message me before purchasing if your project involves sensitive data, regulatory compliance, legacy systems, or a complex production deployment.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, Natural Language Generation, Natural Language Understanding, Sentiment AnalysisAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, PyTorchAI Models
GPT-4, LLaMA, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$149
|
Standard
$399
|
Advanced
$899
|
|---|---|---|---|
| Delivery Time | 7 days | 13 days | 20 days |
Number of Revisions | 1 | 2 | 4 |
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.
Additional Revision
+$50Frequently asked questions
About Nhat
AI Software Engineer | AI Agents, LLM Applications & RAG
Hanoi, Vietnam - 1:18 pm local time
What I can build:
- AI Agents & tool-calling systems
- LLM applications & RAG
- AI chatbots and business automation
- OpenAI / Claude integrations
- AI APIs & backend services
- AI evaluation, observability and optimization
I focus on practical engineering: choosing the right architecture, integrating AI into existing systems, and making AI applications reliable, maintainable, and cost-efficient.
Steps for completing your project
After purchasing the project, send requirements so Nhat can start the project.
Delivery time starts when Nhat receives requirements from you.
Nhat works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1 - Use-Case and System Review
I review the goals, workflows, data sources, constraints, and selected package. I confirm the scoped deliverables and identify
Step 2 - Architecture and Technical Plan
I design the LLM workflow, model strategy, RAG or agent components, integrations, evaluation approach, and deployment structure appropriate to the selected package.