You will get a production-ready AI agent with RAG and API integrations
Project details
I will build a scoped enterprise AI operations agent that does more than chat. It can understand a business request, retrieve approved knowledge with RAG, return cited answers, call permitted APIs, and pause high-impact or low-confidence actions for human approval.
This service fits customer support, internal operations, document workflows, and back-office automation. I can integrate the agent with Java/Spring Boot services, REST APIs, databases, dashboards, and team workflows.
Delivery can include:
• Structured agent workflow and tool calling
• RAG with citations and metadata filters
• API and database integration
• Confidence gates and human approval
• Audit logs for sources, decisions, and actions
• Source code, setup files, tests, and documentation
Each package covers one defined business workflow. Standard includes one knowledge source and one API. Advanced includes up to two APIs, an approval flow, auditability, testing, and deployment support.
Please message me before purchase if your workflow spans multiple teams, data sources, or systems so I can confirm the scope.
This service fits customer support, internal operations, document workflows, and back-office automation. I can integrate the agent with Java/Spring Boot services, REST APIs, databases, dashboards, and team workflows.
Delivery can include:
• Structured agent workflow and tool calling
• RAG with citations and metadata filters
• API and database integration
• Confidence gates and human approval
• Audit logs for sources, decisions, and actions
• Source code, setup files, tests, and documentation
Each package covers one defined business workflow. Standard includes one knowledge source and one API. Advanced includes up to two APIs, an approval flow, auditability, testing, and deployment support.
Please message me before purchase if your workflow spans multiple teams, data sources, or systems so I can confirm the scope.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
JavaAI Tools
Azure OpenAI, Hugging FaceAI Models
ChatGPT, GPT-4, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$299
|
Standard
$899
|
Advanced
$1,999
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 18 days |
Number of Revisions | 1 | 2 | 3 |
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 |
Frequently asked questions
About Hongkai
AI Agent & RAG Developer | Java, Spring Boot, Vue, LLM APIs
Beijing, China - 4:03 am local time
My core focus is AI agents and AI-enabled enterprise systems: agent workflows, RAG and knowledge retrieval, tool calling, multi-agent orchestration, LLM API integration, structured outputs, evaluation and guardrails, and human approval flows. I can connect OpenAI, Anthropic, or local models to existing Java/Spring Boot services, databases, internal APIs, Feishu/Lark, and web dashboards.
With 5+ years of full-stack experience in aviation logistics and business operations, I can handle architecture, backend, frontend, integration, deployment, and debugging end to end.
What I can deliver:
- AI agents for customer service, operations, research, document processing, and internal automation
- RAG knowledge bases with hybrid retrieval, citations, access control, and feedback loops
- Multi-agent workflows and task orchestration
- LLM and API integrations with reliable structured outputs and audit trails
- Spring Boot REST APIs, microservices, Vue interfaces, MySQL/PostgreSQL, and Redis
- Docker-based deployment, monitoring, and performance optimization
- Existing-system modernization and complex business workflow implementation
I focus on production readiness: clear scope, maintainable code, security boundaries, observability, testing, and measurable business outcomes. I can start with a small paid proof of concept and turn it into a stable service.
Steps for completing your project
After purchasing the project, send requirements so Hongkai can start the project.
Delivery time starts when Hongkai receives requirements from you.
Hongkai works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement and acceptance mapping
Confirm the workflow, users, data, integrations, success metrics, approval points, and out-of-scope actions.
Agent architecture and RAG setup
Design the agent states, prompts, retrieval pipeline, citation format, tool permissions, and integration contracts.