You will get HR Automation with Multi-Agent AI (Onboarding, Training, FAQs)
Project details
We’ll first go over your project details so I can give you an accurate delivery time and a fair cost estimate.
I will build a custom HR automation system powered by Python, LangChain, CrewAI, and LangGraph to handle repetitive HR processes such as onboarding, document management, FAQ answering, task scheduling, and training reminders.
The system will feature multiple specialized AI agents working together:
• Document Agent: Delivers and manages HR documentation.
• Task Scheduler Agent: Assigns and tracks onboarding tasks automatically.
• FAQ Agent : Answers HR and policy-related questions instantly.
• Training Agent: Sends training reminders and tracks completion.
• Feedback Agent: Collects and analyzes employee feedback using sentiment analysis.
Benefits:
• Reduce HR workload by automating repetitive processes.
• Improve employee onboarding speed and satisfaction.
• Multilingual support for global teams.
• Adaptable to both startups and enterprises.
I will build a custom HR automation system powered by Python, LangChain, CrewAI, and LangGraph to handle repetitive HR processes such as onboarding, document management, FAQ answering, task scheduling, and training reminders.
The system will feature multiple specialized AI agents working together:
• Document Agent: Delivers and manages HR documentation.
• Task Scheduler Agent: Assigns and tracks onboarding tasks automatically.
• FAQ Agent : Answers HR and policy-related questions instantly.
• Training Agent: Sends training reminders and tracks completion.
• Feedback Agent: Collects and analyzes employee feedback using sentiment analysis.
Benefits:
• Reduce HR workload by automating repetitive processes.
• Improve employee onboarding speed and satisfaction.
• Multilingual support for global teams.
• Adaptable to both startups and enterprises.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, Conversational AIAI Development Language
PythonAI Models
ChatGPT, GPT-3, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$80
|
Standard
$250
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 8 days | 12 days | 20 days |
Number of Revisions | 1 | 2 | 1 |
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 | - | - | - |
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SA
Shahzad A.
Oct 15, 2025
Backend AI Developer for AI Agent with RAG Pipeline
Working with Sana was an excellent experience. She successfully completed the backend RAG system for our AI agent with great attention to detail. The project was delivered fully tested, well-documented, and organized — including all source files, FastAPI service, and a clear deployment guide. Communication was smooth throughout, and she was always ready to assist with deployment or testing. Highly professional and reliable — I’d definitely work with her again in future projects.
About Sana
AI Developer | AI Agent Development | RAG | UI Development
Multan, Pakistan - 8:57 pm local time
Not proof-of-concepts that break under real conditions. I engineer backend AI systems and UI Development that operate reliably inside real business environments fast, secure, and fully integrated.
What I Build
- Autonomous AI Agents: Context-aware agents that handle customer support, HR, document processing, or scheduling with zero manual input.
- RAG & Knowledge Systems: Retrieval-Augmented Generation pipelines that give factual, source-backed answers using your company data.
- Email & Workflow Automation: AI systems that read, understand, and reply to emails or perform backend business actions automatically.
- Custom LLM Integrations: GPT, Claude, LLaMA, or DeepSeek embedded into backend workflows for real-time, domain-specific reasoning.
- Multi-Agent Architectures: Coordinated AI units that collaborate to complete multi-step processes and handle complex queries.
Recent Work
AI-Integrated Frappe Backend: A secure, on-premise RAG + LLM system that connects directly with ERP data through FastAPI, LangChain, and LangGraph.
Autonomous Email Reply System : An AI system that reads Gmail messages, analyzes intent, and writes human-like replies automatically using Gmail API + llm.
Customer Support AI Agent: A context-aware support bot that retrieves accurate answers from knowledge bases, maintains conversation memory, and cuts response time by 80%.
Document Intelligence Agent: Multi-agent pipeline that extracts data, generates summaries, and classifies documents with context awareness.
Knowledge Retrieval Platform: FastAPI-based vector search system using FAISS embeddings to provide precise, source-backed responses.
Meeting Intelligence System: An AI workflow that transcribes, summarizes, and extracts action points from recorded meetings using LLM reasoning and RAG.
Why Clients Hire Me
100% focused on backend AI I design the architecture, pipelines, and logic that power real-world systems.
I build from scratch: no copy-paste, no “AI wrappers”. Everything is modular, scalable, and production-ready.
I’ve designed and deployed AI systems that cut manual workload by 80% and reduced process times from days to hours.
Clear communication, structured progress, and milestone-based delivery. You’ll always know what’s built and how it performs.
Tech Stack
Python | FastAPI | Flask | LangChain | LangGraph | CrewAI | LLMs | RAG | VectorDB | FAISS | Pinecone | Frappe API | ChromaDB | GPT | Claude | LLaMA | DeepSeek | Groq API | Gmail API |
Full Stack | React Native | UI Development
If you’re looking for an AI developer who builds systems meant to run, not just impress let’s get your project moving.
Steps for completing your project
After purchasing the project, send requirements so Sana can start the project.
Delivery time starts when Sana receives requirements from you.
Sana works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering & Initial Discussion
Review client’s needs via Upwork Chat, clarify goals, and confirm feasibility before starting development.
Requirements & Workflow Mapping
We’ll define your HR process flow, identify automation points, and finalize agent roles.