You will get a RAG pipeline chatbot built on your private documents
Rising Talent
Project details
Your business has valuable knowledge locked inside PDFs, contracts, manuals, wikis, or databases. I build RAG (Retrieval-Augmented Generation) pipelines that let you or your customers ask questions in plain language and get accurate, sourced answers from that private data.
No hallucinations. No generic AI answers. Only answers grounded in your actual documents.
What I build:
• Document ingestion pipeline (PDF, DOCX, TXT, HTML, Notion, Confluence, URLs)
• Intelligent chunking strategy and embedding (OpenAI, Cohere, or local models)
• Vector database setup (Pinecone, ChromaDB, Weaviate, or FAISS)
• LangChain or LlamaIndex orchestration layer
• Conversational memory with source citation
• REST API backend (FastAPI or Node.js) ready to connect to any frontend
• Clean chat UI or integration into your existing app
• Accuracy evaluation and testing before delivery
Use cases: legal document Q&A, internal knowledge base, product manual assistant, contract review tool, HR policy chatbot, customer support trained on your docs.
No hallucinations. No generic AI answers. Only answers grounded in your actual documents.
What I build:
• Document ingestion pipeline (PDF, DOCX, TXT, HTML, Notion, Confluence, URLs)
• Intelligent chunking strategy and embedding (OpenAI, Cohere, or local models)
• Vector database setup (Pinecone, ChromaDB, Weaviate, or FAISS)
• LangChain or LlamaIndex orchestration layer
• Conversational memory with source citation
• REST API backend (FastAPI or Node.js) ready to connect to any frontend
• Clean chat UI or integration into your existing app
• Accuracy evaluation and testing before delivery
Use cases: legal document Q&A, internal knowledge base, product manual assistant, contract review tool, HR policy chatbot, customer support trained on your docs.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
BigDL, Chainer, deeplearn.js, Google AutoML, MATLAB, MLflow, OpenCV, PyBrain, Sonnet, TheanoAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,000
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 18 days |
Number of Revisions | 3 | 5 | 8 |
AI Model Integration | - | ||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - | - |
Frequently asked questions
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iheb m.
Aug 31, 2025
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I really appreciate their attention to detail, problem-solving ability, and commitment to meeting deadlines. I would definitely recommend [Freelancer’s Name] to anyone looking for a dedicated and talented professional. I look forward to working with them again on future projects.
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The freelancer did an excellent job! The work was delivered on time, with great attention to detail and professionalism. Communication was smooth, and the final result exceeded my expectations. Highly recommended
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I’m very satisfied with the work delivered! The freelancer was professional, responsive, and delivered everything on time with great quality. I really appreciate the effort and dedication put into this project and would definitely recommend working with him.
About Nader
AI Mobile & XR Developer | Flutter | Unity | LLM Integration
Borj Cedria, Tunisia - 2:51 am local time
Chat assistants, AI coaching apps, LLM-integrated workflows, real-time AI features inside existing apps
— Enterprise XR & Unity simulations
Training simulations, serious games, AR/VR prototypes for industrial and medical clients, Photon multiplayer, cross-platform deployment
— Flutter apps from MVP to App Store
Full-cycle development: architecture, Firebase backend, payment integration, App Store + Play Store submission
Why clients work with me:
→ I've maintained a $10K+ long-term engagement for a single client — I'm not a one-project developer
→ Production-ready code with clean architecture, not copy-paste tutorials
→ I flag problems before they become blockers, not after
→ Fast response, honest timelines, zero scope surprises
Tech stack:
Flutter · Dart · Unity · C# · Firebase · Node.js · OpenAI API · Claude API · Gemini · REST APIs · Photon · AR Foundation · XR Toolkit · .NET · Angular · React · Figma
Flutter developer | Flutter app developer | AI mobile app developer | AI app development | Flutter Firebase | Flutter OpenAI integration | Flutter Claude AI | Flutter Gemini | Unity developer | Unity XR developer | Unity AR developer | Enterprise XR simulation | Unity training simulation | Serious game developer | Flutter iOS Android | Mobile app developer | Flutter MVP developer | LLM integration developer | AI chatbot mobile app | Flutter Node.js | Flutter full stack | Unity C# developer | Photon Unity multiplayer | Flutter in-app purchases | App Store submission Flutter | Flutter bug fix | Unity bug fix | Flutter web app | Flutter desktop | AR Foundation Unity | XR Toolkit Unity | Firebase Flutter | Flutter REST API | AI agent mobile app | Flutter Riverpod | Flutter BLoC | Flutter clean architecture
Steps for completing your project
After purchasing the project, send requirements so Nader can start the project.
Delivery time starts when Nader receives requirements from you.
Nader works on your project following the steps below.
Revisions may occur after the delivery date.
Agil
We will complete the project using agile methodology