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You will get a custom RAG chatbot trained on your documents, PDFs, or website

Yaqov B.Status: Offline
Yaqov B.
Preview image

Let a pro handle the details

Buy Generative AI services from Yaqov, priced and ready to go.
Yaqov B.Status: Offline
Yaqov B.
Preview image

Let a pro handle the details

Buy Generative AI services from Yaqov, priced and ready to go.

Project details

You'll get a production-ready RAG (Retrieval-Augmented Generation) chatbot trained on YOUR documents — PDFs, websites, knowledge bases, support tickets, or any text data. The bot answers questions with accurate, grounded responses and citations back to the source, so users (and you) can trust every answer.

I'm a senior AI engineer who builds RAG systems for real businesses, not toy demos. Stack: LangChain / LlamaIndex, OpenAI / Anthropic / open-source LLMs, vector databases (Pinecone, Weaviate, Qdrant, pgvector), and clean web UIs. I focus on retrieval quality, prompt design, and evaluation — the things that actually make a RAG chatbot useful vs. frustrating.

Whether you want a customer support bot, an internal knowledge assistant, or a research tool over hundreds of documents, I'll deliver a working chatbot deployed where your users actually are — your site, Slack, or a hosted dashboard. Source code included.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer Model
AI Applications
AI Chatbot, AI Content Creation, Conversational AI, Natural Language Generation, Natural Language Understanding
AI Development Language
Python
AI Tools
Hugging Face
AI Models
BERT, ChatGPT, GPT-4, LLaMA
What's included
Service Tiers Starter
$399
Standard
$899
Advanced
$1,999
Delivery Time 5 days 10 days 21 days
Number of Revisions
123
AI Model Integration
Batch Normalization
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Database Integration
Detailed Code Comments
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Image Upscaling
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MLOps
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Model Deployment
Model Documentation
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Model Monitoring
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Model Testing & Optimization
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Model Tuning
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Natural Language Processing
NLP Tokenization
Pre-Training
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Prompt Engineering
Setup File
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Source Code

Frequently asked questions

Yaqov B.Status: Offline

About Yaqov

Yaqov B.Status: Offline
Agentic AI Systems Architect | LLM Orchestration, Full-Stack & Busines
Shlomi, Israel - 4:10 pm local time
I build production-grade Agentic AI systems, LLM-powered automation pipelines, and full-stack SaaS platforms that deliver measurable ROI — not just code that works in a dev environment.

With 20+ years of hands-on experience as a CTO and AI Systems Architect, I specialize in the most in-demand areas of 2026:

▸ AGENTIC AI & LLM ORCHESTRATION
Multi-agent systems, autonomous decision-making pipelines, RAG architectures for enterprise knowledge bases, and custom integrations with Claude, OpenAI, DeepSeek, Groq, and Ollama.

▸ BUSINESS PROCESS AUTOMATION
End-to-end workflow automation using n8n, Python, and custom AI agents. From lead management to customer service to data pipelines — I replace manual work with intelligent, scalable systems.

▸ FULL-STACK SAAS & API DEVELOPMENT
Production-ready platforms built with React, Next.js, FastAPI, Node.js, and PostgreSQL. Microservices architecture, real-time dashboards, and seamless API integrations.

▸ DATA ENGINEERING & AI ANALYTICS
Data pipelines, BI dashboards, predictive analytics, and NLP systems that turn raw data into business intelligence.

What sets me apart: I don't just write code — I own the entire lifecycle from strategy and architecture to deployment and scaling. Clients get a technical partner who understands both engineering and business outcomes.

If you need a specialist who can build, automate, and scale your AI-powered system end-to-end — let's create something exceptional together.

Steps for completing your project

After purchasing the project, send requirements so Yaqov can start the project.

Delivery time starts when Yaqov receives requirements from you.

Yaqov works on your project following the steps below.

Revisions may occur after the delivery date.

Discovery & document ingestion

We review your documents, choose the right chunking + embedding strategy, and build the vector database.

Build the RAG chatbot

I build the retrieval pipeline, LLM prompts, chat UI, and deploy a working bot you can test end-to-end.

Review the work, release payment, and leave feedback to Yaqov.