You will get Agentic RAG Chatbot with MCP & LLM Integration
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Project details
I build intelligent, agentic chatbots using cutting-edge RAG architecture and MCP integration with large language models. My solutions autonomously retrieve and synthesize knowledge from multiple sources to provide precise, context-aware responses that reduce support costs and improve customer satisfaction. Clients benefit from scalable, production-ready systems deployed seamlessly with FastAPI, vector databases, and real-time monitoring. With 5+ years in AI and backend development, I deliver clean, tested code and comprehensive support for a smooth launch and ongoing optimization.
AI Algorithms
Large Language Model, Linear Discriminant Analysis, Multimodal Large Language Model, Self-Organizing MapAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI Text-to-Speech, AI-Generated Art, AI-Generated Code, Conversational AI, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, GPT-Neo, LLaMA, Midjourney AI, Naive Bayes Classifier, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$250
|
Standard
$450
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 7 days | 15 days | 20 days |
Number of Revisions | 2 | 3 | 5 |
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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About Kunal
AI Engineer for Software Development & Digital Transformation
100%
Job Success
Ahmedabad, India - 7:55 am local time
I have 7+ years of experience across software architecture, SaaS development, API integration, cloud systems, and product delivery. I usually work with clients before or during development to bring clarity around the right AI approach, MVP scope, architecture, timeline, risks, and execution plan.
I can help with:
- AI integration strategy for SaaS products and web applications
- RAG architecture for document, knowledge base, and internal search systems
- AI chatbot, AI assistant, and AI copilot planning
- AI agent and multi-agent workflow design
- OpenAI, Claude, Gemini, Cursor, LangChain, and LlamaIndex solution planning
- AI-powered document processing, summarization, search, and reporting
- SaaS architecture, API integration planning, and cloud readiness review
- AI MVP scoping, technical roadmap, and development team guidance
Clients usually come to me when they need answers to questions like:
1. Can AI actually solve this product or business problem?
2. Should this be a chatbot, RAG system, AI agent, copilot, or simpler AI feature?
3. How do we connect AI with our SaaS product, database, CRM, internal tools, or APIs?
4. How do we reduce hallucinations and unreliable AI responses?
5. What should be included in the first MVP?
6. What will it take to build this securely, scalably, and cost-effectively?
My focus is not “adding AI” just because it sounds good. My focus is helping clients build AI features that solve real product, workflow, and business problems.
Relevant areas I can help plan:
1) AI Integration for SaaS Products - AI search, AI assistants, AI copilots, automated summaries, smart recommendations, document analysis, reporting workflows, and backend AI features for SaaS products and internal platforms.
2) RAG Systems and Knowledge Assistants - RAG architecture for products that need to answer from documents, PDFs, websites, customer records, internal knowledge bases, or structured business data.
3) AI Chatbots and AI Agents - Planning chatbot and agent workflows with conversation flow, role-based access, admin controls, escalation logic, backend integration, API actions, and human review where needed.
Tools and technologies I work around include OpenAI, ChatGPT, Claude, Gemini, LangChain, LlamaIndex, RAG, vector databases, Pinecone, Weaviate, Chroma, Supabase, Python, FastAPI, Django, Node.js, React, Next.js, REST APIs, SaaS architecture, AWS, Azure, Google Cloud, API integrations, CRM/ERP integrations, n8n, Make, and Zapier-style automation.
I bring both technical and business understanding. I can work with founders, product owners, CTOs, business teams, and developers to convert an idea into a clear technical direction.
When needed, I can also support execution through AI and SaaS engineering team.
Steps for completing your project
After purchasing the project, send requirements so Kunal can start the project.
Delivery time starts when Kunal receives requirements from you.
Kunal works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Requirement Analysis
Understand your business goals, data sources, and chatbot requirements. Define use cases, conversation flows, and integration needs to tailor the RAG MCP LLM solution perfectly for your objectives.
System Architecture & Design
Design the technical architecture including RAG pipeline, agentic reasoning modules, MCP integration points, and data flow. Create wireframes and system diagrams for your approval.