I will build an ai chatbot for customer support with accuracy tracking


About this gig
Most RAG chatbots hallucinate they give confident answers that aren't grounded in your actual data. And you won't know it's happening until a customer complains.
I build RAG-powered chatbots with reliability built in, not bolted on. Every conversation is tracked for faithfulness, accuracy, and relevancy with low-confidence or ungrounded responses automatically flagged for human review before the customer sees a wrong answer.
What you get:
*Chatbot grounded in your documents/data (zero-hallucination retrieval)
*Real-time monitoring dashboard faithfulness, deflection rate, accuracy
*Escalation queue that catches bad answers before customers do
*Built with FastAPI, LangChain, Supabase clean, production-ready code
Whether you're a business owner or an agency building for clients, I don't just hand you a chatbot and disappear. I give you visibility into whether it's actually working.
---Let's build something your customers can trust.
Get to know Pathuri Venkat
AI RAG Agent Developer Data Analyst SQL, Power BI,Python
- FromIndia
- Member sinceAug 2026
Languages
Telugu, English
My Portfolio
FAQ
What does "RAG" mean, and why does it matter for my chatbot?
RAG (Retrieval-Augmented Generation) means the chatbot pulls answers directly from your documents/data instead of guessing from general knowledge. This dramatically reduces hallucinations — wrong or made-up answers.
How is this different from a regular chatbot?
Most chatbots give you no visibility into accuracy. Mine comes with a live dashboard showing faithfulness, deflection rate, and flagged conversations — so you always know if it's working correctly
What documents/data can I use to train the chatbot?
PDFs, FAQs, product docs, website content, or any text-based knowledge base. Send me your files after ordering and I'll handle the setup.
Do I need technical knowledge to use this?
No. I set everything up and hand over a working system with clear instructions. The monitoring dashboard is simple — green/red indicators, no technical jargon.

