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I will build a rag chatbot trained on your private docs
Cristian
Level 1
About this gig
I build RAG chatbots that answer only from your own documents and cite the source on every reply, so users can trust what the bot says.
The generic chatbot you tried confidently makes things up. Mine retrieves the relevant passage from your PDFs, Notion, knowledge base, or live website first, then answers grounded only in that passage. When a topic is outside your docs the bot stays silent instead of guessing. That is what actually earns trust.
Most sellers hand you a no-code shell. What they skip is the retrieval tuning that decides whether answers are correct, the secure data handling, and someone who has shipped this in production. I have: a RAG system over a client's full email history, 29 intents mapped, source-cited, running over six months with zero hallucinations on covered topics.
Solo AI engineer at Uva Automation Studio (@crissenpai). No agency markup. You talk to the person writing the code.
Message me before ordering and I will map your architecture for free in one exchange. AI use is disclosed, the build is fully licensed for your commercial use.
Get to know Cristian
Cristian
AI Agents and Automation Engineer
Level 1
- FromItaly
- Member sinceMar 2021
- Avg. response time2 hours
- Last delivery1 week
Languages
English, Italian
I'm Cristian, founder of Uva Automation Studio. I build AI automation that ships to production: AI voice agents that call, qualify leads and book meetings (Vapi, Retell, Twilio), n8n workflows and AI agents, voice cloning and text to speech, and chatbots that answer from your own documents.
You get the whole build, not a demo. Clean code on your server, documented, set to run without me. 40+ projects for clients across the UK, US, Australia, Pakistan and Canada. I'm also studying Computer Engineering at the University of Bologna.
Tell me what's eating your time and I'll build it.
My Portfolio
FAQ
How is this different from a standard ChatGPT chatbot?
A standard ChatGPT bot answers from its training data and guesses about your business. A RAG chatbot retrieves the matching passage from your documents first, answers only from it, and shows the source so you can verify. No made-up answers on topics your docs cover.
Why not just use a $20 gig or a no-code tool?
No-code tools give you a shell. What they skip is proper chunking and retrieval tuning (which decides accuracy), secure private-data handling, a real vector DB, and someone who has shipped this in a live environment. You are paying for a system that works reliably, not a widget that demos well.
Is my private data safe? Will it be used to train any AI model?
No. Your documents only build your vector index and never go to any training pipeline. On the Fortress tier the whole system runs on your own VPS, so files never leave your control. On Grounded and Verified your credentials stay in your own accounts.
Can it run fully self-hosted so my documents never leave my server?
Yes, that is the Fortress tier. Full self-hosted deployment via Docker, role-based access control, and your own inference endpoint if needed. I apply OWASP best practices throughout and deliver a full runbook so your team can operate it independently.
What document types and platforms can you connect?
PDFs, Word and Google Docs, Notion, Confluence, your website (crawled), Google Sheets, or a SQL/Postgres DB. Deploy as a website widget, Telegram, WhatsApp, Slack, or a REST API. Something unusual? If it has an API or an export, I can most likely ingest it.
What happens when someone asks something that is not in my documents?
The bot says it does not know, cleanly, without guessing. I tune the retrieval threshold so that if no document passage meets the confidence cutoff the bot explicitly declines to answer rather than fabricating one. That guardrail is the difference between a demo and a production system.
What do I need to provide before you start?
Four things: your doc sources (Drive link, Notion share, PDF ZIP, or website URL), a rough count of docs or pages, who uses the bot and for what, and where you want it deployed. Not sure yet? Message me first and I will map it out before you commit.
Which package is right for me?
Grounded ($249) fits one source and a simple use case, like a FAQ or product-docs bot. Verified ($599) suits businesses with multiple sources, a branded UI, and lead capture. Fortress ($1,400) is for confidential data that must run on your own server with role-based access. Message me to pick.
