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Fiverr Pro
English
$
USD
I will build a custom rag ai chatbot trained on your documents and data
Sajid Ali
About this gig
Give your customers and team instant, accurate answers from your own documents, help center or database, through an AI assistant embedded in your website or app.
WHAT I BUILD
Ingestion of PDFs, docs, web pages, Notion or database content
Chunking, embeddings and a vector store (pgvector, Pinecone or similar)
Retrieval tuned for accuracy, with source citations in answers
Chat UI as an embeddable widget, React component or API endpoint
Guardrails: answers limited to your content, fallback when unsure
Optional lead capture, human handoff or an admin page to update content
PROCESS
1. Review your data and use cases, agree a set of test questions
2. Build and test against real questions from your business
3. Deploy to your hosting and hand over code, docs and test results
STACK
TypeScript, Node.js, Next.js, OpenAI or Anthropic models, LangChain or a custom pipeline, Postgres pgvector
NOT INCLUDED
AI API and vector database fees (billed to your accounts), cleanup of very large archives, voice or phone bots, or no code platform builds.
Large or sensitive datasets? Message me for a custom offer.
Get to know Sajid Ali
Sajid Ali
Senior Full Stack and AI Engineer for SaaS and custom apps
- FromPakistan
- Member sinceSep 2017
- Avg. response time1 hour
- Last delivery4 years
Languages
Urdu, Hindi, English
I build custom web apps, SaaS MVPs, and AI-powered features for startups, founders, and product teams.
Stack I work with day to day: React, Next.js, TypeScript, Node.js, Svelte/SvelteKit, APIs, and modern databases — plus AI integrations, agents, and RAG on your own data.
I focus on clear scope, clean architecture, and production-ready handoff. Prefer high-value builds over quick low-ticket work. Contact me before ordering so we can align on requirements, timeline, and package vs custom offer.
Based in Pakistan. Comfortable working with international clients in English.
Other AI Development Services I Offer
FAQ
What should I prepare before ordering?
Your documents or links, an idea of how many pages there are, 10 to 20 real questions users ask, and where the chatbot should appear. If your content is messy or very large, message me first so it can be scoped.
Is it really trained on my data?
It uses retrieval augmented generation (RAG). Your content is indexed and the most relevant passages are given to the model with each question, so answers come from your material, with citations. No expensive model retraining is needed.
Who pays for OpenAI or Anthropic usage?
You do, through your own API account. Vector database fees are also billed to you if you use a paid service. I will estimate typical monthly costs for your traffic and can use pgvector to avoid an extra subscription.
Do I own the code and data?
Yes. The code goes to your repository, and all data, embeddings and API keys stay in your accounts. Nothing is locked into a third party chatbot platform.
Where is it hosted?
On your infrastructure, usually Vercel, AWS or your existing server, with the database on your Postgres or vector service. I deploy it and document how to run and update it.
Can it be added to my existing website or app?
Yes. Each implementation is one place the assistant runs: a script widget for any website, a React component for React or Next.js apps, a hosted chat page, or an API your developers can call. Document Assistant includes 1, Embedded 2, Product Knowledge AI 3.
What counts as a revision vs new scope?
Each package includes tuning rounds after delivery: 1 on Document Assistant, 2 on Embedded Assistant, 3 on Product Knowledge AI. Tuning covers answers, prompts, styling and behaviour in scope. New data sources, integrations, languages or features are new scope, quoted separately.
Do you fix bugs after delivery?
Yes. Bugs in the delivered scope are fixed free for 14 days after delivery. Ongoing content updates or improvements are available by custom offer.
Can I get a custom offer for a larger project?
Yes. Large document sets, multiple integrations or enterprise privacy needs are handled through a custom offer with milestones, for example data pipeline first, then the assistant, then integrations.
How do we communicate and what is your timezone?
Through Fiverr messages with regular progress updates, and calls when useful. I am in Pakistan (UTC+5) and keep overlap hours with Europe and the US.
