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I will build a chat with PDF and database ai assistant
Vikant Sharma
About this gig
Do you need an intelligent AI system that can read, extract, and accurately answer questions from your private documents? I will build a production-grade Document AI and RAG solution tailored to your files and business data.
Supported Document Formats:
- PDFs, scanned reports, and research papers
- Excel spreadsheets & CSV files
- Word documents (DOCX), Markdown, and TXT
- Knowledge bases (Notion, Google Drive, SQL dumps)
Technical Capabilities:
- Accurate Source Citations: Every answer references the exact page and source paragraph to prevent hallucinations.
- Vector Embeddings & Hybrid Search: Pinecone, Chroma DB, FAISS, or PGVector for fast semantic retrieval.
- LLM Integrations: OpenAI (GPT-4o), Anthropic Claude 3.5, or 100% private local models via Ollama (Llama 3, Mistral).
- Table & Structure Parsing: Accurately extracts numbers and financial tables without losing structure.
- Full-Stack UI: Clean, intuitive React frontend where you can drag-and-drop new files and chat in real-time.
Senior Full-Stack & AI engineer. Clean code with full documentation.
Please message me before placing an order to discuss your document formats and setup!
Get to know Vikant Sharma
Vikant Sharma
Full Stack Developer, Web and Mobile Apps, AI Driven
- FromIndia
- Member sinceAug 2020
- Avg. response time1 hour
Languages
Hindi, English
Hi! I am a Senior Full-Stack Engineer with 9+ years of experience building high-performance web, mobile, and AI solutions. I specialize in React, React Native, Node.js, and TypeScript, alongside modern AI integrations using LangChain, RAG pipelines, and OpenAI APIs. From complete MVPs and scalable architectures to bug fixes and automated workflows, I deliver clean, secure, and production-ready code fast. Reach out with your project requirements and let's get started!
My Portfolio
FAQ
How does the bot avoid hallucinations when reading my documents?
We implement strict Retrieval-Augmented Generation (RAG) guardrails. The AI is restricted to answering exclusively from the retrieved document chunks and includes precise citations (such as page numbers and document titles) for every fact it outputs.
Can the AI read complex tables, charts, or scanned PDFs?
Yes. For standard digital PDFs and spreadsheets (CSV/Excel), text and tabular structures are parsed directly. For scanned documents or image-heavy PDFs, we integrate OCR pipelines (such as Unstructured or Tesseract) to extract tables and text accurately.
Can this run completely offline without uploading my data to third parties?
Yes. If privacy or compliance is a priority, I can deploy the solution using local open-source LLMs (like Llama 3 or Mistral via Ollama) and a local vector database (like Chroma). Your documents never leave your server or local machine.
How do I add or update documents later?
In the Standard and Premium packages, the system is designed to dynamically ingest new files. You can drop new PDFs, CSVs, or text files into an upload directory or frontend interface, and the pipeline automatically chunks, embeds, and updates the vector database.
