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Fiverr Pro
English
$
USD
I will build ai document chat, ocr, rag, vector database and document processing backen
Adriana Laura
About this gig
Need a reliable backend architecture for an AI document chat system?
What I can build
- PDF and document ingestion pipeline
- OCR for scanned documents and image-based PDFs
- Text extraction and document preprocessing
- Chunking and metadata extraction
- Embeddings and vector database integration
- RAG (Retrieval-Augmented Generation) architecture
- AI document chat / question answering
- Source citations and page references
- Document upload and processing workflow
- Semantic and hybrid search
- Document classification and metadata handling
- API/backend architecture
- Error handling and processing validation
- Cost estimation per 1,000 pages
- Scalability recommendations
- Testing strategy for difficult scanned documents
I can design around issues such as:
- Low-resolution scans
- Skewed or rotated pages
- Blurry documents
- Multi-column layouts
- Tables and complex formatting
- Handwritten content
- Images containing important text
- Mixed scanned and digital PDFs
Send me your document types, expected page volume, and preferred technology stack, and I will help map out the backend pipeline.
Get to know Adriana Laura
Adriana Laura
Your AI System Built Right From Day One
- FromBrazil
- Member sinceSep 2026
- Avg. response time1 hour
Languages
English, Portuguese
I build smart AI assistants, AI agents, and automation systems that help businesses save time and get more done. I work with Hermes Agent, JARVIS-style assistants, Obsidian, AI dashboards, n8n, APIs, and custom workflows. My goal is simple: turn your idea into a working AI system that is easy to use and can grow with your business. I focus on clean setups, reliable automation, and solutions built around your real needs.
FAQ
Can you build a chatbot that answers questions from my PDF documents?
Yes. I can build a document-chat system where users upload PDFs and ask questions, with answers generated from the document content.
What if my PDFs are scanned and have no selectable text?
I can add an OCR pipeline to extract text from scanned and image-based PDFs before processing them for AI search and chat.
My AI chatbot gives answers that are not actually in my documents. Can you fix this?
Yes. I can design a RAG pipeline with better document chunking, retrieval, metadata, and source grounding to reduce unsupported answers.
Can the chatbot show me where an answer came from?
Yes. The system can return source information such as the document name, page number, section, or retrieved text alongside the answer.
I have thousands of documents. Can they all be searchable with AI?
Yes. I can design a scalable ingestion, embedding, and vector-search architecture for large document collections.
My scanned documents contain tables, columns, or unusual layouts. Will OCR still work?
These layouts can cause extraction problems. I can design preprocessing and validation steps to handle common OCR failure points and improve the quality of extracted content.
