Humata AI
An AI document agent that answers questions across files and knowledge bases.
The challenge
Teams often store important knowledge inside long PDFs, reports, contracts, and technical documents, but finding the right answer takes too much time. Users needed a reliable AI agent that could understand uploaded files, search across document content, summarize key information, compare documents, and return clear answers with enough context to build trust.
What 13Floors built
13Floors designed and built an AI document-agent workflow with file upload, document parsing, chunking, embeddings, semantic retrieval, and LLM-powered answer generation. The agent was structured to understand user questions, retrieve the most relevant document sections, generate grounded responses, and support follow-up questions across multiple files. The interface focused on making document Q&A feel simple, fast, and trustworthy.
The value created
Humata AI helped users reduce document-reading time and turn large files into searchable knowledge. Instead of manually scanning pages, users could ask natural-language questions, receive AI-generated answers, compare files, and extract insights from their knowledge base through one conversational web app.
Technology
- React
- Next.js
- TypeScript
- Node.js
- OpenAI API
- LangChain
- RAG Pipeline
- Vector Search
- PDF Parsing
- Tailwind CSS