A data layer for AI, not just a converter
Clean conversion is the start. LLMtoMD turns your documents into searchable, structured, AI-ready knowledge your models can actually use.
Layout-aware conversion
PDFs, Office docs, images, audio, video, and websites become clean, structured Markdown — tables, headings, and reading order preserved.
Semantic search
Every converted document is chunked and embedded, so you can search your knowledge by meaning and retrieve the right passage — not just keyword matches.
Document Q&A
Ask questions in natural language and get cited answers drawn from your own documents, with the source passages attached.
Automatic enrichment
Each document gets a summary, topics, entities, and a detected type — semantic metadata you can filter, route, and build on.
Structured extraction
Pull named fields out of any document with reusable schemas, and auto-extract on conversion when a document matches a schema you've defined.
Knowledge graph
Entities found across your documents are linked into a graph, so you can see how people, organizations, and topics connect.
RAG-ready export
Export any document as chunked JSONL with embeddings — a drop-in for vector databases, LangChain, and LlamaIndex.
Automated ingestion
Push documents via the API or point a watched source at a storage prefix, and new files convert and index themselves.
Convert anything to AI-ready Markdown
PDFs, Office docs, images, audio, and whole websites — clean Markdown and RAG-ready exports for your LLM, in seconds.