Xberg

Xberg is a full content intelligence engine that extracts text, tables, entities, and embeddings from over 100 formats.

Xberg is a full content intelligence engine designed to process documents, URLs, code, images, audio, and archives through a single API. It extracts clean Markdown, entities, code structure, and embeddings without requiring multiple stitching libraries. The platform handles 107 formats including PDFs, Office files, images, email, e-books, and academic papers, alongside code intelligence for 371 languages. It features automatic OCR for scanned pages, Whisper transcription for audio and video, web crawling capabilities, and recursive extraction from nested archives. Users can pull structured JSON matching specific schemas using local or hosted LLMs without prompt engineering. It offers native bindings and packages for multiple languages including Python, TypeScript, Rust, Go, Java, C#, Ruby, PHP, and Elixir, alongside a CLI, REST API, MCP server, Docker, and WASM support.

Xberg at a glance

Best for: Software engineer
Runs on: Web, API, CLI, Docker, self-hosted, open source
Pricing: Free
Released: January 2025
Category: AI productivity tool
Website: docs.xberg.io

Key features

Extract text and tables from 107 formats
Transcribe audio and video tracks with Whisper
Perform automatic OCR on scanned pages
Crawl and fetch web pages via http(s)
Extract files recursively from nested archives
Generate structured JSON matching schemas via LLMs
Analyze code structure across 371 languages
Generate embeddings for search and RAG

Use it for

Convert various document formats into clean Markdown
Transcribe audio and video files automatically
Extract structured JSON data from unstructured documents
Crawl web pages and extract content
Analyze and extract symbols from source code

Alternatives to Xberg

Docling — Provides advanced PDF understanding and local execution for sensitive data.
Sparrow — Extracts structured data locally from documents without cloud dependencies.
NuMind — Achieves high accuracy in document extraction and outperforms generalist models.
MinerU — Parses complex documents and tables into structured markdown for agents.
PDF Inspector — Detects if a PDF is scanned or text-based to avoid unnecessary OCR costs.
IWE — Works natively across Mac apps, text editors, terminal CLI, and MCP servers.
Chandra — Provides precise document parsing with bounding box data for complex layouts.
Pagesift — Extracts web data with high memory efficiency and speed for AI agents.
Hyper-Extract — Extracts complex knowledge graphs and hypergraphs from documents with one command.
Jina — It provides reliable reader and search APIs optimized for LLMs and RAG systems.
Basic Memory — Stores data in local Markdown files that remain accessible and readable by any AI.
Knowhere — It preserves page-native structures and source links for accurate agent retrieval.

All Xberg alternatives