Astra extracts structure, text, tables, charts, maps, images, and language from messy documents — then turns them into JSON, XML, Markdown, and searchable context for AI applications.
Real enterprise documents are visual, multilingual, structured, and messy. Plain text extraction loses the information AI systems actually need.
Columns, titles, captions, footnotes, figures, and sections get flattened into text.
Multi-column pages and mixed layouts are read in the wrong sequence.
Rows, columns, merged cells, and headers lose structure.
Charts, maps, figures, and images are ignored or reduced to empty placeholders.
Mixed languages, scripts, diacritics, handwriting & low-quality scans create OCR errors.
One-shot outputs leave teams with no way to review, correct/ apply changes across documents.
Astra preserves what matters: layout, hierarchy, reading order, tables, visual elements, language, and source grounding.
Astra combines visual parsing, multilingual extraction, structured outputs, and review workflows in one system.
Detects titles, paragraphs, lists, tables, figures, charts, maps, images, and document regions.
Preserves headings, sections, captions, references, footnotes, and semantic grouping.
Reconstructs reading paths across columns, mixed layouts, RTL scripts, and dense pages.
Extracts text at line and region level with coordinates, confidence, and language labels.
Identifies languages at region or line level across multilingual pages.
Handles Indic, Arabic-script, Latin, CJK, and other language packs with routing and review.
Extracts table structure, cells, rows, columns, Markdown, JSON, and descriptions.
Describes trends, axes, labels, regions, and visible data in English.
Generates grounded descriptions and links them back to source regions.
Exports machine-friendly outputs with source locations and confidence.
Creates searchable context with hierarchy, citations, and metadata.
Lets humans or agents correct text, labels, blocks, tables, and structure before export.
Astra supports Indian and global language packs, with script-aware extraction, language ID, and review workflows for mixed-language pages.
Click any block, cell, line, or description to see where it came from. Review, correct, and apply fixes across the document set.
Astra prepares documents for AI applications that search, answer, cite, summarize, route, and act.
Monitor extraction quality, route low-confidence blocks to review, manage language packs, track cost, and feed clean context into AI applications.
Astra is built for teams that need structure, traceability, and multilingual understanding — not just OCR text.
Administrative files, archives, forms, maps, reports, and multilingual records.
Contracts, statements, filings, court documents, compliance records, and evidence packs.
Forms, reports, claims documents, patient instructions, and scanned records with review controls.
POs, invoices, vendor files, tables, charts, and process documents for downstream workflows.
Books, manuscripts, learning materials, newspapers, and archives into searchable structured formats.
Internal documents, presentations, reports, and knowledge bases for RAG and agentic workflows.
Run document intelligence through a workspace, integrate it into your product, or deploy it inside your enterprise environment.
Upload, review, correct, and export document sets through a visual interface.
Send files, receive structured outputs, and integrate extraction into your application.
Run in Zangoh Cloud, private VPC, or on-prem for high-control environments.
Astra is designed for multilingual, layout-heavy, visually rich, and low-quality documents where simple OCR fails.
Layout detection, OCR accuracy, table structure, semantic description, & language ID.
Skewed, noisy, blurred, rotated, scanned, mixed-script, and dense layouts.
JSON, XML, Markdown, tables, descriptions, language labels, and coordinates.
We'll extract, structure, review, and make it ready for search, RAG, or production AI workflows.