Multi-language OCR
90+ languages
// official site: github.com ↗
AI / LLM · PRO TIER
Surya OCRpro
Surya OCR is Datalab's modern document AI toolkit — multilingual OCR (90+ languages), layout analysis, reading order detection, and table recognition in one package. Significantly higher accuracy than Tesseract on real-world documents (magazines, forms, scanned photos).
// What it is
A closer look.
Surya OCR is Datalab's modern document AI toolkit — multilingual OCR (90+ languages), layout analysis, reading order detection, and table recognition in one package. Significantly higher accuracy than Tesseract on real-world documents (magazines, forms, scanned photos).
The 2024 generation of document AI, the canonical alternative to Tesseract for modern OCR workflows.
// Use cases
What it's for.
Concrete scenarios where teams pick Surya OCR over the SaaS alternative.
Layout analysis
section blocks (title, paragraph, table, figure)
Reading order detection
correct text flow on complex pages
Table recognition
extract structured tables
Form processing
extract key-value pairs
Document classification
by content type
// Who it's for
Built for these teams.
If your team profile matches one of these, Surya OCR is a strong fit out of the box.
Document AI teams
processing real-world inputs
Legal / contract platforms
OCRing scanned documents
Operula
digitizing artisan documentation, certificates
Invoice / receipt processing
workflows
Academic researchers
processing historical documents
Hosting providers
offering document AI tier
// Differentiators
Why teams pick Surya OCR.
When evaluating self-hosted options for this category, here are the dimensions on which Surya OCR consistently lands above the alternatives.
- ✓GPL-3.0 — fully open
- ✓Better than Tesseract — on modern documents (forms, magazines, screenshots)
- ✓Built-in layout + table — Tesseract requires plugins
- ✓90+ languages — broad coverage
- ✓Active maintenance — Datalab continuous improvements
- ✓Streamlit UI — included for non-technical users
- ✓API-friendly — for batch processing
// Integrations
Connects to.
The stack you'll plug Surya OCR into — services, protocols, and adjacent apps in the BluixApps catalog.
◇
Streamlit web UI
(BluixApps default launcher)
◈
Python API
for batch processing
◆
CLI mode
for command-line workflows
▣
Pair with
NLLB-200 (OCR → translate)
▦
Pair with
LLM (OCR → entity extraction → structured data)
▩
PDF + image
input formats
▼
Outputs
JSON, Markdown, CSV (for tables)
// Adoption & deployment
Notable users & community
- 10k+ GitHub stars
- Datalab + extensive contributor base
- Featured in document AI roundups as Tesseract successor
- Active research integration with modern LLM workflows
- Multiple commercial integrations
What we ship
- Docker (pytorch CUDA 12.4 + surya-ocr + streamlit + poppler-utils)
- Streamlit GUI launcher (
surya_gui) - Persistent volumes: cache (models, ~2 GB), input, output (JSON/MD/CSV)
- Port 7883 mapped
- Install report at
/root/bluixapps/surya.txt - Language guidance
- Pipeline stage documentation
- Surya vs Tesseract comparison
- Use case examples (legal, archives, invoices)
- Pairing suggestions (NLLB, LLM for entity extraction)
- GPU pre-flight check via
bluixapps_ensure_nvidia_runtime - Backup hook covers cache + output
// Tips & operations
Run it properly.
Operational guidance from running this in production — what to lock down, what surprises people.
// PERFORMANCE
Languages
// SECURITY
Speed
// OPERATIONS
VRAM
4 GB minimum
// RELIABILITY
Pipeline stages
// DEPLOYMENT
CLI batch
process entire folders
// SCALING
Best inputs
scanned PDFs, photos of documents, screenshots
// MAINTENANCE
Surya vs Tesseract
6144
// min ram (MB)
8
// min disk (GB)
7883
// access port
http
// protocol
pro
// bluixapps tier
// Alternatives in AI / LLM
Compare with
Project resources
Official sitegithub.com ↗