Generic OCR extracts characters into a disordered string. Pluton's Vision-Language architecture extracts structured data while understanding hierarchy, tables, keys, values, and contextual nuances in Indian languages.
Drop-in REST API integration for Python, cURL, Node.js, and Android Kotlin with sub-second latency.
import requests
# Pluton Document Intelligence Indic VLM API
url = "https://api.plutontech.in/v1/ocr/indic"
headers = {"Authorization": "Bearer YOUR_API_KEY"}
with open("land_record_khasra.jpg", "rb") as doc_file:
response = requests.post(
url,
headers=headers,
files={"document": doc_file},
data={"preserve_layout": "true", "target_languages": ["hi", "en"]}
)
data = response.json()
print("Devanagari Confidence:", data["confidence_score"])
print("Structured JSON Output:", data["structured_data"])Estimate the cost and staff-hour savings by switching from manual processing or western cloud APIs to Pluton Document Intelligence.
Runs on-device via native C++ and OpenCV pipelines. Computes contour detection, affine homography transformation for deskewing, and CLAHE adaptive contrast normalization to eliminate glare and deep shadows.
Identifies document visual hierarchy: distinct tables, header blocks, stamp seals, signatures, key-value pairs, and line item grids using spatial attention maps.
Our fine-tuned vision-language transformer recognizes Devanagari Matras, half-characters, complex joint ligatures, and mixed-code Hinglish scripts with 99.4%+ character confidence.
Transforms extracted blocks into normalized JSON schemas (tax invoices, land records, KYC forms) and generates vector embeddings ready for LLM semantic search, automated accounting, and enterprise compliance.
Local on-device inference for basic offline scans, with high-concurrency cloud GPU clusters (H100/A100) handling massive enterprise batch jobs.
Evaluated across a benchmark dataset of 10,000+ authentic Indian tax invoices, handwritten land records, and degraded carbon copies.