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Computer Vision

Computer Vision & Document Intelligence

Document processing is where AI still pays for itself fastest, because the work being replaced is genuinely repetitive and the accuracy bar is a tired human at the end of a shift. We build extraction and vision systems that handle the messy reality — poor scans, regional-language forms, inconsistent layouts, handwriting — and that flag low-confidence output for review rather than pushing it silently into your database.

What We Deliver

Our Capabilities

Comprehensive Computer Vision capabilities backed by deep expertise and proven methodologies.

Intelligent document processing — invoices, purchase orders, contracts, forms and statements
Optical character recognition — printed and handwritten text, including Indian scripts
Structured extraction — documents to validated fields, with per-field confidence
Identity and KYC document handling — verification workflows with an audit trail
Image classification and object detection — inspection, sorting and condition assessment
Quality inspection — defect detection on production imagery
Video analysis — event detection and summarisation from recorded footage
Human review queues — low-confidence output routed to a person, and their corrections fed back
Accuracy measurement by document type — so you know exactly where the system is weak
Tech Stack

Technologies We Use

We leverage industry-leading tools and frameworks to build robust, scalable solutions.

PyTorch
OpenCV
YOLO
Amazon Textract
Amazon Rekognition
Google Document AI
Tesseract
PaddleOCR
Claude Vision
ONNX Runtime
FastAPI
Python
Our view

What we would tell you in the first meeting

Ask any vendor for accuracy on your worst documents, not their sample set. The average across clean scans tells you nothing about the 8% that will consume all of your operations team's time. That tail is the entire business case.

FAQ

Computer Vision — Frequently Asked Questions

How accurate is document extraction on real-world scans?+

Ask any vendor, including us, for accuracy on your worst documents rather than a clean sample. Averages across good scans hide the tail — the poor photocopies, the regional-language forms, the handwriting — and that tail is where your operations team will spend its time. We measure per document type and per field, and we report the weak spots rather than the headline.

What happens when the system is not confident?+

It routes to a person. Every extraction carries a per-field confidence score, and anything below the threshold you set goes to a review queue rather than silently into your database. Reviewer corrections feed back in, so the weak document types improve rather than staying weak.

Can you handle Indian languages and handwriting?+

Yes, with realistic expectations. Printed Indian-script documents work well. Handwriting varies enormously by form design and writer, so we evaluate on your actual documents before quoting an accuracy figure, and we design the review queue on the assumption that some proportion always needs human eyes.

Ready to Get Started with Computer Vision?

Tell us what you are trying to build and what is in your way. We will tell you how we would approach it — including when the answer is that you do not need us.

Talk to an engineer