Nanonets

If you're drowning in documents (and let's face it, who isn't?), you've probably realized that traditional OCR is like bringing a knife to a gunfight. Sure, it can read text, but it has no clue that the number sitting next to "Total Due" is probably more important than the one next to "Page 2 of…

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With the rapid advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs), many believe OCR has become obsolete. If LLMs can "see" and "read" documents, why not use them directly for text extraction? The answer lies in reliability. Can you always be a 100% sure of the veracity of text output that LLMs…

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"Let's just ensure that going forward, all the invoices are forwarded to Mr. X for validation before processing." If only invoice validation were that simple. In reality, it requires systematic checks and balances, not just one person's oversight. Studies show that 25% of invoice errors slip through accounts payable processes undetected despite internal correction…

The need for automation in the insurance industry is more pressing than ever. According to a recent study by Datos Insights, the insurance industry lags in terms of digitisation, with only 20% automation in underwriting and less than 3% automation in claims processing across sectors. This gap represents a significant opportunity for improvement and cost…

Introduction Large Language Models or LLMs, have been all the rage since the advent of ChatGPT in 2022. This is largely thanks to the success of the transformer architecture and availability of terabytes worth of text data over the internet. Despite their fame, LLMs are fundamentally limited to working only with texts. A VLM is…

In today's business world, data is everything. However, much of the data we need to make critical decisions is often trapped in PDF documents — invoices and expense reports to orders and delivery notes. The problem here is that PDFs are designed for viewing, not editing. It makes data manipulation a daunting task. PDFs store…

Data annotation is the process of labeling data available in video, text, or images. Labeled datasets are required for supervised machine learning so that machines can clearly understand the input patterns. In autonomous mobility, annotated datasets are essential for training self-driving vehicles to recognize and respond to road conditions, traffic signs, and potential hazards. In…