Evolution AI

www.evolution.ai

Enterprises worldwide spend over $40Bn annually on manually extracting data from documents. This extraordinary sum represents hundreds of millions of human hours spent on tedious, grinding, soul-crushing work which is also slow and prone to errors. The incumbent technology, OCR (optical character recognition) has been around for decades. It’s simplistic, rule-based and performs poorly on many real-life documents. We founded Evolution AI in 2015 to solve that problem. Evolution AI revolutionised data extraction by building a deep-learning machine that closely mimics how humans read documents. Humans not only read characters off the page, we heavily rely on visual cues from graphic design (tables, font types and sizes, colours, bold/italic etc) and of course - on meaning and context. In AI terms, these translate to Visual Reasoning - a branch of computer vision that focuses on how objects visually relate to each other - and NLP (Natural Language Processing), dealing with meaning and semantics. In short, our AI weaves together text, vision and semantics to extract data from documents - just like humans do. Today we process over 1.5M pages per day for our clients. Our unique scientific approach enables us to automatically extract data from any type of document including the most complicated such as quarterly reports, balance sheets, P&L statements, account statements, invoices etc.

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Enterprises worldwide spend over $40Bn annually on manually extracting data from documents. This extraordinary sum represents hundreds of millions of human hours spent on tedious, grinding, soul-crushing work which is also slow and prone to errors. The incumbent technology, OCR (optical character recognition) has been around for decades. It’s simplistic, rule-based and performs poorly on many real-life documents. We founded Evolution AI in 2015 to solve that problem. Evolution AI revolutionised data extraction by building a deep-learning machine that closely mimics how humans read documents. Humans not only read characters off the page, we heavily rely on visual cues from graphic design (tables, font types and sizes, colours, bold/italic etc) and of course - on meaning and context. In AI terms, these translate to Visual Reasoning - a branch of computer vision that focuses on how objects visually relate to each other - and NLP (Natural Language Processing), dealing with meaning and semantics. In short, our AI weaves together text, vision and semantics to extract data from documents - just like humans do. Today we process over 1.5M pages per day for our clients. Our unique scientific approach enables us to automatically extract data from any type of document including the most complicated such as quarterly reports, balance sheets, P&L statements, account statements, invoices etc.

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City (Headquarters)

London

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Employees

11-50

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Founded

2015

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Estimated Revenue

$1,000,000 to $5,000,000

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Potential Decision Makers

  • Chief Technology Officer

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  • Director of Operations

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  • Head of Business Development

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  • Software Engineer

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