The funding round saw participation from existing investors Elevation Capital, YCombinator, and others.
Nanonets, an AI-based workflow automation platform, raised $29 million in a Series B funding round led by Accel. The funding round saw participation from existing investors Elevation Capital, YCombinator, and others. This takes the total funding raised to date to $40 million.
Over the last 2 years, Nanonets has seen extensive growth in their customer base, with over 34 per cent of the Global Fortune 500 companies having used their AI-based workflow automation platform across finance, accounting, operations, and several other business use-cases. Their user base has grown fourfold in the last 12 months, reads a company statement. Nanonets had earlier raised $10 million in a Series A investment round in 2022, led by Elevation Capital.
"The internet was going to kill paper, but businesses today are producing more documents than ever, just in new forms. Email, PDF contracts, whitepapers, etc. There are millions of highly skilled professionals stuck looking for needles in haystacks and entering this data from these documents into different software. Nanonets uses cutting-edge AI to automate these different processes,” said Sarthak Jain, CEO and co-founder of Nanonets.
A majority of Nanonets’ revenue comes from automating finance processes such as accounts payable, reconciliation, etc. A typical invoice takes 15 minutes to process manually, with processes such as entering an invoice into the ERP, matching against the purchase order, and a GL-code lookup followed by approvals. Nanonets brings this down to under a minute.
Nanonets’ primary innovation is their ability to guarantee Straight Through Processing (STP), the percentage of data processed without any manual intervention, as per a company statement. Other generative LLMs tend to struggle with STP due to data hallucinations, hindering the large-scale adoption of autonomous agents for end-to-end tasks.
The Turing test has evolved from humans being unable to differentiate an AI in conversation to humans being unable to differentiate an AI in performing tasks. Nanonets' autonomous agents excel at performing tasks end-to-end. Additionally, their models learn instantly from new information, eliminating the need for complex training, according to the company statement.