News Report Technology
March 12, 2024

Nanonets Raises $29 Million Funding to Ease Workflow Automation with AI Agents

In Brief

Nanonets raised $29 million funding to enhance its AI workflow automation system’s accuracy and facilitate team expansion.

Nanonets Raises $29 Million in Funding to Advance AI Workflow Automation

AI-based workflow automation platform Nanonets raised $29 million in an all-equity Series B funding round led by Accel, alongside existing investors Elevation Capital and YCombinator, among others. This brings Nanonets’ total funding to $42 million, including its $10 million Series A round in 2022. The newly raised capital will be directed towards research and development to improve system accuracy and facilitate team expansion.

The startup has developed an AI platform providing no-code solutions designed to assist businesses in extracting information from various sources such as documents, emails, tickets, and databases and transforming it into actionable insights. Utilizing machine learning architectures, the company’s AI platform analyzes unstructured data from uploaded documents to extract valuable information.

“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. We are taking the most repetitive and mundane office work and automating it,” said Sarthak Jain, CEO and co-founder of Nanonets.

However, Nanonets’ key innovation lies in its capacity to ensure Straight Through Processing (STP), indicating the percentage of data processed without requiring any manual intervention. This comes as a notable achievement as many generative large language models (LLMs) encounter challenges with STP due to data hallucinations, hindering the broad adoption of autonomous agents for end-to-end tasks. Notably, by handling millions of documents monthly, Nanonets achieves a superior STP rate of over 90%, resulting in notable gains in productivity and cost efficiency.

The company’s autonomous agents demonstrate proficiency in completing tasks end-to-end, and their models quickly adapt to new information, eliminating the necessity for intricate training processes. Furthermore, these agents can be integrated into ERP platforms, including QuickBooks, Xero, Sage, and NetSuite, to automate accounts payable processes. Additionally, they can optimize supply chains by utilizing historical data from Square and Tableau and summarize health reports from patient management systems.

Nanonets Elevates Landscape of AI-based Workflow Automation

Founded in 2017, Nanonets provides intelligent automation solutions that transform business operations across various sectors. Through its no-code platform and adaptable decision engines, Nanonets empowers organizations to expedite decision-making processes and attain unparalleled efficiency. The company serves over 10,000 customers worldwide.

Operating in a competitive global market for AI-based workflow automation, the company currently faces competition from traditional optical character recognition (OCR) platforms and emerging startups like Rossum AI and Hyperscience. Larger players like automation software company UiPath also provide workflow automation, albeit with a focus on structured data.

With the new investment, Nanonets is set to enhance its capabilities, further solidifying its position as a leading provider in the competitive market of AI-based workflow automation.

Disclaimer

In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.

About The Author

Alisa is a reporter for the Metaverse Post. She focuses on investments, AI, metaverse, and everything related to Web3. Alisa has a degree in Business of Art and expertise in Art & Tech. She has developed her passion for journalism through writing for VCs, notable crypto projects, and scientific writing. You can contact her at alisa@mpost.io

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Alisa Davidson
Alisa Davidson

Alisa is a reporter for the Metaverse Post. She focuses on investments, AI, metaverse, and everything related to Web3. Alisa has a degree in Business of Art and expertise in Art & Tech. She has developed her passion for journalism through writing for VCs, notable crypto projects, and scientific writing. You can contact her at alisa@mpost.io

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