In a recent significant funding round led by Accel India, Nanonets, a company utilizing AI for implementing back-office strategies, secured $29 million. The primary objective is to enhance the reliability of technological processes dealing with extensive unstructured data.
The processing of unstructured data from documents like receipts and invoices often involves labor-intensive tasks and significant manpower. Nanonets, focusing on the financial services sector, asserts that its AI system is designed to enhance the efficiency of these processes and cut down on expenses.
As a Y Combinator alumnus, Nanonets has created an AI platform that provides no-code solutions to help businesses extract insights from various sources such as documents, emails, tickets, and databases. The AI system of the company analyzes unstructured data from documents and utilizes machine learning frameworks to extract relevant information. These no-code AI agents can be seamlessly integrated into ERP systems like QuickBooks, Xero, Sage, and NetSuite to streamline accounts receivable processes, enhance supply chains, leverage historical data from Tableau, and generate comprehensive reports from individual control systems.
Nanonets claims that while manually processing an invoice typically takes 15 minutes, their automated financial solutions can accomplish the task in less than a minute. These solutions find applications in activities like account reconciliation, accounts receivable, and expense management.
The company plans to allocate the new funding towards sales and marketing initiatives, alongside enhancing research and development efforts to bolster system accuracy. With a workforce of approximately 100 employees, predominantly comprising members of its Indian executive team, Nanonets aims to optimize its operations using the fresh capital.
Elevation Capital and Y Combinator, existing investors of Nanonets, participated in the all-equity Series B round, elevating the company’s total funding, including the \(10 million Series A round in 2022, to \)42 million.
Initially leveraging Convolutional Neural Networks for image analysis and object identification, Nanonets later transitioned to transformers and bidirectional architectures for improved accuracy compared to conventional machine learning methods. Co-founder and CTO Prathamesh Juvatkar mentioned the evolution of their models based on customer data to enhance accuracy with each new client introduction.
Founded by IIT Gandhinagar alumni Juvatkar and CEO Sarthak Jain, Nanonets prioritizes transformers over traditional AI models to mitigate hallucinations, a common issue in AI systems generating information not present in the source documents. Despite the prevalence of document-agnostic machine learning architectures, Nanonets focuses on the financial services sector due to its substantial customer base in that industry. Moreover, the company is expanding its services to clients in manufacturing and healthcare sectors.
In the AI-based workflow automation market, Nanonets competes with traditional OCR platforms and startups like Rossum AI and Hyperscience, as well as larger enterprises like UiPath offering structured data processing solutions. Nanonets differentiates itself by achieving a 90% straight-through processing rate, indicating the percentage of data processed without human intervention, which contributes to winning deals based on accuracy, customer experience, and interface quality.
Nanonets offers three pricing tiers – Starter, Pro, and Enterprise – with Pro and Enterprise tiers being the primary contributors to monthly recurring revenue. Additionally, the company provides tools for image to text conversion, CSV, JSON, XML and text conversion, and image to text conversion, catering to over 34% of Fortune 500 companies globally. With a fourfold increase in its customer base over the past year, Nanonets currently serves over 10,000 clients worldwide.
While Nanonets serves a global user base, the United States contributes around 40% of its revenues, with Europe accounting for 30% to 35%. Despite not disclosing specific figures, Juvatkar mentioned a consistent threefold annual revenue growth since the 2022 round, with plans to double or triple the bottom line this time.
Despite a global decline in investments, AI startups continue to attract funding due to their consistent revenue growth. Nanonets aims to capitalize on this trend to further expand its operations and enhance its financial performance.
