We’re thrilled to announce that with this new year comes a new chapter for Nanonets: we’ve raised $10 million in our Series A funding round!
Our Series A is unique. Along with Elevation Capital, it’s led by some of the biggest leaders in the future of cloud-based SaaS — including Nakul Aggarwal and Ritesh Arora (Co-founders, BrowserStack), Ashish Gupta (Co-founder, Helion), Amar Goel (Founder & Chairman, PubMatic), Vetri Vellore (Founder and CEO, Ally), Krish Subramanian and Rajaraman Santhanam (Co-founders, Chargebee Inc.), Vara Kumar Namburu and Khadim Batti (Co-founders, Whatfix) and Gautam Kumar and Kushal Nahata (Co-founders, FarEye).
Over the last two years, hundreds of companies have started using Nanonets to manage documents, capture information and simplify communication. Our software has helped tens of thousands of new users build workflows, develop hundreds of thousands of AI workflows, and process a few billion files. Nanonets is on a mission to leverage Deep Learning to build the world's most frictionless document communication platform.
Now that you’ve seen our vision, what is Nanonets doing to bring that vision to life? To get there, Nanonets has relentlessly focused on building the best deep learning technology. Here’s an overview of some of the recent activity in each of these areas.
Paradigm Shifts for Knowledge Work in 2019 and 2023
In 2019 Deep Learning reached an inflection point which made the Nanonets technology possible. We could take any document and extract the information of interest from it even if we had never seen it before. This was made possible by the number of parameters that could be added to a Deep Learning model.
In 2023 we will reach another inflection point, where Deep Learning models will have more parameters than the human brain. This doesn’t mean “conscious machines”. It means we will have computers capable of learning and mimicking any complex cognitive process a person can.
Change in Business Processes - Learning from People
With the change in what Deep Learning is capable of, we will see more and more business processes automated with machines. Processes like AP Automation, Expense Management, Contract Lifecycle Management, Claims Management etc. will be hyper automated with most of the redundant repetitive tasks moved to Computers. The primary role of the people involved in these processes will be supervision, they will become 10x more productive and will spend less time on tasks like data entry and verification and more time on complex business decisions and strategy. These people will move from doing grunt work to strategic execution and process management.
Rapid acceleration due to Covid
Businesses have become even faster to adopt process automation due to the changing nature of businesses themselves when going remote. It’s much easier to do process supervision with AI than working with distributed teams. Automation has been a key backbone in keeping business running with reduced staff, remote work and digital coordination.
The new Role of AI Process Manager
An entire job function will be created of AI Process Manager whose sole responsibility will be to manage AI exceptions, keep the system trained, ensure veracity of training data and AI performance. There will be very limited to no job displacement since the existing skill set of process understanding will be the same needed for AI management. The fundamental change will be in the amount of work that can be done by a person increasing 10 fold. To make this transition smoother we are launching a dedicated academy for knowledge workers to upskill themselves to become AI Process Managers through webinars, courses and education material. Along with this we are also launching a series showcasing how businesses are adopting AI driven process automation to automate manual and repetitive tasks.
The AI Business Process Management Platforms
We foresee a new set of utilities emerging which are at the heart of AI process management that is the go to tool of the knowledge worker in the late 2020s. This will replace tools like spreadsheets that have been used for performing most of the job, and change to people defining and managing AI workflows using these tools. We believe Nanonets to be a front runner in creating this entirely new category of platforms. Which will move from databases used to store data for processes to AI that manages these processes end to end.
Lowering the barrier to entry to AI-automation
Nanonets lowers the barrier to deploy AI for workflow and business automation for everyone, anywhere. Using Nanonets means you can get the world’s best Deep Learning team working for your company without having to hire them. Typically creating a Machine Learning model that’s custom to your business needs requires many months, millions of data points and the world's best talent. We have taken that process and condensed it into a simple workflow of just uploading your data and automatically getting a best in class Deep Learning model spit out by the system in a matter of minutes. This reduces the cost of hiring, onboarding and retaining top talent.
Build the Future of Work!
We couldn’t be more excited to continue building a better Nanonets product for you and your team. While improving the most used business app is no small feat, our Series A funding will propel us to move faster.
We are so grateful for the continued support of our customers, investors, family, and friends — and we look forward to helping teams around the world work happier. Be sure to follow along with all the latest Nanonets updates on our Changelog and Blog!
Have questions? Reach out to us on info@nanonets.com or Speak with us!
