AI for Workflow Automation
Updated: March 16, 2021
2021. DeepSee.ai raises $22.6M for its AI-centric process automation platform
DeepSee.ai, a startup that helps enterprises use AI to automate line-of-business problems, has raised a $22.6 million Series A funding. The company argues that it offers enterprises a different take on process automation. The industry buzzword these days is “robotic process automation,” but DeepSee.ai argues that what it does “knowledge process automation” (KPA). But the company also argues that today’s bots focus on basic task automation that doesn’t offer the kind of deeper insights that sophisticated machine learning models can bring to the table. The company also stresses that it doesn’t aim to replace knowledge workers but helps them leverage AI to turn into actionable insights the plethora of data that businesses now collect.
2020. Salesforce applies AI to workflow with Einstein Automate
Salesforce announced Einstein Automate, a new AI-fueled set of workflow solutions. Einstein is the commercial name given to Salesforce’s artificial intelligence platform that touches every aspect of the company’s product line, bringing automation to many tasks and making it easier to find the most valuable information on customers, which is often buried in an avalanche of data. Salesforce is also bringing into the mix MuleSoft, the integration company it bought for $6.5 billion in 2018. Instead of processes like a mortgage approval workflow, the MuleSoft piece lets IT build complex integrations between applications across the enterprise and the Salesforce family of products more easily.
2020. Hypatos gets $11.8M for a deep learning approach to document processing
The Germany and Poland-based process automation startup Hypatos has raised a $11.8M seed round. Hypatos is applying language processing AI and computer vision tech to speed up financial document processing for business use cases such as invoices, travel and expense management, loan application validation and insurance claims handling via — touting a training data set of more than 10 million annotated data entities. Hypatos says its use of deep learning tech supports an “in-depth understanding” of document content — which in turn allows it to offer customers a “soup to nuts” automation menu that covers document classification, information capturing, content validation and data enrichment.