Image credits: Re:Infer
UiPath, a Romania-founded and currently New York-based Robotic Process Automation company, announced on Monday that it has acquired Re:infer, a London-based Natural Language Processing (NLP) company.
Founded in 2015 by Ph.D. scientists from the AI research lab at University College London, Re:infer uses Machine Language (ML) technology to mine context from communication messages and transform them into actionable data.
Re:infer: What you need to know
Over 80 per cent of enterprise data, stored in various forms like emails, documents, and chat logs to social messages, is unstructured. Organisations must address these communication forms as they are the primary means their customers use to engage with them.
Every customer conversation contains valuable information about the customer’s preferences and needs, and the organisation’s products, services, and processes.
The London-based company allows users to deploy custom machine learning models to analyse documents and communications data generated by a business.
The company’s no-code interface allows business users to train their AI models for greater specificity and flexibility. In addition, the self-learning capability improves model accuracy in identifying bottlenecks and inefficiencies.
The company says its solution is used by the organisation across various industries such as banking, insurance, and e-commerce.
“Automating the interpretation of documents and communications data bridges the gap between humans and information technology systems, and structured and unstructured data to supercharge digital transformation efforts in the enterprise,” says Dr. Ed Challis, CEO and Co-Founder of Re:infer.
“We have spent the last seven years building an innovative technology and believe UiPath will take us to another level. We couldn’t be more excited to access UiPath’s power of scale and introduce Re:infer to a new global audience. We’re joining the leader in enterprise automation, and it’s an incredible day for us,” he adds.
How does the Re:infer acquisition benefit UiPath?
Re:infer’s NLP model, combined with the UiPath’s Automation platform, will enable developers to build automation that optimises the customer experience (CX) and operational scalability of contact centres.
Developers can also enhance existing automation that works with an email to make them smarter with Re:infer.
Re:infer’s product capabilities are available to UiPath customers in private preview, says the company.
“Automation and AI are a powerful and natural pair that together empower the vision of the fully automated enterprise,” says Ted Kummert, Executive Vice President, Products & Engineering at UiPath.
He adds, “Our customers are awash in documents, communications, and data that they need to understand the meaning of and process efficiently. Combining Re:infer’s NLP technology with our Document Understanding and AI products expands the breadth of our current AI-powered automation capabilities and unlocks new automation opportunities for our customers.”
UiPath: What you need to know
UiPath was founded in 2005 as a 10-people team based in Bucharest, Romania, led by Daniel Dines. Initially, it outsourced automation libraries and software to some of the world’s biggest companies.
The company is on a mission to unlock human creativity and ingenuity by enabling a fully automated enterprise and empowering workers through automation.
The company designs and develops robotic process automation software. It offers foolproof development tools, automation of intricate processes, enhanced control, cloud and on-premise deployment, robust governance, and multiple robots on a single virtual machine.
The company moved its headquarters to New York in 2017 to be closer to its international customer base.
Currently based in New York, the company claims its Automation Platform is designed to transform how humans work, providing customers with a vast set of capabilities to discover automation opportunities and build, manage, run, engage, measure, and govern automation across departments within an organisation.
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