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nRoad, a Boston-based AI startup that abstracts and incorporates unstructured data into important business tasks, today launched a new platform called Converse – aimed at helping enterprises meet the challenges of unstructured data. In the enterprise ecosystem, employees are building a bottomless data lake, based on the corporate mantra, “Save everything, just in case,” according to an article published in Gartner. Alan Dale, Gartner’s former director of research, notes that the rise in data growth over the past decade has created an unstructured data nightmare. “It’s not just the cost of storing it. The huge amount of dark data makes it difficult to find useful and could mean we lose business opportunities, “says Daly.
Mike Gualteri, Forrester’s VP and chief analyst, notes in an article that between 60% and 73% of all data within an enterprise goes unusable for analysis. Gartner predicted that by 2021, more than 80% of organizations would fail to develop a unified data security policy across Silo, leading to potential non-compliance, security and financial liability. As organizations seek to create strategies to meet the growing Unstructured Data Challenge, nRoad says its new platform is built and trained on long-form, highly unstructured documents and content. nRoad says that designed to be form- and format-agnostic, Convus is powered by a set of modularized engines that are API-powered.
Drilled into the complexities of the platform via email interview with Ashish Mehta, CEO of nRoad, for a broader reference on the VentureBeat platform and how it affects enterprise data infrastructure.
Eliminate the need to train and process unstructured data separately
According to Mehta, nRoad’s new platform eliminates the need to train and process various unstructured data separately, offering a single interface (API) to perform any downstream tasks. This allows enterprise technology teams to get rid of widely available template-based solutions.
Mehta said Convus ™ in conjunction with Classical ML algorithms and the NLP layer, uses new vision-based and other deep learning algorithms that take advantage of the publicly available Transformer Language models. Mehta claims that the platform has the ability to incorporate domain knowledge using differential factor, graph techniques and domain-specific language models which enables it to maintain the semantic similarity of domain context, relationship and data.
“Fundamental shortcomings in general approaches to solving unstructured data problems, such as RPA, OCR software, and cloud-based solutions, lack of consideration in the limitations of input variability, content variability, language and localization,” Mehta said.
He added that the founding team of nRoad has also developed a unique but standardized and intermediate presentation of the entire document – thus enabling faster deployment of downstream models for data reusability and new use cases.
n Road wants to act as a non-intrusive input source of unstructured data in structured format, Mehta said. Convus is designed to handle volume, velocity, variability and variety, he added. nRoad believes that enterprise CTOs and CDOs can take advantage of its platform’s domain-based training capabilities to better reference data.
The company says its AI-powered Convus ™ platform is 2.8 seconds faster than popular cloud solutions, has 90% extraction accuracy and, to date, has produced more than ten million domain-specific terms.
Unstructured data opens up significant market opportunities
Mehta noted that many enterprises have invested huge resources in their business process management (BPM) and other tools over the past decade to automate structured content. However, even with this investment, unstructured content processing is still a major challenge and there is a significant limitation in their quest to achieve true digital transformation and hyperotomation. Given that unstructured content represents the bulk of the total content generated today, Mehta said it represents a significant opportunity for nRoad.
n Road addresses the major challenge of automating unstructured content processing. Mehta said, “For example, if a large financial institution receives approximately 50 million documents each year, each time the workflow process encounters any unstructured content, the process becomes manual and suffers from all sorts of inefficiencies.” Mehta said. “Our platform helps automate the processing of these documents by extracting key variables and the insights gained. These variables can then be fed into the workflow to ensure a friction-free process that does not create any dark data.
Variations of overall players nRoad in the industry
According to Mehta, there are three main types of players in the industry:
- Cloud-based, horizontal platform providers that focus on providing enterprise tools to address unstructured content processing needs.
- Players focused on providing a work-specific solution, such as a document or mortgage documents.
- Business Process Outsourcing (BPO) companies focused on processing documents as part of their outsourced services using tools and manual efforts.
He said the uniqueness of nRoad lies in its ability to provide fully automated and measurable solutions that can stay behind the enterprise’s firewall. He added that nRoad also enables small and medium-sized enterprises (SMEs) to interact with processed data to gain more intelligence.
While Mehta agreed that nRoad has competition among all three players, he said that nRoad’s solution provides a unique and low-risk opportunity for the enterprise to address unstructured content processing needs without losing control over their workflow, unlike any other in the industry.
“Our platform can process super-text-heavy documents to generate insights like private credits, ESG reports and PPMs, and this sets us apart from many players in the industry,” he said.
In its press release, nRoad claims that its Convus ™ platform currently serves the financial services industry, and has proven its capabilities to some of the largest fintech players, asset management firms and financial data providers globally.
Expected next milestones
nRoad envisages more use of NLP techniques, graph techniques, machine understanding and new vision-based techniques to handle complex business use cases.
nRoad was established in 2020 and has a current number of 35, but the company expects to double that number to accelerate its revenue growth and implementation of its production roadmap.
While Mehta did not comment on the exact number of customers of nRoad services, he said the company has grown by 175% in 2021 in terms of customer growth.
n Road has so far been self-funded, but the company will launch a funding round in the coming months, claiming that its customers and some VC partners have shown interest in investing in the company.
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