Yseop, the world-leading AI software company and pioneer in Natural Language Generation (NLG), today announced the launch of Augmented Analyst, a new enterprise-wide NLG automated report generation platform. Augmented Analyst is designed to help financial companies accelerate their digital transformation.
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Stemming from the imperative to move away from high-cost individual point solutions, Yseop leveraged over 10 years of experience in the field and invested into an important R&D program, working closely with industry leaders such as Sanofi, Moody’s and BNP Paribas to develop its Augmented Analyst platform.
Built on a unique synergy of advanced AI technologies, Augmented Analyst relies on a powerful industry-leading patented NLG engine and extended NLU and Machine Learning capabilities, to draw insight from structured data, translating them into clearly written reporting narratives. The technology is praised by end-users for the high quality of the human-like language output.
With a short learning curve and deployments reduced to weeks, rather than months, Augmented Analyst provides a new opportunity for enterprises to fast-track first NLG use case implementations. This is significantly reducing the time and cost of repetitive reporting tasks, with an immediate impact on the bottom line. The platform, scalable by design, can then seamlessly be extended to streamline from 1 to dozens of the most complex report automation processes, exponentially increasing ROI benefits for a lower total cost of ownership. The new platform currently supports two vertical solutions, Augmented Financial Analyst and Augmented Medical Writer.
According to Gartner’s 2019 Market Guide for Natural Language Generation Platforms, “25% of enterprises will use some form of natural language generation technology by 2022”1. Based on actual ROI findings collected across over 100 successful Yseop projects, scaling from single use case applications to enterprise-wide deployments could translate into billions in savings for the financial and pharmaceutical industries.
Developed with high levels of user-adoption as a driver, the new Augmented Analyst solutions come with a user-friendly Studio interface, providing intuitive drag-and-drop functionalities. The new interface was built to empower non-tech savvy business experts to design and configure reporting models based on their needs and across different business departments with no custom development. The solutions also encourage user feedback and will rely on machine learning to constantly adapt to analysts’ style and preferences for superior end-user experience and satisfaction.
Emmanuel Walckenaer, CEO of Yseop: “In the finance industry, we receive multiple testimonies from our clients, highlighting how we help them transform the way they manage financial reporting, improving the efficiency of their teams by automating many of the previously manual, repetitive tasks and processes. As artificial intelligence is now becoming widely available, Augmented Financial Analyst is designed to make the technology available to large companies worldwide in a way that is cost-effective, scalable and truly valuable.” Yseop initiated last quarter a series of breakfast briefings “ YseopMorning ,” inviting users of its technology to share their return of experience with the local community of actual or prospective NLG practitioners. The second installment will be taking place in Paris on February 25 in the presence of Capgemini and BPCE presenting Yseop Augmented Analyst case studies.
Notes to editor:
Augmented Analyst is powered by “intentions”, an innovative approach to natural language generation developed by Yseop. Intentions are pre-packaged libraries of reporting typologies and text structures addressing specific financial and medical reporting use cases, based on deep industry expertise, regulatory requirements and the latest in AI and NLG technology. Out-of-the-box financial reporting intentions cover up to 80% of all reporting requirements, with the remaining 20% based on tailored rules and formats specific to each business. Intentions enable multiple narrative versions to be generated at once, marking a significant step forward from traditional ‘template-based’ systems which are much less flexible in terms of narrative output.
The platform combines different AI technologies including machine learning, NLG and natural language understanding allowing users to customize reporting narratives and feedback to the system. This enables the platform to learn a user’s specific style to improve future text generation, facilitating high-levels of end-user adoption.
Augmented Analyst is fully integrated with Microsoft Office and other business intelligence solutions like Oracle or IBI, meaning analysts only need to focus on adding their insights to already qualitative reports. The platform can be deployed on the premises or in private or public cloud, including Amazon Web Services (AWS)
YSEOP is an international company specializing in artificial intelligence and a pioneer in natural language text generation (NLG) technology.
Its Natural Language Generation (NLG) solutions utilize artificial intelligence (AI) to make sense of complex data sets, generating high-quality written narratives accurately, quickly and at scale. With specialist tools for complex financial and medical report writing, as well as sales automation, Yseop is trusted by leading global businesses to help automate and industrialize processes, empowering workers and driving digital transformation.
Founded in Lyon, with headquarters in Paris, Yseop works with clients across Europe and the United States. It is rapidly expanding globally, providing enterprise-level automation solutions for some of the world’s largest companies, including in finance (Credit Agricole, SG, Moody’s, BNP Paribas), pharmaceuticals (Sanofi), and the technology sector (Oracle). It also partners with strategic consulting and integration firms including CapGemini, Accenture, and LTI, who support the deployment and adoption of Yseop’s NLG technology.
Find out more: https://yseop.com/
1Gartner, Market Guide for Natural Language Generation Platforms, 27 June 2019, Bern Elliot, Anthony Mullen, Adrian Lee, Rita Sallam