Content Intelligence With Bill Galusha, VP Marketing at ABBYY

Automatic TRANSCRIPT

Guest today is is Bill Galicia. WHO's the director of Product Marketing at Abbey High Bill. Thank you so much for joining us on this podcast today. Thank you for having me on. Welcome bill and thanks for joining us. We'd like to start by having you introduce yourself to our listeners. Tell them a little bit about your background and your current role at Abbey sure so I currently work for have you have been there for about a year and a half now. I'm the Director Director of Product Marketing I head up our innovative products group focusing on some of the growth markets that we see and kind of we're Abbey's technology can be we're customers can benefit benefit within different markets and different industries prior to come into abby and I've been in the offer industry and a price offer industry about twenty three years now working for both small Paul Startup companies and large enterprise companies like EMC as well as Colfax previous company. I worked for so my background has been both in product management product marketing focus on enterprise software everything from processing and understanding content to business process automation platforms. I have managed as well to his sounds great and in one of the things is that when we spent a lot of our time talking to enterprises and organizations both in the private sector as well as the public sector you might think of information stuff that's stored in databases and applications applications but as we all know like ninety plus percent of the information that is flowing through the enterprise and the organization is unstructured. It's information that's an documents and emails and texts and voicemails videos and images and even log files you just kind of like lots of the stuff that's just kind of dominating the enterprise between all of that and it makes over ninety percent of the information so clearly that's part of the reason why people are looking at technology is like ai machine learning extract more value from this and try to learn and find the patterns earns you. How are you seeing companies using AI and cognitive technologies to extract more value from this vast treasure trove of information in the enterprise yeah yeah great question and you know if he kinda rewind go back ten fifteen years. You know a lot of enterprises were processing information that was trapped on papers. You saw a a lot of canning going on in back offices high volume scanning in with the purpose of turning that into digital information and extracting the content the data from those documents and putting it into systems systems and paper has gone away. There's been this kind of this thought that well. We don't have you know unstructured content documents to deal with anymore. which really isn't the case anymore or in really what you see is that a lot of the content is now being digitized at the point of origination and being sent in as documents minutes attached to an email as an example or being captured on a mobile device so you still have this requirement where you have all this unstructured information that's trapped within these documents then needs to be understood and extracted and connected into a business process and those processes really transcend many different industries banking insurance logistics excess manufacturing? Some of these processes are back office so you think a good example is really in finance so you get processes like invoices purchase orders and sales orders and some of that is digital so you have companies that work with their vendors and it's all the information digitally transferred but again some of these documents are are captured the source attached as say a PDF or an image to an email sent in and that's really where Abbey's technology comes in the play to be able to understand classify what what type of document is this an invoice from ABC companies from a different company being able to extract the information say from Invoice the header the photo Lai nine details really putting heading into a structured format inputting information into a system like New York P. System Mendon connecting a to a process where he will have approvals and reviews along the way while too so There's a lot of different use cases so some of these are in the back office a lot of our front office where it's directly connected to a customer experience so banking is another good example where a lending process will kick off requirement for certain documents be sent in by that consumer. I mean those are documents that Abbes technology and Dan the used to not only are the technology digitize it but also be able to classify extract and continuously learn on you know what type of document and so those are as well as being able to extract the information and enacted into the appropriate system and

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