New In Nuix Neo - Introducing V1.3

for my name is Rick Barnard I'm a member of the leadership team here in the north Americas and I am hosting and moderating today's Global webinar focused on the introduction of newx Neo version 1.3 and I want to First address a few housekeeping items uh first uh there is questions and answers available you can submit your questions via the ask a question Tab and we will answer all those questions at the end of the segment or at the end of the presentation so we welcome all your questions so please submit them throughout the presentation at the end end of the webinar we're going to take a moment to rate or we hope you will take a moment to rate this presentation and provide feedback using the survey Tab and a recording will be available of this presentation and shared with you and we welcome you to share this with your colleagues um after the conclusion of of of the webinar discussing today's agenda we'll start with a quick welcoming introductions so welcome uh thank you for joining us I'm joined with two of my colleagues who are going to lead the presentation first uh James Silman who's the director of product management here at nck and Stephen Stewart who is the America field Chief technology officer they will be discussing new EXO going into detail in regards to version 1.3 release specific Fe fees and capabilities enhancements that are available and detail how those relate specifically to investigations use cases and then we will conclude with a pathway for those of our existing customers that currently use nux to newx Neo and and the options that are available and we will conclude with questions and answers so at this time I like to proceed and turn it over to James Silman James thanks Rick as Rick said my name is James Suman and I work here at Nock on the product team so to give you a little bit background about myself my background is in computer forensics and I primarily worked in the government and corporate space doing investigations I was previously a NX customer before joining NX almost about eight years ago now so as Rick said I just want to briefly introduce you to newx Neo talk about what it is and then I'll talk to you about some of the exciting enhancements we have as part of this release so what is newx Neo newx Neo is our unified platform that helps organizations solve their most challenging data problems a true endtoend platform at its heart the world's most powerful processing engine Enterprise Automation and AI built in that allows you to work faster easier and smarter so when we say faster what do we really mean by that so customers today are limited by the number of workers they have this causes constant tradeoffs in priority and reduced delivery time times with new Neo we've eliminated eliminated this restriction with unlimited workers so you can now process more data faster producing time to results additionally manual workflows they are timec consuming and aone you know I remember as a customer having to log on late at night or on my weekends to start to process new data start OCR or other activities also we could maximize machine time and our workers newx Neo's Enterprise automation capabilities allow you to develop workflows that not only automate newx but your entire Enterprise this ensures consistent repeatable defensible processing minimizing machine downtime and maximizing dat data proof so when we say easier what do we really mean so traditional tools they're very siloed in nature if only one user being able to access them at time our web first approach allows collab our web first approach and our collaboration tools built into the platform make it even easier for investigators to work together and collaborate and access Neo from anywhere additionally artificial intelligence is huge right now you know rightly so it has the power to transform our workflows and make our lives easier the challenge is it's prohibitively expensive to high data scientists and the tools that we have today are available aren't customizable and are bit of a black box so you don't even know how it's making the decisions with Neo we've democra democratized artificial intelligence a no code AI model builder allows anyone to develop their own AI models within minutes that suit their business needs and deploy them within seconds that's if the hundreds of models that ship out of the box don't already fit your needs each one of those customizable additionally RI allows you to understand how the decisions it's making are done and so you can easily defend um defend the results and finally smarter you I've already mentioned that you can build your own AI models are no code UI or you can leverage the hundreds of models that come out of the box r allows you to prioritize what needs to be looked out first allowing you to understand the types of documents you have in your data set what are people talking about what kind of pii or PCI you may have or why your resc is so today you can easily check a box to find all your PDFs or emails now you can easily check a box to identify your contracts your legal documents or where people are talking about politics or terrorism all in a all of this enables you to work smarter so the newx new platform is backed by the newx engine and allows you to bring in those over 100 over a thousand file types of unstructured data however Neo is a true entm platform from identifi from data identification collection enrichment and intelligence extraction through our AI all through to review all automated on top of our platform are our tune Solutions with data privacy and investigations available today in new legal coming soon each one of these Solutions is tuned to solve your use cases we have additional extensions that enable you to augment a Neo platform depending on your organizational needs being able to identify what risky data exists on your users endpoint or machines our threat detection and data protection capabilities as part of adaptive security or our extensible SDK if you to customize a Neo platform so I'm hopeful with this brief overview you can see that the NX Neo allows you to drive to outcomes faster pushing your data through regardless of where it lives through our engine at scale and using AI to understand your data and extract vital intelligence to cut through the noise all automated and all ready for review so I want to share with you some of the exciting updates that we've made as part of this latest version of Neo we're going to talk about our knowledge graph and how it's redefining data analysis how our Enterprise automation can reduce your backlogs how our solution packs reduce time to results enhancements to our connectors ensure you can get access to your data anywhere we've expanded our forensic e EOS system we've got new UK and Australian AI models that help to extract intelligence easier and finally I talk to some of the existing NE capabilities that we have that massively improved the lives of our customers so one of the most exciting aspects of this release is our knowledge graph so as we know relationships are key in any investigation questions like how are these two people connected what connections to these individuals have in common that's where our knowledge graph really shines it allows you to cover hidden patterns and Connections in your data the traditional investigative methods might miss our knowledge graph empowers you to extract meaningful insights identify Trends and make smarter decisions faster the intuitive user interface allows even non-technical individuals to do deep data analysis and ask complex questions so they always say a picture is worth a thousand words so seemingly simple question how are these two nodes connected traditionally this would be a painstaking manual Pro process happen to do search after search while trying to uncover a path between those two nodes what happens when you uncover a new person of interest now you s again this process is time consuming and doesn't really work well with being able to quickly iterate on different questions that you might have as an as part of an ongoing investigation using our knowledge graph we can select those two nodes simply right click and choose shortest path within seconds we've uncovered not only that these two entities are connected but by what means can you imagine having to do this manually when there's multiple Degrees of Separation another example Can you spot the hidden patterns in this data again a simple right click using the All NE neighbors algorithm and we managed to cut through the noise and you can start to see patterns in the data for those familiar with graph databases you may be aware that traditionally for you to do what I just showed you they all needs to be Pro pre-processed ahead of time with all those relationships def up front traditionally this is done in a spreadsheet it's extremely time consuming and expensive because it's a manual process with Neo Knowledge Graph we're leveraging the power of the engine and what it does best taking the unstructured data and then normalizing it we then layer on top our AI which helps extract that intelligence and enrich that data all that data is then loaded into the graph all automated no manual work up front and All tune to solve your specific use cases our knowledge graph works knowledge graft Works seamlessly with Neo being able to quickly send results back and forth providing you with traditional review capabilities of the new platform enhanced with the power and visualizations of the knowledge graph so now you can take any data and uncover hidden relationships that would otherwise be missed another exciting enhancement as part of this release is a Monumental leap that we've made in our automation capabilities we know that data volumes today are growing in variety and variability and increasing that in expend exponential rate we know that there's an increased pressure for organizations to deliver results faster driven by the advantages in technology and the 24-hour new cycle we know that organizations are being asked to do more with less and the skilled labor shortage is causing a backlog of cases our Enterprise automation allows you to automate hundreds of steps but not just across newx across your entire Enterprise allowing you to collect process and push dat to review all automated our automation uh Enterprise automation comes with granular security controls that ensure consistency by preventing incorrect usage predefined outof thebox workflows to reduce time to Value all customizable uh so you can fit it with your business needs easily extensible scripting capabilities and the ability to hook into your enterprise system to make more informed decisions and finally the ability to manage Cloud resources being up to spin up and spin down machines in the cloud to take advantage of those unlimited workers and to cut through your backlog one of the guiding principles we've had since the obsession of Neo is how do we reduce time to value and time to answers you've already seen this with how Neo is faster easier and smarter but as part of that g principle we've developed what we call solution packs every Neo solution comes with a solution pack tuned to those specific use cases these solution packs are made up of three main areas we distill best practices when it comes to processing Automation and review to take the guess work out of it these include things like default processing profiles search fils metadata profiles dashboards and more each solution pack also comes with AI models designed to identify data relevant to those use cases this is in addition to the hundreds that already ship the box and finally each pack comes with automated graph analysis playbooks that Leverage The Power of the knowledge graph to help you identify hidden connections and what and what matters most in your use cases each of these solution packs is fully custom customizable and provides a great springboard and allows you to just add data more and more of our customers data is moving to the cloud and the cloud makes deployment and management of Enterprise applications you know seamless and easy the challenge is these Services don't make it easy for you to export your data not only are the tools provided complex leading to mistakes exporting data in especially in large volumes is time consuming that's why we've continued to enhance our connectors to take advantage of the new capabilities released by these vendors with each of these connectors we've meticulously optimized them in uring each one is simple intuitive and performant so you can get access to your data faster I'll talk more about Microsoft 365 shortly but with both slack and Gmail we've implemented search ahead so now you can reduce the volume of data that you need to export and review saving you time and costs and these are just really a subset of the connectors available within the newx Neo platform we know from speaking with our customers that the collection of Microsoft 365 is Paramount we know that collection of this data be that emails teams data SharePoint or one drive is complex Microsoft offers multiple ways to collect the data there's the graph there's Microsoft perview as well as traditional PST exports it's timec consuming manual collection has multiple steps each requiring the user to sit and wait while each stage completes moving on to the next an eror prone these tools are confusing and lead to mistakes that can cause huge amounts of rework all of this is in addition that Microsoft continuously making changes to their platform other tools provide you with a single way to collect data from Microsoft 365 not great if that doesn't align with your organizational needs or security requirements Neo offers a comprehensive set of capabilities to collect Microsoft 365 data that can meet your organization's needs and we've automated The Collection as well to reduce human time and errors we've expanded our forensic ecosystem we know customers today use other tools as part of their workflows especially mobile forensics once you've collected data in these various tools are customers to run into several challenges you can't search across your disparate data sets which results in misconnections you can't dup across tools result in additional review and lost time and you can easily collaborate on complex investigations in these Silo tools that's why customers love the holistic view they get from NX the ability to bring in data regardless of source so you can search dup and collaborate all in one platform in this these we've enhanced our support for expert witness format and the latest version of oxygen mobile forensics you can also bring in your existing magnet cases including any work that you've done such as taging into newx this is on top of our existing support for tools like celebrate MSB and Hong being able to extract intelligence from your data set is critical we know that we also know that traditional ways of identifying pii or PCI such as Rex are fraud of issues it's complicated writing reject is highly Technical and error prone this leads to lots of false positives or Worse false negatives while you miss critical pieces of data by leveraging the AI capabilities in newx Neo we're able to reduce false positives as newx MP understands the data so rather than a system blindly assuming that any n digigit digit number is a social security number our language model models understand the context is this a nine digigit number near someone's name inside of a paycheck proper your social security number it's this nine digigit number in a gardening magazine probably not this reduces the time spent on review as well as your overall risk so in this latest release we've developed new models to identify pii PCI and banking data specifically for the UK and Australian markets now this is in addition to the hundreds of models we ship with today each one customizable in our no code UI the ability to understand how AI makes its decisions finally I just want to touch on some of the key features of the new newo platform that we're seeing transform our customers workflows I've already touched on it but our AI enabled workflows each solution comes with equipped with hundreds of models out the box including ones that are custom tuned for data privacy investigations and soon legal this allows our customers to drastically reduce a time it takes to to identify important document types topic types risky and risky documents as part of their data set search while loading so today you have to wait until tasks such as processing or have finished to start to review your data this slows down time to results but also forces customers to start to complicate their workflow by creating subcases so they can continue to review their existing data while data is processing I know that when I was a customer I remember having to continuously create subcases and having to move those so they could be added to compound cases this really complicates workflows and causes extra burden on administrators with search while loading you no longer need to wait until task like processing or have finished to start to look at your data what it's only available as part of elastic now every Neo customer can review their data while it's still processing we've made it even easier to onboard users to the new to the newest platform with single sign on across Neo not only can you quickly switch between capabilities within the platform but our Enterprise authentication also makes it easier to hook into your organization's existing security infrastructure we've added rsmf support with the increase in chat data and complexity ease it brings we've added support of rsmf that enables you to seamlessly bring in and Export chat data this enables for the interoperability between Neo and other platforms and finally enhan promote to discover makes it even easier to move data from ECA all the way to review with all the control you need all automated overall these are just a small subet of capabilities that we've introduced since the launch of newx Neo I'm excited to hand over now to Steven Stewart who's our field C and he's going to talk to you about our Neo our Neo investigation solution Thanks James uh I'm excited for the opportunity to talk to everybody today uh again James that was an excellent overview of of Neo and how we're thinking a more broader sense about the Neo platform and really sort of grounded in sort of you know a couple of fundamentals you know around faster smarter easier and solution ions uh you know to get it started you know I'm sure uh many of you know me my name is stepen Stewart I am new ex's Chief technology officer or field Chief technology officer uh I've been around new for close to 16 years at this point uh and really have spent my entire professional career in sort of the the document management archiving Discovery investigations and Big Data space and really what I find so interesting about the culmination of all of those different experiences is it all comes down to getting to know and understand the data and in almost every fashion you're basically conducting a large scale investigation and that large scale investigation really is about how do you answer those fundamental questions of who what where how when and why and as you sort of start with those basic questions and you expand that out into all of the disperate data types that our investigators are confronted with on a daily basis you know across the the thousand different file types and the 10 dimensions of data and all those those different things the goal is the same you're really very much trying to just understand what happened uh pull those pieces together and really sort of get a true sense as to exactly what happened when and where and that's no more prevalent than the amazing work uh that all of our customers and partners are doing out there in the wild and I take tremendous Pride at being at newx over the years and sort of understanding our software's relationship to tremendous uh events that have sort of made the national stage uh it's interesting to sort of be asked questions uh you know and say a one year and then several years later understand the nature of that question you know so in the top left you know mobs mob storms the capital so that's January 6th here in the United States uh some number of months after that I was asked a sort of super random question that came out of nowhere hey we're trying to find Flags in some data that we have do you have anything that will help with image classification and the answer was yeah we have an image classifier uh you know it does these specific things here's how you might be able to use it uh and they were like oh okay great and then that was all we heard and then come back you know a year later and they're like oh yeah we used the engine and the image classifier we were looking for flags and it was this great experience of sort of like yeah you know it cut us from like six million images down to like 100,000 that we had to look through and it was sort of F and it was fantastic similarly in sort of the upper right operation Ironside a global law enforcement engagement you know several years before it was sort of made public I had a random question about hey what if I put 12,000 mobile phones uh into the uh newx investigate canvas what would happen would it basically all of a sudden sort of would it tip over would it work and I was like I don't know like here let's try it let's see how we can do these we can change these things lo and behold operation Ironside comes out and it's contextualized as to what the types of problems that our customers are trying to solve and so the reality is it's out there and there's you guys are working with tremendous volumes of data trying to solve that but at the end of the day it kind of comes down to really just kind of crunching through some numbers that the scale and complexity of large investigations is increasing you know basically and the Not only is it the size and scale of the investigations but it's basically the dollars that are involved you know so the UK actually estimates in 219 Mill billion dollars could be lost associated with fraud and that's a just a staggering number and that's just within the UK in the US it's anticipated to be closer to 374 billion dollar excuse me 364 billion and so with that in mind those are just staggering that's nearly half a trillion dollars or more than half a trillion dollars that could have been loss associated with fraud and the problem is is that it's very difficult to investigate you know some resource says that there's up to 25 ,000 plus devices in the backlog and so again this is the basics of how do you sort of hit you know the singles to accelerate the investigative process how do I allow organizations to work through their backlog more quickly and more efficiently because it's certainly not available to hire another 10,000 investigators to look at this you've got to come up with ways in which you can be work faster smarter and easier and not to mention sort of you know the idea that sort of within that uh you know there's such a small amount that's actually being investigated and so you know you take that backlog you take uh the small percentage relative to something like the 40% uh of actually sort of uh number of matters or crimes that are need to be investigated and we're facing a global investigative crisis and that we're basically falling further and further behind and so in order to sort of start to think about that you know you have to think about how do you scale and scope and sort of approach your investigations you know high volume low comp lexity in one corner low volume low complexity in the other and then in the upper right you've got the high volume High complexity and so high volume High complexity these are your most difficult ones there's a lot of them that you have to work through you're dealing with a lot of devices and a lot of items but sort of what is that high volume High complexity is that only the uh the top tier serious and organized crime the multinational aspects all of these other elements you know sort of is it that sort of characterizes that and so when you think about it you could actually roll back the clock and sort of one of the very first and sort of largest investigations uh in sort of law in UK law enforcement into basically one of the earlier s serial killers Peter stut Cliffe uh you know the idea was the data there was incredibly complex there were only over 2.2 uh excuse me only over 250,000

people were interviewed 32,000 witness stat statements taken and 5.2 million car registrations checked and the reality is as that investigation took place they generated so much paper that they actually had to reinforce the floor now in every matter that's a hugely complex investigation there were hundreds of people working on it over the years and a tremendous volume of effort went into sort of trying to figure that out and so you can you imagine if you now roll that forward and you start to think about basically a single mobile device so the one that each of us probably has in our pocket may be more as I sit here doing this presentation I've got my mobile phone on my desk I've got one laptop in front of me I've got all of the other laptops around my house investigating a single suspect could lead to hundreds of millions of messages all sort of contained within a single household so now everything is basically a high volume in terms of data quantities and high complexity because you're trying to understand how all of this stuff interrelates and you need to be able to feed it into a system that'll allow you to index process it extract that information and get to those outcomes as quickly as possible and so when we sort of take that step back and we think about newx Neo and solutions this industry has known newex for for decades actually as you know one of the leaders in digital investigations and really The Sweet Spot of where noex excels is around sort of the complexity of being able to pull lots of different disparate data sets together you know James sort of in the in the feature over in the Fe feature overview of Neo he mentioned sort of being able to pull in data from magnet cases or eyewitness cases or other auction mobile forensics the ability to sort of aggregate and roll up data collected from all different sources perview Google mobile phone devices ufdr Etc and then be able to present it into a single view is really what differentiates newx and the newx investigation Solutions if we're going from labs to Smart Labs all the way up but when you think about like the life cycle of a typical investigation how do I start to think about reducing that time window like you see the longest bar there you know the DF digital forensics and investigation that is basically the long poll in the tent how do I Crush that data understand it handle it in a consistent repeatable and defensible process and again then move it Downstream into legal and within that there's a huge amount of sort of repe process and the key things is how do I shorten those windows and you can shorten those windows pretty easily you can shorten those windows with operating smarter so basically use AI to be able to find the answers more quickly faster being able to sort of run horizontally more operations and easier by being able to automate a consistent repeatable and defensible process that allows you to ensure that all of the work you're doing across all of your data is actually well well understood and easy to manage Ag and so with that you sort of take that idea of what are what is available and then what is being done by organizations are out there so uh police Scotland are sort of a real great Testament of what they can do and how automation can sort of dramatically improve the process and they took this upon themselves and built their automation from the ground up to be able to quickly drive that process they're now looking at sort of all of the other ways in which they can expand that Automation and sort of take it to the next level in and around sort of adding AI into their workflows and other things you know basically vone on the other end went for almost to z% backlog or basically 90 a no backlog with 99% processing so this ways in which these organizations are essentially chewing through that device backlog that we heard a few minutes ago about 25k uh devices and stting to work through the automation that making it faster smarter easier is really sort of at the heart of what Neo is designed to offer and so again when we talk about newx Neo specifically newx Neo investigations it's how are we thinking about taking these investigations to the next level you know people have used uh the workstation and investigate and they basically have built labs and they've scaled it out and Managed IT and so with Neo it's about bringing all of those components together into a single unified platform that is basically enabling automated case specific workflows and those automated case specific workflows are very much how can I take every investiga bit of intuition that each of your investigators has and basically memorialize that into a specific workflow step how can I then repeat that every single time such that it's tagged and processed Etc how can I sort of again then scale that out horizontally such that I'm going faster not just per unit but faster across all of my horizontal resources to basically drive that AI powered language models to be able to get you to that answer more quickly and then sort of that last bit around sort of Greater insights through the link analysis you know at the end of the day it all comes down to sort of where James started about being able to take huge volumes of information and drive that through to data insight as quickly as possible and those Data Insights sort of are so much more than just a search and tag they are how can I understand the hidden relationships how can I prioritize what I need to look at first by doing uh risk scoring associated with those items and again pushing that as part of the neop platform and investigations is really sort of what we're driving here today and then when I think about sort of like what does it mean around sort of driving this from the bottom up sort of with investigations it's how can I think about how taking the new XO investigative solution and basically thinking about larger more complex investigations and all the people that need that so we're talking about public and private sector we're talking about regulatory investigations we're talking about fraud at sort of a national or global scale we're talking about serious and organized crime and in each one of these individual layers they basically are building up to deliver elements of Fraud and if you can start to understand how fraud and how that money flows across all of these and the hidden relationships you really could start to see how the overall newx Neo platform and our specific focus on fraud for investigations can drive tremendous acceleration across all of your investigations and so again back to the faster smarter and easier and we really sort of reiterate this because by being faster smarter and easier we think we can do tremendous or provide tremendous value and that tremendous value is again pretty simple how can I get more data through more quickly how can I work through my backlog how can I start to handle sort of data in real time so we start to think about some of the added capabilities around the it's the realtime analysis so many of your use cases May deal with collected or static evidence others of you may want to basically be able to stream uh sort of licensed plate reading information or other Financial transactions or other thirdparty information into the system so that it can be correlated one of the most exciting things about sort of uh newx Neo investigations in the knowledge graph is being able to look for hidden relationships Beyond just the evidence but being able to start to think about leveraging reference data that can then F further inform your investigation and sort of ask those simple questions about how far away is this from a known bad transaction or a known bad actor so all about sort of making things faster uh easier uh actually easier and when we think about easier uh easier is all about getting through the work with less friction and so how do I make it easier I make it easier by automating the process uh you know as I've said I've been at newx for 16 years and in those 16 years I've pushed a lot of buttons on workstation I've also done sort of by hand some of our gigantic investigations and supporting different financial institutions the largest one was 340 terabytes of Legacy email data that resulted in like I think it was 3.2 billion emails the reality is that took an inordinate amount of button pushing and that button pushing even though we automated specific elements required us to try to run amongst us almost for a 24 uh 24 by7 clock for I think 45 days that was brutal I now look at what we're doing with Automation and the ability to report across that process Auto those workflows drive that let's just say I could have gotten a lot more sleep over those 45 days if I'd had newx Neo today and so by making that process easier and focusing on things like how can I leverage all of my internal subject matter expertise as opposed to always having to go outside I can start to do things like building AI models using a no code user experience I can interoperate with the seamless webbased user experience that I can single sign on across my various things kick off my job jobs get email notifications all of these things are really about making this process much much easier and then the last bit is around smarter you know so faster smarter and easier when I think about smarter I mean obviously you want to work smarter uh so things like automation scaling out horizontally to get more done more quickly but then that ultimately lends yourself to how can I use AI to point me to the items that matter most and so depending on your use case here today we're talking about investigations we focused a lot of our tent our time and attention around fraud and things like identifying Financial transactions uh looking for financial documents so ledgers all of those types of things and basically being able to effectively pre-aged the you know the experience of your most seasoned investigators they probably have a pattern that almost in every single investigation or an investigation of a specific type you know be it fraud be it serious organized crime you know they know what they look for every single time and that's where they start what this allows us to do is take that intelligence and wisdom and start to build models that can basically pre-aged and basically push that information forward uh as you start to think about it when you start to understand and Elevate those scores so again that idea of faster smarter and easier and what drives that is really the enrichment and so when we think about the workflow the data rolls through the newx engine text and metadata is extracted it's then pushed back into the newx case when it's pushed back into the newx case it then becomes searchable across all of the newx aspects so you can search it from workstation the engine investigate via the API you could promote that information out to discover you can promote it out to other third parties and so by enriching those individual items with classifications categorizations facts that have been extracted prioritize around risk scoring and then help you visualize this really sort of allowing you to work much smarter and so of the elements is the classification so what is this document is this a financial Ledger is this a tax document is it a credit card agreement uh we had someone yesterday asking us about trying to be able to use these classifications uh to rule out garbage so they were tired of looking at help files and so they said all right well can you build a model for that sure that's really easy and one of the most important things to go to the easier is the noode model builder and the no code model builder allows your subject matter expertise to basically take tune and basically even augment our existing models but then easily build new models from scratch so again new X is and newx Neo is all about pushing the AI as far to the left or as far forward in the process as possible a lot of the other investigative platforms out there will push the analytics to the right and they're purely ring on using analytics to accelerate how you review documents we're Accel we're using AI to accelerate sort of like what you look at first and again by telling you what it is and each one of these elements is stackable so they basically accumulate value as you go through so if I talk about you know what is a document and then I ask the question what is this document about is it about sports is it about politics uh is it about uh terrorism you can then sort of use these layers to start to sort of pull different information together you know again start to think about how can I sort of take and tune you know so as it relates to things uh within the investigation Sol ution pack from a categorization perspective it's looking for things like pressure rationalization and opportunity so how can I start to understand and categorize data based off human language uh and it's not just keywords it's using the vectors and the contextual information to really start to understand how that information Works uh you then take that next step and you start to think about extraction so how can I extract this information in a meaningful fashion and so this is what James was talking about is sort of the idea of regular expr ex and false positives or worse than that false negatives uh anybody that's ever tried to create a regular expression for for a social security number and doesn't want to miss anything uh that's pretty dicey uh you can basically pull in every single nine-digit number uh out there but what you can't do is basically contextualize it well at least until now with nox's cognitive expressions and what this really allows you to do is take a whole bunch of sort of outof the boox regular expressions or easily add in your own you know some of the work that we've done with the release of newx Neo 1.3 is we've really started to dial in those uh regular expressions and cognitive expressions for the UK and Australian markets so we started with the US market so we have sort of a robust base and we're now augmenting them around sort of different things like UK driver's license or Australian identification cards to basically ground them the value of the cognitive expression which is the other part of the fact extraction piece is how do I then say okay well what contextual information around this lets me know that this is a social security number is it something like SSN or is it you know national ID or what are these other aspects you then take that around things like credit card information so you're looking for security ID you're looking for CCV you're looking for other things around that that contextualize and this contextualization and this sort of fact extraction is really what drives our sort of uh knowled graph uh expertise and so for years we've been talking about how to do this better and through the addition of NLP and our context to Weare entities we are really able to nail sort of a highly reliable and uh chated Knowledge Graph so if I then sort of take that and think about okay well that's great uh you know so I've got I can understand what the document is I can categorize it I can extract the information out of it the next thing is really sort of how do I start to think about prioritizing and prioritization goes to things like Risk scoring and so in each one of those instances let's say let's take for example a US tax document so us tax form say a W2 uh in of itself is uh like let's say a blank W2 is not that interesting but I would like to know what it is uh if I have a populated so that basically means a W2 form that has pii and Phi okay that is more interesting that is more potential risky if I have a PDF file that has 100 pages of W2 forms and 100 people's pii that is incredibly interesting and I want to prioritize that by telling you to look at that first and I can use the combination of scoring with NLP as well as sort of classic uh search and tag to basically be able to bubble that information up to the top and so again this idea of really being able to drive that and push it forward to sort of understand sort of what needs to be looked at first and again we've put this into the investigation solution for Neo but we also have a framework that allows you to take your own explicit knowledge and augment it in a really really simple and easy fashion and the last piece is you know as we start to think again not the last piece but as we start to go through the multi-dimensional uh text analysis is then how do you sort of pull this stuff out and so again that idea of running all these systems under the hood to really then drive it to hey look at me first and so when we get to the hey look at me first we've actually built in logic that sort of applies this bubbles this stuff up to the top so as your investigators land in uh in the web application you investigate they can immediately go and say okay well I want to look at this stuff first and so it's again taking our knowledge our experience working with subject matter experts in the industry to really help and sort of drive that prioritization delivering dashboards that allow you to sort of accelerate and understand that information and most importantly prioritize you know when we thought about sort of that fraud timeline from a couple slides ago you know it's all about how can I compress time not only how can I process the data faster but once I processed it what can I do to it to enrich it to basically point the investigators hey look here first and instead of having to just sort of start from a and go to Z uh they can basically jump right to M where the most relevant information May lie they're then welcome to go back from a through M but if we can point them to what they need first uh through AI Automation in a consistent repeatable defensible fashion with sort of all of the other aspects around explainability and specificity and transparency in our AI these are all really valuable elements that help you sort of get to that answer more quickly and the last piece and James touched on this uh is really the how you start to think about understanding and visualizing this information so James touched on the the knowledge graph uh the knowledge graph uh for me is an incredibly exciting advancement in our technology uh and in practice we've tried it in the past using things like regular Expressions to basically drive a knowledge graph or we've created a Knowledge Graph based purely on Communications data so to from ccbcc the reality is they were okay but the question from everyone in the field is how do I correlate and understand the relationships across all of this data how do I link email Communications to financial transactions to a list of people and known bank accounts how do I put that all in one system and basically say all right well how is Stephen Stewart related to Kaiser so you know my my favorite sort of fictional bad guy and before as James said sort of when he was talking about the features that's really really difficult it's a lot of interrogation of information it's a lot of repetitive searches it's a lot of ring documents wouldn't it be better if I could basically feed all of that information into the newx Neo engine extract that information normalize it and then create a highly curated Knowledge Graph that highly curated Knowledge Graph sort of has well-defined nodes and edges a well-defined schema that can be targeted directly from the engine or targeted through NLP such that you can start to build that information up and really start to visualize how this information is connected you know so on the screen we've got a screenshot of looking at Bitcoin and asking how Bitcoin is connected to open source intelligent information this is really about how can I do this without creating the gigantic hairball that many of you would have seen if you've tried to use graph technology it's just hasn't been smart enough until today but now with nox Neo investigations we've got the smarts we've got the Engine That Could extract that text and metadata and now we've got the schema and the playbooks that allow us to Define and drive a really accurate and highly curated Knowledge Graph when we think about sort of you know kind of to little bit of a recap that's the idea of you know look within the investigation solution you the idea is make it so that you can just add data you know we've got the solution pack that includes targeted investigative NLP models targeted uh things for extraction of pii and Phi metadata profiles processing profiles workflow automation steps visualizations within and dashboards within investigate and then the Playbook that basically allows you to drive the customized linking associated with the knowledge graph so really powerful powerful ways that you can take it out of the box or you can tailor it to your specific data in your specific use cases and really sort of take this solution framework to the next level and Beyond but it's all rooted in sort of our core tenants of newx Neo and it's really trying to make it your work faster easier and smarter because ultimately the challenge that you're facing is backlogs pressure time time resource the desire to actually get home and see your family and so all of those things can be sort of facilitated through better automation easier user experience how can I sort of get you to those answers more quickly so whether you're in the lab trying to process that data and get it prepped or you're the investigator that's trying to answer time critical and sensitive uh investigative requirements it's how can we get the right data in front of the right people as fast as con ably possible and so with that you know we really are on the journey you know the people that have are here today you guys are definitely on the journey to Neo with us you've been part of the newx Neo and investigation or excuse me the newx investigations and really sort of how can we think about taking you from where you are today into sort of what we think is an amazing way uh to accelerate your outcomes and really ultimately get to those answers much more quickly and so with that I'd like to turn it over to my colleague Rick Bernard uh to take you through the pathways to Neo Sten thank you so much also James appreciate it uh great discussion and overview um so I'm just going to conclude the discussion with options for any customer including existing customers on our our journey together uh to Neo and then we'll open it up for uh Q&A so if you've had any questions throughout this presentation take the time now now to submit your questions and we will address them in just a couple short minutes but I'll start with the bottom right so that's the foundation that we're that we're building off of right neix that you've been using for for decades our classic capabilities you can continue using those um you know the newx engine you can build around it you can augment with U third party products or automation with newx Automation and rampa to enhance the the workflow end to end from collections to processing all the way to review so there's a lot of enhancements and Innovation that we can build around our traditional components and use that as a pathway to build upon to enhance your your workflows your playbooks your visualizations your reporting and build on that to uh bring enhancements um on our journey together the second option that we'll build off of that is is what we'll call the pathway to newx Neo which again is to extend and enhance so that gives you unlimited cores it boosts your productivity we start building templates playbooks together again some of the same um elements that I just talked about with extensions from legal hold to perview collections and that gives you you access also to nux's tailored Advantage offering which which is a um customer success journey to allow you to unlock the full capabilities of the new xneo platform as we move to a more usage based licensing model um which is which is also available with newx Neo right so the the third option is obviously to go to newx Neo which a lot of our customers are doing you've got tailored Solutions whether it be data privacy including data breach notification or the investigation solution that we talked about today but it's really focused on addressing our toughest data challenges in a customized configured um solution which has all the configured workflows all the customized NLP models and user profiles to really unlock the power of the Neo platform and we've talked a lot about that in the last uh 40 minutes in terms of all the benefits that it provides and all the features it provides unlimited cores for processing and usage based licensing so whether you're ready for newx Neo or you want to build a pathway to Neo we have lots of different options for for um for customers to consider so with that I think I will uh transition to the Q&A session we're going to move to sort of a a panel view with all three of us uh showcased here and um so I just wanted to open it up for a few questions hopefully Stephen and James have been able to catch a quick drink uh to answer some questions so we've got number of questions that have just come in and a few that uh came in throughout the the presentation um so just wanted to to highlight some of those specifically so we've obviously been focused a lot on investigations today um one quick NLP question um so one question that came in was really around sort of the the the customizations that have been built into the investigation solution with NLP so can um I guess I'll direct this to James James can you touch on some of the the entities or topics document types or skills that that have been configured as an NLP model for the investigation solution yeah absolutely um yeah as sort of we were discussing earlier as part of that that solution pack that comes with um the investigation uh solution uh We've developed a number of models uh so those are things like looking for um crypto value uh transactions crypto transactions crypto amounts we're looking for other things like Financial transactions as well financial documents um looking for indicators of fraud inside of documents or inside of emails or chat messages you know traditional of opportunity um pressure and rationalization so looking for those types of attributes inside of that that data so look to see if we can start to get ahead of um someone potentially committing uh fraud itself looking for things like the 419 scam fishing emails and a variety of other different s of aspects that are all associated with uh with fraud so those ones are specifically for the investigation solution and sort of sit on top of the the hundreds of out the box models and I know I've mentioned it a few times um mainly because I'm super passionate about it but I'll no code UI modeler allows you to build these build models like if you can drag files from your desktop uh into a browser uh you can build your own model uh you know your data best um so we can help you on that Journey with creating your own models or you can take the models that we built for you and tune them to your specific use cases fantastic Thanks James yeah so the other thing we talked a little bit about um was obvious was the unlimited processing capacity uh that newx Neo provides and the fire power that that enables to process data faster um Stephen can you talk a little bit about how that coupled with sort of the the process Pro you know search while loading works and how that really translates into a lot of benefits and value for for customers investigations yeah absolutely thanks Rick and so again I guess sort of Rick touched on a couple things you know pre prior to Neo if you had unlimited workers uh you were kind of on your own to automate their use on your on your own uh and so it's sort of a little bit of a slippery slope with Neo and the automation layer it is incredibly easier to add resources to a pool and then have nox Neo's automation layers automate the entire process orchestrate that process across however many machines you may have including do things like in AWS or Azure dynamically spin up new ec2 instances so you really have the ability to take advantage of the tremendous horizontal scale that available uh with the unlimited workers uh from there you sort of then think about okay well what other advancements and I don't think we've really touched on it is this idea of searching while loading you know so since I think 7.0 of the engine when we offered uh started offering elastic search as a backend that was the first opportunity that you could actually be interacting with a case while data was being processed and processing in this context uses I'm speaking to things like worker activity so loading data ocing exporting you know Imaging all those types of things with Neo there's actually something called The Derby service and with that Derby service does is it actually allows you to share and have simultaneous access to an Apache Derby Lucine case while worker operations are taking place so long-winded way of saying is that one of the biggest challenges that we sort of have had feedback over I need to be able to do two things at once on the same case is now a thing of the past so with Neo I can be loading data I can scale that out horizontally and I can be searching it while that data is being loaded so when we talk about sort of time to value and reducing the overall amount of time you no longer have to wait uh for stuff to happen you can also do things like case uh do a light metadata scan and then enrich that case so there are lots of ways in which you can leverage the Neo stack to really sort of get to those answers more quickly awesome Stephen yes so we've been we've been focused on investigations in this discussion right so that is one of the the solutions or modules available with newx Neo um this question is both for James and Stephen in terms of so what's next um what's the next solution that that newx is going to be releasing and how does that layer on top of nux as a platform and unlocking these different use cases on the same on the same platform yeah great question um I'll take a take a first run I'll let Stephen follow up but yeah the the the beauty of sort of the I guess to answer the first part of the question what's next uh so the the legal solution is next uh in terms of what does that timeline look like um we are starting to look for early adopters now and that you know releases within the next you know few months so it is very soon when we see soon um in terms of how does that work you know the benefit of as we continue to enhance the the Neo platform as that serves as a base for all of our Solutions enhancements to the platform sort of bubble up if you will into each of those Solutions so as we add you know new new file types new connectors new capabilities those all sort of manifest themselves in all of the solutions and then on top of those Solutions we're sort of layering on the like we talked about before those solution packs that really um sort of help identify the different aspects of those use cases pretty you pretty investigation solution we've got the knowledge graph being able to drive investigations there um Stephen do want to followup point no I mean I think really sort of one of the one of the key things about sort of like the neop platform is it really is a platform that allows us to start to think extensively uh you know if you think about the funnel slide that both James and I showed it starts with a lot of data and sort of winds up with insights that is a a a pattern that can be applied to lots of different things you know we started with data privacy and releasing investigations the next is legal you know you can easily see things like consumer complaints or other general purpose data and analytics processes you know so again for for newx and the journey through Neo it's really all about getting answers out of your data in a smart uh and intelligent fashion great great yeah so I've been looking over as you can see that we've had so many questions just come in I don't think we're going to be able to get to all of them um as we're trying to wrap up um so I think we'll just take one more question and I just wanted to make everybody on the call aware of how they can get all their questions answered um certainly you can reach out to me my name is Rick Barnard my email is rick. Barnard neck.com or you can reach out to your account exec that you currently work with but just wanted to wrap up with with one last question as we reach the t

2025-01-02 10:51

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