Rick Barnard: My name is Rick Barnard. I’m a member of the leadership team here in the North Americas, and I’m hosting and moderating today’s global webinar, focused on the introduction of Nuix Neo version 1. 3.
I want to first address a few housekeeping items. First, there is questions and answers available. You can submit your questions via the “ask a Question tab”. We will answer all those questions at the end of the segment or at the end of the presentation. We welcome all your questions, so please submit them throughout the presentation.
At the 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”. A recording will be available of this presentation and share it with you and we welcome you to share this with your colleagues, after the conclusion of the webinar.
Discussing today’s agenda, we’ll start with quick welcome introductions. So welcome. Thank you for joining us. I’m joined with two of my colleagues who are going to lead the presentation.
First, James Sillman, who’s the director of product management here at Nuix and Stephen Stewart, who is the America’s Field Chief Technology Officer. They will be discussing Nuix Neo, going into detail in regards to version 1.3 release, specific features and capabilities and enhancements that are available, and detail how those relate specifically to investigations use cases.
Then we will conclude with a pathway for those of our existing customers that currently use Nuix to Nuix Neo and the options that are available. We will conclude with questions and answers. So, at this time, I’d like to proceed and turn it over to James Sillman.
James Silman: James. Thanks Rick. As Rick said, my name is James Sillman and I work here at Nuix 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 Nuix customer before joining Nuix almost about eight years ago now.
So as Rick said, I just want to briefly introduce you to Nuix 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 Nuix Neo? Nuix Neo is our unified platform that helps organizations solve their most challenging data problems. A true end to end 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?
Customers today are limited by the number of workers they have. This causes constant trade-offs in priority and reduced delivery times. With Nuix Neo, we’ve eliminated this restriction with unlimited workers, so you can now process more data faster, reducing time to results.
Additionally, manual workflows. They are time consuming and error prone. 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. All so that we could maximize machine time and our workers.
Nuix Neo’s enterprise automation capabilities allow you to develop workflows that not only automate Nuix, but your entire enterprise. This ensures consistent, repeatable, defensible processing, minimizing machine downtime, and maximizing data throughput.
So, when we say easier, what do we really mean? Traditional tools, they’re very siloed in nature, you’ve only got one use of being able to access them at a time. Our web first approach and our collaboration tools are built into the platform, making it even easier for investigators to work together and collaborate and access Neo from anywhere.
Additionally, artificial intelligence is huge right now. Rightly so. It has the power to transform our workflows and make our lives easier. The challenge is it’s prohibitively expensive to hire data scientists and the tools that we have today that are available aren’t customizable and a bit of a black box. So, you don’t even know how it’s making the decisions.
With Neo, we’ve democratized artificial intelligence. Our no-code AI model builder allows anyone to develop their own AI models, within minutes, to 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 is customizable.
Additionally, our AI allows you to understand how the decisions it’s making are done and so you can easily defend the results. And finally, Smarter. I’ve already mentioned that you can build your own AI models with our no-code UI or you can leverage the hundreds of models that come out of the box. Our AI allows you to prioritize what needs to be looked at 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 risk 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 of this enables you to work smarter.
The Nuix Neo platform is backed by the Nuix engine and allows you to bring in over a thousand file types of unstructured data. However, Neo is a true end to end platform, 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 and Nuix 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 user’s endpoint or machines. Our threat detection and data protection capabilities as part of adaptive security or extensible SDK for you to customize the Neo platform.
I’m hopeful with this brief overview you can see that the Nuix 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 ensuring you can get access to your data anywhere.
We’ve expanded our forensic ecosystem. We’ve got new UK and Australian AI models to help to extract intelligence easier. And finally, I’ll talk to some of the existing Neo 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 uncover hidden patterns and connections in your data that 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’s worth a thousand words. So, a seemingly simple question, how are these two nodes connected?
Traditionally, this would be a painstakingly manual process, having 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 just start 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 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. Now, 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 Neighbours algorithm, and we’ve 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, the data all needs to be pre-processed ahead of time, with all those relationships defined up front.
Traditionally, this is done in a spreadsheet. It’s extremely time consuming and expensive because it’s a manual process. With Neo’s 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 tuned to solve your specific use cases. Our Knowledge Graph works seamlessly with Neo, being able to quickly send results back and forth, providing you with traditional review capabilities of the Nuix 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 are increasing at an exponential rate.
We know that there’s an increased pressure for organizations to deliver results faster, driven by the advantages and technology and the 24-hour news cycle. We know that organizations are being asked to do more with less and the skilled labour shortage is causing a backlog of cases. Our enterprise automation allows you to automate hundreds of steps, but not just across Nuix, across your entire enterprise, allowing you to collect, process, and push data review all automated.
Our enterprise automation comes with granular security controls that ensure consistency by preventing incorrect usage, predefined out of the box workflows to reduce time to value. All customizable 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 able 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 inception 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 guiding 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’ve distilled best practices when it comes to processing, automation, and review to take the guesswork out of it. These include things like default processing profiles, search filters, 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 about 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 in what matters most in your use cases.
Each of these solution packs is fully 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 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 and 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, ensuring 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 explore and review, saving you time and costs. And these are just really a subset of the connectors available within the Nuix 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 OneDrive is complex. Microsoft offers multiple ways to collect the data. There’s the graph, there’s Microsoft Purview, as well as traditional PST exports. It’s time consuming.
Manual collection has multiple steps, each requiring the user to sit and wait while each stage completes, moving on to the next. And error prone. These tools are confusing and lead to mistakes that can cause huge amounts of rework. All of this is in addition to the 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. 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 in mobile forensics. Once you’ve collected data in these various tools, our customers run into several challenges. You can’t search across your disparate data sets, which results in missed connections.
You can’t dedupe across tools, resulting in additional review and lost time. You can’t easily collaborate on complex investigations in these siloed tools. That’s why customers love the holistic view they get from Nuix. The ability to bring in data regardless of source. You can search, dedupe and collaborate all in one platform.
In this release, we’ve enhanced our support for ExpertWitness format, 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 tagging, into Nuix. This is on top of our existing support for tools like Cellebrite, MSAB and Hancom.
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 rejects, are fraught with issues. It’s complicated writing. Rejects is highly technical and error prone. This leads to lots of false positives or worse false negatives where you miss critical pieces of data.
By leveraging the AI capabilities in Nuix Neo. We’re able to reduce false positives as Nuix NLP understands the data. So rather than the system blindly assuming that any nine-digit number is a social security number, our language models understand the context. Is this a nine-digit number near someone’s name inside of a pay check? Probably a social security number. Is this nine digit number in a Guardian 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 PAI, PCI and banking data specifically for the UK and Australian markets. This is in addition to the hundreds of models we ship with today, each one customizable in our no-code UI with the ability to understand how AI makes its decisions.
Finally, I just want to touch on some of the key features of the Nuix Neo 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 of the box, including ones that are custom tuned for data privacy, investigations, and soon legal. This allows our customers to drastically reduce the time it takes to identify imported 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 OCR have finished to start to review your data. It 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 that 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 tasks like processing or OCR have finished to start to look at your data.
While it’s only available as part of Classic, now every Neo customer can review their data while it’s still processing.
We’ve made it even easier to onboard users to the Nuix 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 the complexity ease it brings; we’ve added support for RSMF that enables you to seamlessly bring in and export chat data. This enables for the interoperability between Neo and other platforms. And finally, Enhanced Promoter 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 subset of capabilities that we’ve introduced since the launch of Nuix Neo. I’m excited to hand over now to Stephen Stewart, who’s our field CTO, and he’s going to talk to you about our NEO our NEO investigation solution.
Stephen Stewart: Thanks, James. I’m excited for the opportunity to talk to everybody today. Again, James, that was an excellent overview of, of Neo and how we’re thinking in a broader sense about the Neo platform. In a really grounded a couple of fundamentals, around faster, smarter, easier and solutions.
To get us started, I’m sure, many of you know me, my name is Stephen Stewart. I am Nuix’s chief technology officer or field chief technology officer. I’ve been around Nuix for close to 16 years at this point. I’ve really have spent my entire professional career in the document management, archiving, discovery, investigations, and big data space.
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. 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.
As you start with those basic questions, and you expand that out into all of the disparate data types that our investigators are confronted with on a daily basis, across the thousand different file types and the 10 dimensions of data and all those different things, the goal is the same.
You’re really very much trying to just understand what happened. Pull those pieces together and really get a true sense as to exactly what happened when and where. That’s no more prevalent than the amazing work, that all of our customers and partners are doing out there in the wild.
I take tremendous pride at being at Nuix over the years and understanding our software’s relationship to tremendous events that have made the national stage. It’s interesting to be asked questions and say one year and then several years later, understand the nature of that question.
In the top left, mob storms the capital, that’s January 6th here in the United States. Some number of months after that, I was asked a 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?”
The answer was, yes, we have an image classifier, it does these specific things, here’s how you might be able to use it and they were like, okay, great. And then that was all we heard. Then come back a year later and they’re like, “Oh yeah, we use the engine and the image classifier”. We were looking for flags and it was this great experience, it cut us from like 6 million images down to like 100, 000 that we had to look through and it was fantastic.
Similarly in the upper right operation Ironside, a global law enforcement engagement. Several years before it was made public, I had a random question about, “Hey, what if I put 12, 000 mobile phones into the Nuix investigate canvas. What would happen when it basically all of a sudden would it tip over? Would it work?” And I was like, I don’t know, 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. The reality is it’s out there and you guys are working with tremendous volumes of data trying to solve that. At the end of the day, it comes down to crunching through some numbers that the scale and complexity of large investigations is increasing. Not only is it the size and scale of the investigations, but it’s the dollars that are involved.
The UK actually estimates 219 million billion dollars could be lost associated with fraud. That’s just a staggering number and that’s just within the UK. In the US it’s anticipated to be closer to $364 billion. 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 lost associated with fraud.
The problem is, is that it’s very difficult to investigate. Some research says that there’s up to 25, 000 plus devices in the backlog. Again, this is the basics of how do you hit the singles to accelerate the investigative process? How do I allow organizations to work through their backlog more quickly and more efficiently?
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 work faster, smarter and easier. Not to mention the idea that within that there’s such a small amount that’s actually being investigated. You take that backlog; you take the small percentage relative to something like the 40% of number of matters or crimes that are needing to be investigated.
We’re facing a global investigative crisis and we’re basically falling further and further behind. So, in order to start to think about that you have to think about how do you scale and scope and approach your investigations. High volume, low complexity in one corner, low volume, low complexity in the other. And then in the upper right, you’ve got the high volume, high complexity.
High volume, high complexity 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 what is that high volume, high complexity? Is that only the top tier serious and organized crime, the multinational aspects, all of these other elements, what is it that characterizes that?
So, when you think about it, you could actually roll back the clock on one of the very first and largest investigations. In law in UK law enforcement into basically one of the earlier serial killers, Peter Sutcliffe, the data was incredibly complex.
There were over 250,000 people were interviewed, 32,000 witness state statements taken and 5. 2 million car registrations checked. As that investigation took place, they generated so much paper that they 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 trying to figure that out. If you now roll that forwards and start to think about basically a single mobile device. The one that each of us probably has in our pocket, maybe 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 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. You need to be able to feed it into a system that will allow you to do index processes, extract that information and get to those outcomes as quickly as possible.
We take that step back and we think about Nuix Neo and solutions this industry has known Nuix for decades as one of the leaders in digital investigations. Really the sweet spot of where Nuix excels is around the complexity of being able to pull lots of different data, disparate data sets together.
James in the feature overview of Neo mentioned being able to pull in data from Magnet cases or eyewitness cases or other auction mobile forensics. The ability to aggregate and roll up data collected from all different sources, Purview, Google, mobile phone devices, you have the arts, etc. To be able to present it into a single view is really what differentiates Nuix and the Nuix Investigation Solution. Going from labs, smart labs all the way up.
But when you think about life cycle of a typical investigation. How do I start to think about reducing that time window? You see the longest bar there, the DF, digital forensics and investigation. That is basically the long pole 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 the legal? Within that, there’s a huge amount of repetitive process and the key thing 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, by being able to 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 well understood and easy to manage.
So, with that, you take that idea of what is available and then what is being done by organizations are out there. Police Scotland are great testament of what they can do and how automation can dramatically improve the process. 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 all of the other ways in which they can expand that automation and take it to the next level in and around, adding AI into their workflows and other things.
Vodafone on the other end went for no backlog with 99 percent processing. This way, these organizations are essentially chewing through that device backlog, that we heard about a few minutes ago, of about 25k devices. Starting to work through the automation, making it faster, smarter, easier. Is really at the heart of what Neo is designed to offer. And so, when we talk about Nuix Neo, specifically Nuix Neo Investigations, it’s about “how are we thinking about taking these investigations to the next level?”
People have used the Workstation and Investigate, and they have built labs, and they’ve scaled it out and managed it. 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. Those automated case specific workflows are very much about how can I take every investigative bit of intuition that each of your investigators has and memorialize that into a specific workflow step?
How can I then repeat that every single time such as when it’s tagged and processed, etc? How can I then scale that out horizontally so 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 that last bit around greater insights through the link analysis.
At the end of the day, it all comes down to where James started about being able to take huge volumes of information and drive that through to data insight as quickly as possible.
Those data insights 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 a risk scoring associated with those items? Pushing that as part of the Neo platform and Investigations is really what we’re driving here today.
When I think about what does it mean around driving this from the bottom up with investigations, it’s how can I think about taking the Nuix Neo Investigative Solution and thinking about larger, more complex investigations and all the people that need that. We’re talking about public and private sector. We’re talking about regulatory investigations. We’re talking about fraud and a national or global scale. We’re talking about serious and organized crime.
In each one of these individual layers, they are building up to deliver elements of fraud. If you can start to understand how fraud and how that money flows across all of these and the hidden relationships, you really can start to see how the overall Nuix Neo platform and our specific focus on fraud for investigations can drive tremendous acceleration across all of your investigations.
So, back to the faster, smarter and easier, and we really reiterate this because by being faster, smarter and easier, we think we can provide tremendous value. That tremendous value is pretty simple. How can I get more data through more quickly? How can I work through my backlog? How can I start to handle data in real time?
So, we start to think about some of the added capabilities around. It’s the real time analysis. So, many of your use cases may deal with collected or static evidence. Others of you may want to be able to stream license plate reading information, other financial transactions or other third-party information into the system so that it can be correlated.
One of the most exciting things about Nuix 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 further inform your investigation. Ask those simple questions about how far away is this from a known bad transaction or a known bad actor?
All about making things faster, and easier. When we think about easier, easier is all about getting through the work with less friction. So how do I make it easier? I make it easier by automating the process. As I’ve said, I’ve been at Nuix for 16 years and in those 16 years, I’ve pushed a lot of buttons on workstation.
I’ve also done 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, 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 twenty-four by seven 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, automate those workflows and drive that. Let’s just say, I could have gotten a lot more sleep over those 45 days if I’d had Nuix Neo today.
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 build AI models using our no-code user experience. I can interoperate with a seamless web-based user experience that I can single sign on across my various things, kick off my jobs, get email notifications. All of these things are about making this process much easier.
The last bit is around smarter, so faster, smarter and easier. When I think about smarter, obviously you want to work smarter, so things like automation, scaling that 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?
So, depending on your use case, here today we’re talking about investigations, we focused a lot of our time and attention around fraud. Things like identifying financial transactions, looking for financial documents, ledgers, all of those types of things, and basically being able to effectively pre-tag those.
If you think about 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, be it fraud, be it serious organized crime, 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-tag, pre-tune and push that information forward as you start to think about it. When you start to understand and elevate those scores. Again, that idea of faster, smarter and easier.
What drives that is really the enrichment. So, when we think about the workflow, the data rolls through the Nuix engine, text and metadata are extracted. It’s been pushed back into the Nuix case when it’s pushed back into the Nuix case, it becomes searchable across all of the Nuix aspects. So, you can search it from workstation. The engine Investigates via the API. You could promote that information out to Discover and you can promote it out to other third parties.
So, by enriching those individual items with classifications, categorizations, facts that have been extracted, prioritize around risk scoring, and then help you visualize this it really allows you to work much smarter.
One 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? We had someone yesterday asking us about trying to be able to use these classifications to rule out garbage. They were tired of looking at help files.
So, they said can you build a model for that? Sure. That’s really easy and one of the most important things to make it easier is the no-code model builder. The no-code model builder allows your subject matter expertise to take, tune, and even augment our existing models, but then easily build new models from scratch.
Nuix’s and Nuix 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 reliant on using analytics to accelerate how you review documents.
We’re using AI to accelerate what you look at first by telling you what it is. Each one of these elements is stackable, so they basically accumulate value as you go through.
If I talk about, what is a document? And then I ask the question, what is this document about? Is it about sports? Is it about politics? Is it about terrorism? You can then use these layers to start to pull different information together and start to think about how can I take and tune. So, as it relates to things, within the Investigation Solution packs 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, and it’s not just keywords. It’s using the vectors in the contextual information to really start to understand how that information works. You then take that next step and you start to think about extraction. So how can I extract this information in a meaningful fashion?
This is what James was talking about. The idea that regular expressions and false positives are worse than false negatives. Anybody that’s ever tried to create a regular expression for a social security number and doesn’t want to miss anything. That’s pretty dicey. You can basically pull in every single nine-digit number out there.
But what you can’t do is contextualize it. Well, at least until now, with Nuix’s cognitive expressions. What this allows you to do is take a whole bunch of regular expressions, or easily add in your own. Some of the work that we’ve done with the release of Neo 1.3 is we’ve started to dial in those regular expressions and cognitive expressions for the UK and Australian markets.
We started with the US market, so we have a robust base, and we’re now augmenting them around different things like UK driver’s license or Australian identification cards to ground them.
The value of the cognitive expression, which is the other part of the fact extraction piece, is how do I then say, what contextual information around this lets me know that this is a social security number? Is it something like SSN, or is it 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. This contextualization and this fact extraction is really what drives our knowledge graph expertise.
For years, we’ve been talking about how to do this better. Through the addition of NLP and our context aware entities, we are really able to nail a highly reliable and curated knowledge graph. So, I’m going take that, I can understand what the document is, I can categorize it, I can extract the information out of it.
The next thing is how do I start to think about prioritizing. Prioritization goes to things like risk scoring.
So, in each one of those instances, let’s take, for example, a US tax document. A US tax form, let’s say a blank W2. It’s not that interesting, but I would like to know what it is. If I have a populated, that means W2 form that has PII and PHI. That is more interesting, that is more potentially risky.
If I have a PDF file that has a hundred pages of W2 forms and a hundred 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 Classic search and tag to basically be able to bubble that information up to the top.
This idea of really being able to drive that and push it forward to understand what needs to be looked at first. 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.
As we start to go through the multidimensional text analysis, is then how do you pull this stuff out? That idea of running all of these systems under the hood, to really then drive it to, hey, look at me first.
So, when we get to the, hey, look at me first, we’ve actually built in logic that applies this, bubbles this stuff up to the top. So, as your investigators land in Nuix in the the web application, the Investigate, they can immediately go and look at this stuff first.
So, taking our knowledge, our experience, working with subject matter experts in the industry to really help and drive that prioritization, delivering dashboards that allow you to accelerate and understand that information and most importantly, prioritize.
When we thought about that fraud timeline from a couple slides ago, it’s all about how can I compress time? Not only how can I process the data faster, but once I process that, what can I do to it to enrich it to basically point the investigators to look here first. Instead of having to start from A and go to Z, 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, if we can point them to what they need first, through AI automation in a consistent, repeatable, defensible fashion with all of the other aspects around explainability, specificity and transparency in our AI. These are all really valuable elements that help you get to that answer more quickly.
The last piece, and James touched on this, is really how you start to think about understanding and visualizing this information. James touched on the knowledge graph. The knowledge graph, for me, is an incredibly exciting advancement in our technology. In practice, we’ve tried it in the past using things like regular expressions to drive a knowledge graph. Or we’ve created a knowledge graph based purely on communications data so To, From, Cc, Bcc.
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 how is Stephen Stewart related to Keyser Soze? My favourite fictional bad guy.
Before, as James said 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 redoing documents.
Wouldn’t it be better if I could basically feed all of that information into the Nuix Neo engine. Extract that information, normalize it and then create a highly curated knowledge graph. That highly curated knowledge graph has well defined nodes and edges. A well-defined schema that can be targeted directly from the engine or targeted through NLP, so that you can start to build that information up and really start to visualize how this information is connected.
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 Nuix Neo Investigations, we’ve got the smarts, we’ve got the engine that could extract that text and metadata. We’ve got the schema and the playbooks. That allows us to define and drive a really accurate and highly curated knowledge graph.
When we think about a little bit of a recap, within the investigation solution, the idea is to make it so that you can just add data. We’ve got the solution pack that includes targeted investigative NLP models, targeted things for extraction of PII and PHI, metadata profiles, processing profiles, workflow, automation, steps, visualizations within and dashboards within Investigate.
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 case. Really take this solution framework to the next level and beyond.
It’s all rooted in our core tenants of Nuix Neo. 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, resource, the desire to actually get home and see your family. All of those things can be facilitated through better automation, easier user experience, how can I get you to those answers more quickly?
Whether you’re in the lab trying to process that data and get it prepped, or you’re the investigator trying to answer time critical and sensitive investigative requirements. It’s how can we get the right data, in front of the right people, as fast as conceivably possible.
So, with that we really are on the journey. The people that are here today, you guys are definitely on the journey to Neo with us. You’ve been a part of the Nuix Neo and Nuix investigations and how can we think about taking you from where you are today into what we think is an amazing way, to accelerate your outcomes and really ultimately get to those answers much more quickly.
With that, I’d like to turn it over to my colleague, Rick Bernard, to take you through the pathways to NEO.
Rick Barnard: Stephen, thank you so much. Also, James, appreciate it. Great discussion and overview. I’m going to conclude the discussion with options for any customer, including existing customers, on our journey together, to NEO. Then we’ll open it up for Q&A. So, if you’ve had any questions throughout this presentation, take the time now to submit your questions, and we will address them in just a couple short minutes.
I’ll start with the bottom. So, that’s the foundation that we’re building on. Nuix, that you’ve been using for decades, our Classic capabilities. You can continue using those. The Nuix engine, you can build around it, you can augment with, third party products or automation with Nuix automation and EVA to enhance the workflow end to end, from collections to processing, all the way to review.
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 workflows, your playbooks, your visualizations, your reporting, and build on that to bring enhancements on our journey together. The second option, that we’ll build off of that, is what we’ll call the pathway to Nuix Neo, which, is to extend and enhance.
That gives you unlimited cores, it boosts your productivity, we start building templates and playbooks together. Some of the same elements that I just talked about with extensions from Legal Hold to Purview collections. That gives you access to Nuix’s tailored Advantage offering which is a customer success journey to allow you to unlock the full capabilities of Nuix Neo platform as we move to more usage-based licensing model, also available with Nuix Neo.
The third option is to go to Nuix 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 solution. It has all the configured workflows, all of the customized NLP models and user profiles to really unlock the power of the Neo platform.
We’ve talked a lot about that, in the last 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.
Whether you’re ready for Nuix Neo or you want to build a pathway to Neo, we have lots of different options for for customers to consider. So, with that, I think I will transition to the Q&A session. We’re going to move to a panel view. With all 3 of us showcased here and so I just want to open it up for a few questions.
Hopefully, Stephen and James have been able to catch a quick drink to answer some questions.
We’ve got a number of questions that have just come in and a few that came in throughout the presentation. I just wanted to highlight some of those specifically.
We’ve obviously been focused a lot on investigations today. One quick NLP question. One question that came in was around the customizations that have been built into the investigation solution with NLP. I’ll direct this to James. James, can you touch on some of the entities, topics, document NLP? That have been configured as an NLP model for the Investigation solution.
James Silman: Yeah, absolutely. We were discussing earlier as part of that, that solution pack that comes with the investigation solution. We’ve developed a number of models. Those are things like looking for crypto value, transactions, crypto transactions, crypto amounts.
We’re looking for other things like financial transactions as well, financial documents. Looking for indicators of fraud inside of documents or inside of emails or chat messages. Traditional opportunity, pressure and rationalization. Looking for those types of attributes inside of that data. Looking to see if we can start to get ahead of someone potentially committing a fraud itself.
Looking for things like the 419 scam, phishing emails and a variety of other different things. Aspects that are all associated with fraud. So those ones are specifically for the investigation solution and sit on top of the hundreds of out of the box models.
I know I mentioned it a few times, mainly because I’m super passionate about it, but our no-code UI model builder allows you to build models. You can drag files from your desktop into a browser, you can build your own model. You know your data best, 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.
Rick Barnard: Fantastic. Thanks, James. The other thing we talked a little bit about was the unlimited processing capacity that Nuix Neo provides and the firepower that that enables to process data faster. Stephen, can you talk a little bit about how that coupled with search while loading works and how that translates into a lot of benefits and value for customers investigations.
Stephen Stewart: Yeah, absolutely. Thanks, Rick. Rick touched on a couple of things. Prior to Neo, if you had unlimited workers, you were on your own to automate their usage and so, it’s a little bit of a slippery slope.
With Neo and the automation layer, it is incredibly easy to add resources to a pool and then have Nuix Neo’s automation layers, automate the entire process and orchestrate that process across however many machines you may have. Including do things like an AWS or Azure dynamically spin up new EC2 widths. So, you really have the ability to take advantage of the tremendous horizontal scale that’s available with the unlimited workers.
From there you then think about what other advancements, and I don’t think we’ve really touched on it, is this idea of searching while loading. So, since 7.0 of the engine, when we started offering ElasticSearch as a back in. That was the first opportunity that you could be interacting with a case while data was being processed. Processing in this context I’m speaking about things that use worker activity. Loading data, OCR-ing, exporting, imaging, all those types of things.
With Neo, there’s actually something called the Derby service, and what that Derby service does is it allows you to share and have simultaneous access to an Apache Derby Lucene case while worker operations are taking place.
So, a long-winded way of saying one of the biggest challenges that we have had feedback over, needing to be able to do two things at once on the same case, is now a thing of the past. With Neo, I can be loading data, I can scale it out horizontally, and I can be searching it while that data is being loaded.
When we talk about time to value and reducing the overall amount of time, you no longer have to wait for stuff to happen. You can also do things like do a light metadata scan and then enrich that case. There are lots of ways in which you can leverage the Neo stack to really get to those answers quicker.
Rick Barnard: Awesome Stephen. We’ve been focused on investigations in this discussion. That is one of the solutions or modules available with Nuix Neo. This question is both for James and Stephen in terms of what’s next? What’s the next solution that Nuix system you’re releasing and how does that layer on top of Nuix as a platform and unlocking these different use cases on the same platform.
James Silman: Great question. I’ll take this one first and I’ll let Stephen follow up. To answer the first part of the question, what’s next? the Legal Solution is next. In terms of what does that timeline look like? We are starting to look for early adopters now and that releases within the next few months. So, it is very soon when we say soon.
In terms of how does that work? As we continue to enhance the Neo platform, which serves as a base for all of our solutions, enhancements to the platform bubble up into each of those solutions.
As we add new file types, new connectors, new capabilities, those all manifest themselves in all of the solutions. Then on top of those solutions, we’re layering those solution packs that help identify the different aspects of those use cases which pretty the investigation solution. We’ve got the knowledge graph being able to drive investigations there. Stephen, do you want to follow up on that?
Stephen Stewart: I think one of the key things about the Neo platform is it is a platform that allows us to start to think extensively. If you think about the funnel slide that both James and I showed, it starts with a lot of data and it winds up with insights.
That is a pattern that can be applied to lots of different things. We started with data privacy and releasing investigations. The next is Legal. You can easily see things like consumer complaints or other general-purpose data and analytics processes. So, for Nuix and the journey through Neo, it’s all about getting answers out of your data in a smart and intelligent fashion.
Rick Barnard: We’ve had so many questions that have just come in. I don’t think we’re going to be able to get through all of them as we’re trying to wrap up. 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.
You can reach out to me. My name is Rick Barnard. My email is rick.barnard@nuix.com, or you can reach out to your account exec that you currently work with. I just wanted to wrap up with one last question as we reach the top of the hour. Obviously, investigations are very complex. We integrate with lots of different solutions to make that possible.
Just wanted to open up to James or Stephen in terms of what third party integrations you think are super valuable, that we haven’t talked about. That support image analysis, translation or transcription services that are really supporting the most complex investigations that we’ve been talking about today.
James Silman: In terms of services that we haven’t touched on that for investigation specifically, we’ve got several different partnerships. Passware, we partnered with them for a while now, that helps us to decrypt disk images. We’ve got a partnership with T3K, that’s image analysis capability. Partnering with Veritone to provide transcriptions and translations. We’re looking further ahead as well.
We know that media analysis is critical to the investigations and we’ve got some of that, and Stephen’s already touched on that. But we are looking ahead to see how we can more tightly integrate that into the new ecosystem. So regardless of whatever data you bring into our platform, regardless of where it comes from, disc images, Cellebrite data, Magnet cases, being able to search across that in a holistic way is the direction that we’re going.
Stephen Stewart: James, you’ve picked up on the main ones as it relates to an extending investigation. I think in terms of always being able to define a pattern that allows us to handle the what’s next. So, by being able to think about handling the what’s next, either in real time through feeding the data in by Kafka.
Basically, containerising and packaging it into a Nuix logical image file format. The platform itself allows us to consume this information, enrich the items within the Nuix case. Then once it’s enriched inside that Nuix case, it’s been available to all of the other services that are part of the Nuix ecosystem.
Send it downstream, push it out to Discover, access it from Investigate, from Workstation, through the APIs, and build custom reports on top of it. So, for me, the heart of the investigative ecosystem really becomes the Nuix case.
I saw one question pop through, the Nuix case is a self-contained database, it doesn’t rely on a third party external for someone who is new to the Nuix world. But again, it’s just about being able to build on top of the Nuix platform and shove as much data into it as you can to make it searchable and basically drive outcomes and insights.
Rick Barnard: Stephen, one last question. You touched on Kafka. Can you talk about some of the emerging real time investigation use cases or just real time processing that can be enabled with the Nuix platform using Kafka and those types of Services?
Stephen Stewart: So, it’s really just another entry way of getting data into to Nuix.
Some of the advancements in Neo around being able to connect to Kafka means that we can consume JSON, consume web links, and reach out to those URLs. We can also sit and listen to financial transactions. Obviously, you have to tell them about us. It’s not like going in the back door or look for license plate scans.
Essentially, any data structure that allows us to connect Kafka to it can now be flowed into the Nuix engine. We’ve had use cases around customer complaints, where organizations are trying to track different web-based systems.
They’re not necessarily traditional emails, but they have an element of what it feels like a communication and flow this in. The great thing is once you flow that data into the Nuix engine, you can investigate it alongside all of your other traditional data. Your team’s data, your email data, your mobile digital forensics data.
The whole idea of Kafka is being able to add a new, less batch mindset to how you get data in and start to open the door to new use cases that we may not even have seen yet. That idea of it’s not just a batch of data that sits on a share, but being able to interact in real time with databases and being able to drive that data in allows for tremendous power and correlation.
Again, you take all of those elements around analytics for classification, categorization and fact extraction. Layer that with search, but now the knowledge graph, you have a huge opportunity to start to understand hidden relationships across all of your investigative data, maybe you’re conducting enterprise investigations, law enforcement style investigation.
All of a sudden, what you can do with the system elevates.
Rick Barnard: Fantastic. Well, James, Stephen, thank you so much and thank you all for, for attending today’s webinar. We have recorded it, and we will share this recording out to all of you. You can share with your colleague and again, I’m sorry we didn’t get to all everybody’s questions.
Feel free to reach out to us. We’re happy to answer each and every one of your questions. Continue this conversation and continue the journey together. Thank you so much for joining. Have a great rest of your day.
