Carahsoft’s webinar introduced Eightfold AI, a FedRAMP-authorized and CDAO IL4-certified talent intelligence platform. Eightfold uses proprietary deep-learning neural networks to analyze over a billion career trajectories, deriving more than a million unique skills and roles. The platform integrates with existing data systems, providing granular insights into individual capabilities and organizational competencies. Key features include rapid talent acquisition, personalized employee development, and efficient resource management. Eightfold’s AI-native architecture allows for dynamic, contextual data analysis, enhancing hiring efficiency and employee engagement. The platform also supports succession planning and long-term workforce readiness.

• Brian Turner is an account manager at Carahsoft supporting Eightfold.
• Carahsoft has secured numerous government contracts for streamlined acquisition processes.
• Carahsoft offers specific state contracts and purchasing cooperatives for state/local government agencies.

Competition

• Eightfold’s AI is native, unlike other major enterprise HC systems that retrofit AI.
• Eightfold can process unstructured data from disparate sources, unlike other platforms requiring pre-configuration.
• Traditional HR systems need to retrofit AI, while Eightfold was built with AI from the ground up.

Objections

• The question of fair hiring practices was addressed, highlighting Eightfold’s bias mitigation strategies.
• Data security concerns were addressed by mentioning FedRAMP and IL4 certifications.

Questions

• What is the difference between native AI and other major enterprise HC systems?
• What are the key benefits of Eightfold’s FedRAMP and IL4 certifications for agencies?
• What kind of data does Eightfold need to start delivering value for an agency?
• How does your AI ensure fair hiring?
• How does Eightfold AI determine which candidates are best aligned to a role or mission need?
• Can Eightfold help with succession planning or long term workforce readiness?

00:01
Jacqueline: Good afternoon, everyone. My name is Jacqueline. On behalf of Carahsoft Technology, I would like to welcome you to our webinar, “Eightfold is mission-ready: Certified, secure and available for government.”

00:12
Brian: Thank you. Jacqueline. My name is Brian Turner. I’m an account manager at Carahsoft supporting Eightfold, I help educate the public sector on the Eightfold platform, capabilities and offerings that are available to meet your needs. Carahsoft has an enormous partner ecosystem with more than 4000 organizations, which include industries leading, manufacturers, government contractors, resellers, as well as system integrators, and to deliver those products and services to you all. Carahsoft has secured numerous government contracts. Each of these that are on the page here offer a streamlined process for acquisition, because their pricing is pre approved, the terms and conditions have all been negotiated, and they ensure compliance with federal regulations so our federal civilian and Department of Defense customers can purchase off of any of these three state local government and education as well as nonprofit organizations can also purchase off of our GSA multiple award schedule, but we do offer specific state contracts as well as purchasing cooperatives that those agencies may be able to purchase off of we’ve also listed the trade winds solutions marketplace. This is the Department of Defense’s digital environment of post competition, readily awardable technology solutions. So Eightfold AI has been vetted and approved for this. It just validates what they offer to the Department of Defense, and that’s available for you all.

01:56
Thanks, Brian. And with that, I like to introduce our speakers for today, Michael Perlstein and Ryan Kirkpatrick, we will be launching polling questions throughout the webinar, so please stay engaged with our polling questions so we can best receive your feedback. And with that, like to pass to Michael.

02:12
Thank you. Jacqueline, I am Michael Perlstein. I’m with Eightfold AI.

02:21
I’ll provide a little bit of background and go through a couple of slides just for context before turning it over to Ryan, who’s going to provide some real insights into the tool. Eightfold is a FedRAMP authorized and DISA IL4 certified talent intelligence platform. We’re currently supporting the federal government. We have multiple engagements, including some active engagements on a joint program with the DoD that actually supports all of the service branches.

02:55
And we’ve supported federal civilian as well as as a talent intelligence platform.

03:00
Our aim is to help support agencies streamline processes associated with talent acquisition, talent management, resource management, career pathing, and this achieves more rapid hiring, better internal deployment, more predictable results, better fit for the role. We achieve this using AI. We have a proprietary deep learning AI that we developed really with the intention of the idea of helping everybody find the exact right career for for them, that’s an ambitious goal. And AI are our proprietary AI is helping us achieve just that. We have a number of patents in this space. The one I like to focus on specifically is on predicting candidates most likely to succeed in the job.

03:53
We accomplish this in part by focusing on skills, skills in the context of work.

04:04
The skills live in the people. It’s kind of the currency for the people. And you know, when you look at the left, that’s people map to jobs, or job descriptions. And the challenge with that is that skills don’t live in job descriptions.

04:21
On the right is where you see how our AI functions. It it maps skills to people in the context of work, looking at what what work needs to be accomplished, and what skills are within the organization or within the applicant pool that actually map to that work that needs to be taken care of.

04:42
And so that’s from a high level, what our AI does. And it is true, skills based hiring.

04:55
One example is, is a current program we’re supporting called GigEagle within the Department of Defense and the DoD had a real challenge.

05:00
They have at any given time, 800,000 to a million reservists, National Guards, members who once they’ve left active duty, the DoD loses insight into any new skills they develop, or anything they learn through active engagements in the commercial space.

05:22
Meanwhile, they have a lot of work that needs to be accomplished, and what they were looking for was a tool that could rapidly scale and provide insights into their existing reservation, guards, guards people’s skills and quickly map them to tasks that need to be accomplished. And some of these gigs are shorter term, a few months. Some of them are upwards of a year. But the Department of Defense chose Eightfold to deploy GigEagle, which gives them real time insights into all of the skills they have and able to provide a clear mapping to the work that needs to be accomplished. And so that’s one example of an active program we have right now. Or the Department of Defense is taking advantage of AI that helps them accomplish true skills based hiring.

06:28
And I think this would be a good time like to introduce Ryan, who can give you a little bit more background on our AI, how it functions, how we’ve put it together.

06:37
Ryan: Thank you very much, Michael, and thank you all for joining today. So AI is obviously a pretty hot topic these days, and I think one of the key aspects to walk through today and give you a high level understanding of is what kind of AI does Eightfold actually use, and why does it matter? So Eightfold actually uses a combination of lots of different types of artificial intelligence, but at the central component is our proprietary deep learning neural networks. What that enables us to do is accurately learn from a tremendous volume of information. So Eightfold was founded by some of the world’s preeminent data scientists, and what we cared about the most in the early days was making sense of the messy world of data about work and workers. So by studying more than a billion career trajectories. You can think of those like career arcs, right? How do people move from one job to the next over the course of their careers? How does that differ within a particular organization or within a particular agency? How do people move inter agency or inter organization? How does that matter in terms of things like industry association? So all of those different groups of data essentially provided us with a rich body of information to do deep analysis, and we were able to derive more than a million unique skills. It’s actually closer to a million and a half now, as well as almost a million unique roles and job titles, more importantly, the connections between those things, and we’ll talk about that in more detail in just a minute. Now, when we work with an individual organization as a client, we then also integrate with your existing data systems. Now these are some examples of typical systems in contracting space, commercial space, obviously, government agencies typically have in house systems as well. What we’re interested in is learning as much as we can about the work that needs to be done and the people that exist within those individual organizations, and we can essentially provide the same type of analysis so that we can learn specifically what is important to you when it comes to capabilities to execute on different bodies of work, what are the competencies that are actually embodied by the individuals that make up your organization? And then once we’re stood up and live, we continue to learn by the usage and outcome of the platform. So as you are making decisions, deploying people in particular projects, hiring folks, deciding to separate with other folks, those actual interactions teach us essentially how decisions are being made, and we’re looking at the underlying skill relationships and capability relationships that travel with those outcomes and decisions. So what is it that separates individuals that progress more quickly than their peers or receive lower performance reviews than their peers? For example, all of those data signals help us understand what the connections are that are unique to your individual organization. So what this really drives is both a very granular understanding of individual capabilities and the ability to really power specific experiences for different user groups that are meaningful to them. So some examples of this, if I’m a job seeker trying to find the most appropriate open role for myself at your organization. Imagine being able to simply match my current CV or my current resume or my current LinkedIn profile against all of the different requisitions that exist at the organization and show me the ones that are actually the best fit for my skill set Eightfold. Can do that if I’m actually an employee and I’m trying to understand what might be next for me.

10:00
What sort of roles exist at this organization that I could move into? What do I need to learn in order to be more prepared to take that next step, Eightfold, can provide insight into that as well matching people against learning content or mentoring opportunities and connections, for example, it also gives you a broad based intelligence at an organizational level. So being able to understand what is the overall landscape of skills and competencies and capabilities at your organization, how does that compare to what is happening outside of the organization? Are we essentially keeping up with the Joneses, if you will, when it comes to capabilities and skills required for certain bodies of work, there’s a lot of capability within Eightfold to do that as well. So to give you an idea of how we put this into place for practical applications, you can think of Eightfold data analysis as essentially the foundation.

10:47
So it’s a little counterintuitive here, but we’re actually going to start from the bottom up. So if we look at what we just spoke about, the data sets, publicly available data, your own organizational information, and the ongoing user interactions, we’re constantly learning from those things, the actual analysis and the contextualization and all of the data protection, all of the anti bias practices and testing that we put into place exists at the platform layer. So if you’re using any component of an Eightfold solution, you’re going to be using our native talent intelligence platform. Now why do we say AI native? It is actually built from the ground up on a core of that deep neural network understanding and capability. So every time Eightfold makes a recommendation or analyzes information we’re doing so using embedded deep learning, neural network, AI, in addition to, again, all the things that power it. So under the hood, there’s machine learning, there is decision trees, there is natural language processing, there’s all kinds of fun stuff that we’d be happy to get into the weeds on with your data scientists as well. But the goal is that, I guess the real point is that the system was built on AI for AI, so it really understands the capabilities of data at scale, and it’s constantly learning from new information. So it’s a very dynamic foundation, whereas most systems within the HR space, especially are not organizations are trying to bolt on AI solutions to systems that were not designed to handle dynamic information. They’re typically systems of record that do very well with static information. So there’s a mismatch there in terms of capability. When we think about the universe of skills, it’s constantly moving. It’s constantly changing, just like the real universe, right? When we try to flatten that and make it one dimensional to fit into a tag or a data field, it doesn’t carry as much power. It doesn’t carry as much nuance. And we’ll show you what that actually looks like in terms of data in just a moment. So that’s a key area that we have differentiation that actually provides distinct value. Being able to use the dynamic relationships between skills and talent allows us to power specific, practical applications that simply drive better results than anything else that’s available. And I know that’s a strong claim, but we’ve got the case studies to back it up. So when we think about talent acquisition, imagine cutting your time to identify the talent that you interview by more than 90% so instead of spending 10 days before you move to interview, imagine doing that day one. That’s actually what some of our clients, like Bayer pharmaceuticals, are doing today. When we think about being able to assess candidates in real time, offer them the availability to interview immediately. That’s the type of thing that talent acquisition can do today. Talent management is really interesting because obviously it’s about empowering the employee journey and making sure that folks are growing, making sure that we understand not only their capability, but also their intention and their interests, so that we can serve up the appropriate learning, development connections, all of the different things that keep people happy and engaged, not only in their current work, but also, moving into the future, there’s a tremendous amount of capability to make sure that that employee experience is optimized, which obviously benefits the organization as well. And then there’s a resource management layer, which is around making sure we identify the most appropriate talent to place against project work. So when we think about deploying individuals for particular role on a project team. They’re not necessarily changing jobs, but we still very much care about their skills and capabilities and competencies to do the work effectively. This is going to also take into account time. Are you available to do this work? Are you coming off of another project, et cetera. So these are some of the core modules or capabilities that will give you a little bit of a high level sneak peek into today. And then there’s additional capabilities that we can talk to in the future if we want to dig in deeper with us, around actual execution of work.

14:49
So leveraging agentic artificial intelligence as well as generative artificial intelligence, to make doing the work faster, easier and more efficient.

14:59
So if you’re going to take a screenshot and has a great time, this is a great area to say, you know, we might want to talk about these other areas in the future with you, we certainly welcome the opportunity to do that with you as well. But without further ado, I’d actually like to bring you into Eightfold. So welcome. This is we’re going to start off with the talent acquisition piece, and then we’re going to back into the engine under the hood, and then we’ll give you a sneak peek of the talent management component and the resource management component, as well as a little, again, insight into some of the most recent releases that we have here at Eightfold. So talent acquisition was the first capability that Eightfold brought to market, and again, it’s about driving the appropriate talent to the appropriate roles as effectively as possible. Now what Eightfold is able to do is give you the ability to essentially tell the system what good looks like for any type of role. So in this case, if I was hiring for very senior cybersecurity role, we can integrate with your existing systems of record. So you see here, we’re working off of Workday. That requisition gets received, we receive all of the information about what requirements of the job are, but then we allow you to add additional intelligence. For example, you’ve got high performers in this role at the organization today.

16:13
Your wish list might include simply being able to clone them if you could. Well, the closest that we can offer is that you can give us the information about those high performers, about those people that you would clone if you could, and we can essentially learn from them. We can break down the information to understand what are the actual competencies, the combination of skills and proficiency with those skills that those individuals bring to the table that make them better performing than their peers, let’s say, or maybe you’re interested in understanding what’s happening in the external market.

16:37
Are people doing this type of work calling themselves by new titles? Are certain job titles declining in prevalence in the market while others are actually inclining in prevalence in the market? Or maybe you’re interested to know what does the skills landscape look like for people who are doing cybersecurity work at a senior level within the public sector space?

17:02
What sort of programming languages are they using, what sort of certifications are required, etc, we can bring those learnings from the external market data to you in the flow of work, so that you can incorporate them into your definition of what good looks like for this role.

17:15
And one of the key components that Eightfold is going to allow you to leverage as well is, of course, skills. You can probably imagine by how many times we’ve mentioned them already, they’re important to what we do. The understanding of skills, though, is really important Eightfold, understands skills at a contextual and conceptual level, as opposed to simply looking at them as words on the page or looking at them as tags.

17:39
This is a great opportunity to give you a sneak peek, sort of under the hood of Eightfold, so you can see exactly what I mean. So this is a data visualization tool you might be familiar with called TensorBoard. We’re actually only looking at small we’ll call it a galaxy out of the universe of data that Eightfold is actually analyzed to date, but it still gives you a lot of meaningful insight. So Eightfold uses a dynamic skills ontology. Whenever we look for skills information, we’re not just looking for the skill the word or a pre programmed set of similar words or acronyms that might represent the same thing. What we’re looking for is all of what we call the adjacencies. What are the types of work that people do that would allow them to develop this skill or require them to utilize this skill. What are the most commonly correlated skills or certifications or capabilities or assessments that travel with that? What type of industries do they serve? And all of those things are actually related in this dynamic ontology, and it’s those relationships that make it in ontology. Normally, when you hear about skills being used in systems, we talk about taxonomies, right? Which is simply a list of the skills. The list doesn’t give you enough information. What we care about is you might have the exact skill we’re looking for, or you might have a lot of signals that show us you probably have the skill you just didn’t say it outright in your profile or in the information that’s been collected from you so far. So we can look at is all of the different relationships and related signals in order to derive the statistical probability that you would have actually developed this capability.

19:13
So when we look for something like Federal Acquisition regulatory requirements, for example, you see that this is related to things like Contract Administration and International agreements and bid protests and close outs and addendums and all the different fun stuff that you have to deal with as part of the requisition cycle, right? Versus, if we look at something like some couple fun examples here, look at something like landing gear, right?

19:34
If I’m a systems engineer designing aircraft, we can see that landing gear is related to things like wind tunnel testing and brake system design and composite systems and, of course, aerospace engineering. So these concepts are recognized as traveling together in Eightfold, not because someone has sat down and pre programmed them, but because that is what the data tells us. All of this is bubbling up from the ongoing analysis in real time, all the time.

20:00
It’s also important to know that it’s not limited to technical concepts or technical skills. When we think about qualifications for individuals for leadership positions, what does it look like to be an effective team leader? How is that expressed in performance review, data, reference, letters, et cetera. There might be 10s of 1000s of phrases that people use to essentially give someone kudos for being able to lead a team. We use a combination, again, of natural language processing to understand what is being said in those data sources, and then we look at what is the contextual and conceptual meaning of what is being said in terms of skills. So we know that things like building relationships, and being results oriented, and having an effective outcome from a team, having a can do approach, all of those things are actually related, conceptually, from a skill perspective, to team leadership as a whole. So this is that engine that is under the hood of all of the recommendations that Eightfold is going to make at any point. So when we think about serving up the most appropriate people to do work in a certain capacity in an organization, we’re not limited to just looking at Yes, they have a skill or no they don’t have a skill. We can look at overall, how relevant is their overall skill set, how quickly would they potentially be able to be trained compared to their peers or other available talent. How relevant is their actual work history and experience to what your definition of good looks like? So there’s always a human in the loop that is defining what good looks like. We’re always going to serve up what we like to call available AI.

21:42
So we don’t want this to be a black box, right? We want you to be able to actually see why recommendations are being made in a certain way, and what are the characteristics of an individual, so you can make the appropriate determination of, again, whether this is exactly what you’re looking for or not. If it’s a little bit off, you can go ahead and change your calibration, change the directions that you’re giving to the AI, essentially, to operate off of. And then there’s a lot of tools to actually be able to execute the tasks. So the recommendation engine, the ability to see the right people, quote, unquote, for every role as quickly as possible, is where a lot of the value is derived from. But there’s also a lot of practical features that we would certainly welcome the opportunity to dive into more deeply with you in the future, such as integrated CRM, the ability to do something about it now that we’ve identified good people, how can I actually contact them using email campaigns, text message campaigns, WhatsApp How can I get the process moving faster by doing things like offering potential AI interviews, so that we don’t need people’s time and effort to go through things like the initial screening interviews, where we have pretty standardized templates of questions that we want to ask, but we want to ask them in a particular way that is personal to each individual recipient, so that it feels like a real interview with a real person, which is the whole goal. We want it to be as close as possible to having one of your employees spend the time to interview someone, making sure that you know the questions are going to be related to their specific experience, and, most importantly, making it interactive, letting the candidate ask questions back, letting the candidate ask for clarifying questions, etc. This is another piece that would again, we’d be happy to do a deeper dive, full demonstration for you, including the ability to create specific roles that are relevant to your organization. So lots of capabilities here. One of the key pieces is obviously the results. So when we think about typical results, one of the major components is obviously time to identify when we identify the right talent faster we can move them through the process faster. Having automation is another key component, so being able to actually create specific workflows to simply have the system do the work for you and integrate back to your applicant tracking system so Eightfold, can keep your ATS up to date while it’s doing things like automatically screening people who pass all of your screening questions during the application, inviting them to the interview, letting the Hiring manager know these people have been advanced. We can automate all those types of actions. For example, there’s also a tremendous amount of capability around, we’ll call them secondary or tertiary concerns around recruiting. You know, do you want to leverage communities in order to build pipelines of talent ahead of need? Well, now you can do that, except, instead of having to rely on candidate behavior to self select into certain job families and sign up for different job alerts, you can simply set up the definition of what good looks like for that community using calibration as well, and people will essentially Auto Filter themselves based on who they are and what their qualifications look like. So for example, for looking for folks that are just coming out of university, for early careers or internship opportunities, we might care less about their technical skill set and care more about the fact that they are early career, that they live in certain target markets that we care about, and that they have some of those human skills that we talked about, you know, folks that are going to be doing.

25:00
Recruiting or some sort of outreach for the community, let’s make sure that they have people skills and communication capabilities. We don’t necessarily look for specific work experience or technical skills, so a lot of really key components there, and there’s a full events management capability here as well. So if you are doing security clearance affairs or any type of hiring event or networking events, where you want to keep track of what connections are being made and what the capabilities of those people might be. All of that is embedded in one platform, so lot of capabilities around talent acquisition, and of course, all of the different aspects are tracked. So are you making progress? Are you hiring faster? Are you seeing faster hiring in certain departments but not others? There’s tremendous amount of insights and analytics that we can dive into at a later time as well, once you’ve identified folks though, that you’re interested in hiring.

25:50
And actually, before I get there, let’s talk about the external candidate experience for a moment, because this is another area where we do see tremendous impact. So we have organizations such as Vodafone, for example, that saw a massive change in terms of both volume and demographics, in terms of who was applying to certain roles. So by having the matching work both directions, we’re not only able to serve up the right people for every job, we’re able to serve up the right jobs for every person. So when an individual does something like upload their resume or their CV or their LinkedIn profile, we can simply comb through all of the opportunities for them and match them to the most appropriate role that they are most likely to accept an offer for and be successful in performing in the role for at least a year. And more importantly, we’re going to highlight why these are the capabilities that you actually have demonstrated through your work history that we need for this role. Gives people the confidence to self assess into that job, and as a result, we see far higher conversion rates. Some of our clients are actually seeing as high as 40% of career site visitors actually convert to completed applications. That’s roughly 40x higher than the industry standard so incredibly valuable to their those organizations.

27:10
And again, Vodafone saw 128% increase in women applying to technical roles, largely because of the ability to show them very clearly there’s qualifications that are met here you should assess yourself into the role, as opposed to questioning whether or not you should apply. So by serving people up with personalized, actionable insight definitely drives results, kind of moving into the candidate experience, or, sorry, the employee experience.

27:30
Imagine being able to provide every employee with the ability to explore all of the potential futures that might exist for them at your organization at the click of a button, that’s exactly what Eightfold is able to do. So by understanding the skills and capabilities that a person has developed through their work history, and by understanding the requirements for all of the different roles that exist across the entire organization, we’re able to bring a new type of insight into what it takes to move from one thing to the next over the course of their career, and what that might actually end up leading to down the road. So this is a pretty realistic example where you know my current role might set me up very well for a logical promotion within my department as the next step, but down the road, it could lead in very different directions, depending on what I decide to pursue for the next two or three or four jobs beyond that, within the organization. So when I want to dive in to understand what it takes to actually move from here to there, I have clear understanding, because Eightfold can provide me with a detailed, personalized skill gap analysis in real time. Here’s what I have today that I can bring to the table. Here’s what the next role would require for me. That represent gap areas. You can see those in gray and most importantly, Eightfold AI, can also serve up content connections to be able to do something about it. So we can integrate with your LXPS or LMS pulling your learning content. We can actually read the course description information, and we can infer the types of skills and the level of skill development that those courses would essentially offer, so that we can provide the most relevant potential learning opportunities to these people to pursue this particular direction. We also have a deep understanding of the other people in the organization, so maybe we can serve up connections for people to potentially network or provide mentoring relationships. There’s also the ability to power cross functional projects. So learning by doing. How do we surface the right opportunities for people to either put their current skills to work to benefit the organization, or gain skills that they might be looking to gain by working with others to learn those skills.

29:41
So this is really helpful at the individual employee level, but it also provides a tremendous amount of impact for the organization when we think about the level of information that is available for each person, right understanding that the individual experiences of each person have helped them develop specific skill areas.

30:00
And by the way, there might be other areas of specialization, right that are not going to be assumed by Eightfold, but that we can serve up as suggestions that that individual can then claim and self assess.

30:21
We have the ability to start granular learning from each individual person, but then that grows into an organization wide understanding of all of the skills that exist across the talent for the entire talent pool within your organization.

30:32
So when you want to understand, what are the skills that we’re gaining as we train, as we hire, as we redeploy. What are the skills that we might be losing as we see churn or as we see terminations? How are those skills distributed in terms of place, in terms of department, if we need to think about things like redeployment or reorganization, that becomes actionable information that is available at a standard dashboard at your fingertips, as opposed to simply not being available at all, which is the reality for most organizations today. So by having the distinct information at the individual level, you then have really actionable, deep information at the organization or unit level, which is really important. So again, another area would be happy, as you can imagine, this is a tip of the iceberg. I think doesn’t even do it justice. We’re kind of doing the 60,000 foot flyover. There’s a lot more we can dig into here, certainly, but I want to make sure we touch on again, two more, two more topics within the next eight minutes or so, one of which is resource management. And I want to give you a sneak peek into the latest and greatest as well. So resource management is, again, really about placing the right employees with the right bodies of work. So this is goes a little deeper than those cross functional projects that I just mentioned with with part of talent management. This is about placing individuals for again, maybe it’s full time deployments, maybe it’s full time projects that are going to last six months to eight months that require a very specific set of skills. This was actually developed in partnership with some of the world’s largest professional services organizations. So you can imagine some of those professional services organizations hire, you know, consultants are who they are, so they are constantly deploying their resources with clients in all sorts of different industries. So it’s not the job title and it’s not the department that’s going to tell you what those capabilities are. It’s the project history. So that ability to track skills associated with certain bodies of work over certain time periods for certain industries or certain clients is something that we can move in a lot of different directions. This is an area that we were working very actively with one of the United States military branches to talk around deployment opportunities so your you know, your MOS code, your rank is not going to be changing, but which deployment best meets your combination of experience and capabilities from your training and also meets your preferences is something that’s really important for them to understand at scale. This is how we’re going to be deploying it for that particular organization on the administrative side, it looks like talent acquisition quite a bit. So the difference is, when we’re not matching people to quote, unquote requisitions, we’re matching people to roles within a project team. So that case, we have the ability to track the project itself, the individual project teams that might exist to support that project, and then within each project, we have individual roles that we can track placement and availability of the associated resources needed to complete that work effectively. So this is an area where, again, we’re taking that power of recognizing who is the right person to do the work, adding in the layer of are they available when we need them to do the work?

33:40
And we can keep track of who is deployed, who is essentially planned for the next stages and months and months and months in advance to make sure that we have that workforce planning capability taken care of.

33:57
So the last couple pieces that I want to talk around. So we just released fairly recently, the capability for you to get your hands on a lot of the core capabilities of managing your skills themselves. Take that as a positive. One of the things that we want to make sure that you know is you have the ability to manage certain components of this on an ongoing basis. So for example, if you’re simply interested to understand what are the skills that have been identified in a particular talent pool within our organization, that’s not something that you have to go run a custom report for. We can really allow you to dive in and actually sort through different categories of skills and sub categories of skills that are specific to your organization. So this is a taxonomy that we’re able to use. We derive it from our ontology. When we do the analysis of your information about your organization, we can distill the skills that exist within your specific organization and help you organize them.

35:00
So that when we think about doing things like defining what a particular skills means, or making sure that we have translation variants that can be displayed to different user groups, that is not something you have to guess around, or do a lot of back end processing or administration, you know, for ENCODE or anything like that, it is here for you to actually touch, see and manage.

35:16
This is also where you can get really interesting, actionable insights about different types of roles that are changing within the organization. So we all know technology is important to everyone. It’s not just in the tech industry anymore, but maybe you’re interested in understanding and keeping up with what are the different skills that a data scientist or software engineer or a cybersecurity professional in the private sector is bringing to the table versus how you’re defining it today. And you can actually do research into skills and skills trends. Which skills are rising in prevalence? What are the adjacent skills that travel with those skills? What are the different trends that we see for particular roles in particular industries. There’s essentially an entire research tool here for you to be able to think about keeping up with the current definition of different roles. And then we give you the tools to be able to actively take action, actively take action, and actively use that data in real time. So this is actually a side by side screen where you can see how you’re defining the role in terms of skills and proficiency with those skills today, how that compares to the skills that are actually exhibited by the individual employees that you have in that role. So you can see if there’s a discrepancy between how you define the work and how people actually do the work day to day. And you can also see external data, what’s changing for similar roles within the industry, what’s changing for similar roles across all industries globally, to get, again, any sort of signals on insights that you might want to incorporate into your definite definition of this role in the near term future. So we try to make this again, very easy to use and put into practical action, and because it is a unified platform that is AI native, when you make updates to what you mean by certain skills for certain jobs, and then you roll that out, if you’re one of our talent management clients, and you change the definition of the skills required for that role, we’re automatically going to be able to roll that out to all of the individual employees that are in that role. So we’re going to be able to understand that the skills required by their role have been updated, the benchmark proficiency expectations have been updated, and that can automatically impact the type of learning and development content that’s going to be served up to them to upskill their own personal journey, to either reach those benchmarks or exceed them and be ready for their next promotion. Next promotion. So the connectivity becomes really important here.

37:47
Last but not least, there is a completely independent opportunity for leveraging AI in the world of work that we’ve just released called digital twin, and this is the ability to essentially create a secure, independent version for each individual client.

38:03
So this isn’t something that there’s not a global data set. We’re going to only be using your data. What we then look at is, what are the systems that we essentially want to extract learning from about what work is happening now? So maybe we’re plugging into your email, into your document library to understand, what are people contributing? What are people looking on? What are working on? What are people researching? And we can essentially then build out digital personas that align with the individual workers within your organization, that allow you to essentially have a personal GPT of each of these persons or each of these groups. So for example, here, I’ve asked Arvind. It’s actually Arvind’s digital twin, who is one of our senior product managers, to describe what are the core types of AI that we use within Eightfold. So instead of having to actually go to Arvind, find time on his calendar, set up a meeting, or stock him on Slack, which is what we use for internal messaging here, I’m simply able to ask Arvind digital twin, it goes ahead and looks for all of the information that it can find from content that Arvind has produced that are across all of our different systems, and then it also produces the source information for the information that’s been presented here.

39:14
So tremendously, time saving allows, again, we have a group digital twin for our solutions architects. So if you have technical questions, instead of asking one of them, you can get information from the group as a whole. Same thing with a legal team. We have lots of different deployments of this capability that we’re going to be releasing over the coming months. So the ability to help people do performance reviews based on being able to see the work that they’ve accomplished over the last year, being able to align people’s skill profiles with their current work without having to get that data in another way is another feature that is coming very soon. So we’re continuously evolving and looking at how do we get the most up to date information?

40:00
In provide actionable outputs in terms of capabilities across the entire spectrum of work and workers.

40:08
So no, it’s a little bit like drinking from fire hose, but as you can imagine, there’s even more. It’s a very broad platform, and there’s a tremendous depth of capability. So again, we welcome you to contact us to do a deeper dive demonstration around your particular initiatives and goals and particular use cases. And very much look forward to the opportunity. Thank you for your time.

40:32
And with that, Michael, I will hand it back to you.

40:35
Michael: Great. Thank you. Thank you, Ryan. I don’t want to take up too much time in closing the presentation portion of this, what I’d really like to do is hear from the audience any types of questions or comments they have. I will say what we’ve heard from the government, and especially folks in human capital or HR it is they’re being asked to lean into AI, where it’s practical, where they can apply it, where it’s going to make what they’re doing and what they have been doing better, both for the citizens that they’re trying to benefit through their mission, as well as the employees. And it’s an exciting time to be focused on on AI and human capital, and I’d really love to hear from the audience.

41:22
And if we can answer any questions today, that would be fantastic. So with that, maybe Jacqueline or Ryan, if you guys are aware of any comments or questions that we can answer for the group.

41:37
So our first question, is, what is the difference between native AI, like an Eightfold system, versus some of the other major enterprise HC systems?

41:42
Ryan, I can take a first pass at that and maybe turn it over to you to add, you know, the main difference is that systems like ours that are built with native AI are in a period right now where we’re not having to retrofit the platform. As new advents with AI are coming to fruition for human capital and HR and so, for instance, a couple of years ago, you know, generative AI was, you know, has surfaced as something that everybody wants to leverage to help them scale and do things faster. And then this year, while generative AI is still very much in the forefront, it’s agentic AI.

42:47
And what could be done, you know, simultaneously or with assistance. And in the next year or two, we’re going to see interest in multi agent, hyper contextual for complex task functions that’s coming for AI. And the difference between a native AI platform like Eightfold is that we’re able to infuse these and insert them into our offering effortlessly, because the system was built ground up, whereas traditional HR enterprise systems are needing to retrofit their platform, which was built or architected 10 years ago without AI even in mind. And so they’re kind of racing with technology giants to infuse or layer on or retrofit, you know, here now we have generative AI here. Now we’ve added this component for agentic AI, etc, and they’re needing to reconfigure a lot of their platforms to accommodate these ways for organizations to take advantage of AI.

43:41
And so that’s that’s one difference I see, Brian, did you want to add anything to that? Yeah, I would just sort of echo one of the things I mentioned very briefly during the presentation, which is the loss of specificity and the loss of nuance that happens when you do that retrofit process that Michael just so eloquently described. So again, we think about that idea of this knowledge, about capabilities as this multi dimensional concept, where the changing association with a job title, changing association with a particular agency, changing association with a particular type of work that served a particular client base, all impacts the understanding of what that particular term actually really means. All of that goes away when we have to flatten it to fit into a system of record. So if we think about project management as an example, when I look at project management in Eightfold, it’s going to essentially say, “Well, wait a second. Are we looking for project management for someone who is in technology or someone who is in AI?”

45:00
Or executive leadership, or someone who is in accounting, because what project management means is completely different for each of those individuals. Soon as we flatten it to fit into a traditional system of record, it just becomes a tag, and project management is project management, and it has no difference anymore unless it’s combined with all sorts of other tags. So you lose the nuance, and you lose the depth of understanding that results in the accuracy, and the accuracy is what drives the results. So that’s the biggest piece for me, is, you know, the the ability to directly connect to the dynamicism, as opposed to having to flatten the data to fit in existing systems.

45:39
That’s it’s a great question there. The bottom line is that a lot of these platforms that are, you know, name brand, you know, were, were built so many years ago with without the thought of AI in mind, and they’re, they’re great at processing, you know, workflows and creating automation for processes.

45:54
But when it comes to AI and leveraging that ability, they’re they’re needing to kind of bolt something on that it wasn’t designed to do in the first place.

46:15
Any other questions? Yeah, great. Thank you guys. What are the key benefits of Eightfold’s FedRAMP, moderate and IL4 certifications for agencies?

46:27
Yeah, I’ll take a pass at that. You know, for FedRAMP authorization, I think it’s great. We are a cloud based SaaS, and that is usually a minimum requirement for any agency FedRAMP. Considering adding that there it de risks the agency’s profile, and so most agencies I’m familiar with will will require FedRAMP authorization if they’re going to use a cloud based SAS. IL4 is also a great differentiator, confidential, unclassified information, or CUI with an IL4 environment is something we can host and process, and that includes people data.

46:59
And so any kind of platform that doesn’t have an IL four environment from DISA certified is going to have to stay outside of that people data and need to process the data from from another mechanism, besides, besides, without, without redaction. So that’s probably the main differentiator. There are other benefits to IL4 and FedRAMP, but those are a couple that come to mind.

47:42
Great. Thank you.

47:44
The next question is, what kind of data does a full need to start delivering value for an agency? Does that data need to be restructured or reformatted and tagged in some way for April to start outputting insights that our agency can use?

48:00
I think this also lends itself to maybe the difference between native AI platforms like Eightfold that were built from the ground up with AI versus other human capital platforms that weren’t built with AI in mind Eightfold, can process and synthesize unstructured data or structured data in disparate repositories equally well as it does with just structured data. And so where that plays out is in a place, in an environment like the federal government, where often agencies have multiple different places where people data is stored, and even more importantly, key elements to their data that would ultimately be pulled together to cohesively output some of the insights that we represent you would need to re platform or centralize that data.

49:01
A lot of these enterprise human capital systems, a lot of the name brand ones, will promise some of the outputs and insights that a native intelligence platform like ours can achieve. But they’ll first need to go into a lot of pre configuration, and they’ll need to integrate with different repositories. They’ll need to tag that data. They’ll need to organize it in a certain way so that it is mapped to the way their platform processes data Eightfold. Can go in and work with unstructured data or from different sources, and because of some of the elements that Ryan was talking about earlier, in terms of the way our AI processes data, can immediately start outputting the insights that that you’re looking for. It doesn’t have to replace systems. It doesn’t have to centralize systems. Those are good endeavors.

50:00
Dollars, but it can sit on top of that information, and immediately the AI can start contextualizing it. Ryan, anything you want to add, honestly, that was very, very inclusive. I think you made all the points I would have as well.

50:17
Great. Next question is, how does your AI ensure fair hiring?

50:23
Right? Yeah, I can take this one.

50:27
Number one aspect for essentially guaranteeing merit based matching and hiring is constant testing. So we have third-party audits on a regular basis as well as internal testing on a continuous basis to make sure that we are testing against disparate disparate outcomes when it comes to any type of bias. And one of the main things for mitigation there is the fact that we actually anonymize data prior to ingesting it for learning for any of the predictive models, so there is no personal data introduced at any point for the models to learn from, which is a big chunk of reducing bias in the outcomes as well. But then we also make sure that we are actively testing to make sure that bias isn’t sneaking through in some other fashion. Another big component is simply the scale of data that we’re using for the model training and tuning. Again, we mentioned, you know, the billion plus individual career trajectories that type of scale helps to mitigate, to some extent, because we are incorporating so many individuals as part of the data set that we are learning from on an ongoing basis. But then again, doesn’t replace testing. We always are looking at what are the actual predictive outputs?

51:41
We test those against purposefully biased outputs and make sure that they do not align perfect. The next question is, how does Eightfold AI actually determine which candidates are best aligned to a role or mission need?

51:52
Yeah, so that goes back to what we showed, particularly in the talent acquisition portion, which is really the calibration. Is essentially the rule set, so there is always a human in the loop from your organization that is defining that calibration of what good looks like for a particular role Eightfold is then applying those instructions to our AI in order to make sure that we are finding the folks that are most closely matching those requirements as they’ve been set by the human being. Then, however, we do have that very particular predictive element, where what we are essentially comparing it to is the likelihood to actually receive and accept an offer for that role or position, which automatically screens out a lot of folks who have all the right words in their profile, but they’re actually too senior for the role. For example, they might be in a quote, unquote overqualified most systems really struggle with that, because all the right data signals are there, but what they don’t understand is career trajectories. So because we also understand the career arc, we can tell when someone has already moved past a particular career, or when someone is set up to move very well to that next step in their career as an alternative, right? So what we’re looking for is the people that are most likely to move into the role, as opposed to the folks that are already past it. And then we also, of course, look at qualification of fit. Do you have the competencies that it takes to do the work that’s required that is always going to be a baseline?

53:16
Great. Thank you. We have one more question, can Eightfold help with succession planning or long term workforce readiness?

53:26
Short answer, absolutely. Give us a call to set up a demo.

53:32
Great. Thank you.

53:39
That’s going to be a wrap on our event. Thank you to the Eightfold team for your insights. I’d like to thank all of our participants for joining us. We hope this information was helpful to you and your organization.