Humans don't need to be in the business of copy and paste anymore.
SPEAKER_01How are you helping them understand like the urgency and the importance of it and like how to do it right?
SPEAKER_00I think the importance of it is directly tied to the reason for the urgency. And I think you could boil the importance down to a few simple statements. You can unlock at least a 2x productivity game with this capability, with AI native intelligent automation, powering true execution, true automation, not just serving up insights.
SPEAKER_01Sales can get pretty churny.
SPEAKER_00Our customers, on the average, are cutting their onboarding time by 50%. Wow.
SPEAKER_01That's internal onboarding, or that's onboarding clients?
SPEAKER_00That's their internal onboarding to productivity for their go-to-market teams.
SPEAKER_01As compared to what industry standard couple of weeks, maybe?
SPEAKER_00Yeah, but it's about three to four weeks.
SPEAKER_01This is just, it's not fair. Jason Eubanks is the CEO and co-founder of Oracle, an AI-native go-to-market platform. He pushes leaders to stop adding chat wrappers to old stacks and instead use intelligent automation that can double sales productivity, eliminate CRM busy work, and help teams move faster than competitors. Welcome to Using AI at work. I'm your host, Chris Dave. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, ChiefAIOfficer.com has the answer. We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day-to-day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company-wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs, and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. Hi, everybody. Welcome to another episode of Using AI at Work. This is Chris Daigle, and I'm actually super hyped up today to talk to our guest, Jason Eubanks, founder of Oracle, about we just kind of had a pre-conversation. We've had a couple conversations before this, and what he's doing is very cool and very interesting to me personally for where our business is. And it's addressing an area of every business where they'd love to get AI involved, and that's in the sales environment. So Jason, before we start, what is the takeaway that you want the listeners to have at the end of this episode today?
SPEAKER_00Yeah, I think there's, if I could expand it to three takeaways, you know, one is just generally speaking, I try to encourage everyone who I have a conversation with to really challenge themselves to think beyond an incremental approach, beyond a wrapper interface when they consider how to use AI at work. And Boris L, of course, is an AI native platform, and we'll talk about that later. And I don't mean this in a self-serving way. I truly mean it in a way that most of the people that I speak to in business are still thinking about the application of AI through the lens of uh a chat. Ask it a question, get an answer. And that's fine because that was the first application and interface for which AI generally was exposed to us as a public. As a platform shift, the power of AI is so dramatically impactful beyond question and answer. And I would challenge everybody as they turn internal to their organizations and think about how to unlock productivity, how to outcompete their market, how to better serve their customers. Just take, throw away that scared incremental approach of putting chat wrappers on this and that and connecting it to Slack and homegrown systems and wiring it up and get past that. Like, it's cool that you could take a little bit more data and and replicate a consumer experience in chat. We really we're past that. Nice products are past that. Technology is ready. I would challenge everybody to jump in with both feet and pin to an AI native approach everywhere you can.
SPEAKER_01Love it. So that's number one.
unknownOkay.
SPEAKER_00It's number one. And then hopefully, somewhere in this conversation, I'll have a chance to talk a little bit more self-serving about Oracle for two things that I'm excited about that we are announcing tomorrow. And so a little preview here, and by the time this gets out of probably will come out. But, you know, fresh off the presses, and we we have taken our AI native platform originally built for CRM plus about 15 other products on top of it, all on a single platform. And we're now um offering, we're taking the power of that AI native platform, decoupling it from the dependency of a CRM and making it available to sit right on top of legacy architectures like Salesforce and HubSpot. Uh so large enterprises have a path to harness the power of AI native intelligent automation for all of the go-to-market through Oracle GTM operating system. And they can sit it right on top of their existing CRM. That's number one. And number two, we're also shipping uh an agent, a custom agent builder inside of Oracle that will unlock the power of AI native agentic workflows for all go-to-market and ops teams out there. They with with just simple natural language prompt, they can you know execute agentic workflows and build their own agents. So really with very few limitations. I mean, it's this is one of those moments where it's like your your imagination is your limitation. Yeah. And it's an exciting time.
SPEAKER_01Awesome. Well, you know what? I think that's gonna give me a lot to chew on here. I want to start with your number one. I'm with you. Like I'm drinking the Kool-Aid, I know what's possible now, and I don't quite understand why. I mean, I I get there's risk concerns, we don't understand the risk associated with it, or does the budget make sense? I get all that stuff. But you're that's a ballsy comment. Just say, guys, jump in. There's how are you helping uh executives that you're talking to, prospects, peers that aren't all in like you and I, how are you helping them understand like the urgency and the importance of it and like how to do it right? What are you telling them?
SPEAKER_00I think the importance of it is directly tied to the reason for the urgency. And I think you could boil the importance down to a very simple a few simple statements. You can unlock at least a 2x productivity game with this capability, with with AI native intelligent automation, powering true true execution, true automation, not just serving up insights. And those who unlock that opportunity for a two to three X game in productivity first will have a tremendous advantage. And as the gains continue to be exponential in the technology platforms that underpin B2B use of AI, they will by default be the first movers. For those other, the other cohort of people that are thinking about this incrementally and trying to stitch together, you know, you you take a fragmented tool stack and you try to stitch together, you know, chat chatbot-like communication across 15 to 20 different vendors. And every time there's an increment there's a every time there's a a step function gain in underpinning AI capabilities, it's just like anything else in infrastructure. You're gonna be stuck trying to manage all of those versions, all of those interconnections, all of the different flavors of a you know, niche agents and your homegrown bots that you've tried to build. And and it and it's just like the spaghetti infrastructure of the past.
SPEAKER_01Sure. Yeah.
SPEAKER_00You know, when you went from you know, scripts to full automation or on-premise to the cloud. I mean, it's just another version of that evolution. And everyone was scared of those technology shifts in the beginning, too. Yeah. And I guess maybe it's because I've been around for 25 years doing this stuff, that you know, I can remember all those conversations when people went from building servers by hand to automating workloads that built data centers to not needing data centers. And and to me, there's a lot of similarities here in the sense that the people that jump in and adopt the full power of AI native capabilities first will continue to stay out in front of those that take an incremental approach and get stuck in the tangled web of you know complexity. And I just think it's a hard thing to outrun. And now's the moment that you have to create that step function shift in your business along with that that disruptive platform shift that's already occurred. Now, that's a bit of urgency. I think the importance really just comes down to you truly can transform the productivity model of your business when we talk about go to market. The traditional B2B sales teams are still in a place that's upside down. I mean, just last year, Forrester and there's all kinds of reports out there. You can this is easy to find the data, but still 80% of the revenue is coming from the top 25% of sellers. That means that you're, you know, organizations are spending 75% of their go-to-market on expense envelope to get 20% of the business. And that's just an unsustainable uh productivity model. When everyone's doing that, you can you you you have small levers for gains. When some portion of the comp competitive landscape starts to garner a 2x productivity gain and through excellence and execution at scale with consistency provided through automation, you take those bottom performers and you move them up to look more like the elite performers of your org. Yeah, yeah. Those those those competitors, those companies that do that first, will simply just outpace the ones that are still here spending 75% of their expense envelope on you know 20% of productivity in a market that is unrelenting around what we've seen recently in value slides. And there's going to be pressure anytime you have a market shift like that. There's going to be natural pressure that flows through on efficiency. And so whether you think about it through the lens of gaining a productive edge or gaining an efficiency edge, either way, whether you want to drive more top line and you want to do it in a more productive way, I just think the opportunity is there. And and those winners will will be the ones that jump in right now. The other side of this is, you know, I I was talking, by the way, just to share a customer's story and I'll keep the keep the names out of it, but I was talking to one of the world's largest, you know, um hardware and technology services companies yesterday. And they've been around for decades and decades and decades. And this is not a company that if I if I had said the brand name to you, you would think, absolutely, they're gonna be on the top of the adoption curve of AI.
SPEAKER_02Yeah.
SPEAKER_00But they are. They are challenging themselves, they're carving off a portion of their business, you know, 150 users out of 2,000 sellers, and saying, hey, we're gonna take this pod and we're going all in, we're throwing out all the 20-year legacy rules, and we're gonna pretend that this is we're going all in right now. How would we build this go-to-market motion today for this division of the company if they were a new company? And they are we're going on that journey with them, and they are benchmarking all of the metrics and all the productivity gains, all of the expense, all the all the additional insights and automation and intelligence. They are benchmarking it, and they're just gonna put it to the test. And that and that's the kind of thing that I would encourage people to do. When you see companies that are hundreds years old doing this, yeah, how could you be a younger company and not?
SPEAKER_01Yeah. So a couple a couple of things. I I like this because I I was actually trying to explain this to someone this morning. This idea that you had about the exponential gains that are gonna occur from the individuals who adopt now, like they're gonna pull away from the pack, and it will you will not be able to catch up with them if you are if you delay three months, six months, and these people are in stealth mode unintentionally, but they're going AI native. So those who wait will not be able to catch up, which is a like that's a paradigm that that doesn't happen that often in business where somebody's like, oh, we just work twice as hard, we'll catch up. No. Like the distance of time, performance, capability, resource requirement, minimization, like all of that will be s an anyway. You you you you verbalized what I was thinking this morning, and that's an unusual place. And I can see how that ties to the importance and the urgency. They're like you said at the very beginning, they're very much tied together. And then I I like this idea a lot about an incumbent saying, Hey, let's peel off a little bit of the business and let's go AI native. Let's go off the reservation, go all AI. How would we do it? They're gonna learn some stuff that will be translated to the rest of the 2,000 sellers and it will be lights out. That's that's amazing. That's a fantastic approach. Um, would love to hear more about that data when you can, if if you can ever share that. Okay, and then now the second thing was you were talking about the uh this kind of overlay that you guys uh I mean, when you and I first spoke about being on the podcast, it was probably you know before the holidays. And just in that short period of time, it sounds like there's been some developments, lessons learned, and enhancements that have like Aura sells a different product than it was 90 days ago. So tell me more about that that overlay. It's basically natural language search and retrieval from all of my legacy systems.
SPEAKER_00Okay, so you're referring to our uh Your second point. Yeah. Okay, so not something that we've we've said on camera yet. So let's bring the audience up to speed. So you're referring to our custom agent.
SPEAKER_01No, that was the third thing that you mentioned just now. It sounded like you you were indicating that this this environment of having this cluster of systems that people used to need is going away. And that's yeah. Let's dig in on that a little bit.
SPEAKER_00Okay, sure. Sorry. So I guess let's let's bring the audience on the journey. So we started Oracle in summer of 2024. Uh out of a place of frustration and technical opportunity. You know, I was I've been an operator for over 20 years, building sales, marketing, and CS teams for multiple startups. My co-founder and CTO ran was SVP of engineering with me at Harness for five years where we last worked together. Prior to that, built big products like the cloud cloud offering at Nutanix and Nutanix and built a lot of product for VMware pre and post-IPO. So worked together for five years. We were talking a lot about the opportunity with AI being a platform shift, and settled in on just a shared concern that we both have, which is the customer journey and how fragmented the existing go-to-market tooling landscape is, and how go-to-market teams really have like three CRMs and tool stacks inside of go to market. You know, you have your your your Martex tool cool tool stack anchored by you know a Marketo or HubSpot Marketing or whatever, kind of as the CRM of marketing, you have Salesforce HubSpot, et cetera, for and have this the sales CRM, and you have you know plan hack, gain site, et cetera, is kind of these CSM products. I I would call that like the quote unquote CRM of of CS.
SPEAKER_01Sure. Yeah.
SPEAKER_00For from a customer's perspective, someone who's buying a solution off somebody, you know, you know, that's just a single customer journey. You go going through different phases of that customer journey. Why should you be, why should that intelligence about that customer journey be spread across three different systems? Why should there be fragmentation that that in the technology landscape that requires 15 to 20 products? When I was in Harness, our go-to-market tooling stack was 22 products. Yeah. Yeah. Sitting on top of Salesforce. And, you know, I had a team of 11 ops people stitching that stuff together manually. You know, we had three products we had custom built to fill the gaps on top of it. We had I had engineers, I had data engineers building data pipelines for analytics on top of all this mess. And it's like a Chenga stack. You know, it's like it just leans over and you have problems all the time, and integrations break, and you don't have a single lens for analytics. Metadata is trapped in 22 different databases. And when you think about applying that legacy architecture and the to to the go-to-market workflows in the era of AI, it just doesn't make sense. In the era of AI, you know, what we've built is an AI native CRM platform. That was the original product that we built at ORSL. An AI native CRM platform. It included the CRM, built on an AI-native architecture with a unified data model supporting structured, typical CRM data, structured data, and unstructured data with a with a data lakehouse. And having knowledge graphing and time series and all these, you know, RAG models and all these AI native architectural components allowed us to build an agentic layer on top of it, you know, being backed up across five of the world's best known LLM models and driving surfacing insights that were relevant to the different personas at the different phase of the prospective buying journey from contact to contract, and then driving intelligent automation through an agentic workflow model built within the platform. That's the first product we took to market and we have customers on today. What we are announcing now are two different products. One, we're taking that the power of that entire AI native platform and decoupling it from our CRM and allowing it to just plug and play right on top of Salesforce or HubSpot. Still getting rid of those 14 other products that you have to plug in on top of your legacy CRM to make them useful. You know, we still ship with 85 million accounts and 850 million contacts. Our platform still ships with the operating system still ships with 10,000 agents in the background that are doing deep research, AI enrichment, surfacing automated AI enrichment, extending custom AI enrichment, and then putting all that to work and automated agentic pipeline workflows, personalized outreach at scale, you know, for AI forecasting, et cetera. So all these capabilities that sit across all the internal and external conversation signals that are being enriched to unlock intelligent actions. That capability is what we're shipping in our go-to-market operating system. But now large enterprises and customers that want to coexist with maybe other workflows that they've that they've built into their CRM system that can coexist and it can either be a bridge for adoption from a legacy tool stack into an AI native plat go-to-market platform as you kind of take a crawl-walk-run approach, or and and or it can coexist forever. Now, what does this mean for the day-to-day work of your sellers or marketers or CS teams? It's simplified, it's automated, it's enriched. You take the the user and you put them in or cell, allow them to have a single place for all of those signals, driving contextual awareness across all the internal and external conversations, and unlocking intelligent actions for them, making them twice as productive, getting rid of 80% of their manual toil time, eliminating the need for another 14 products on top of your legacy CRM. That's what we're shipping in the go-to-market operating system.
SPEAKER_01So as a user, as a participant in those departments, I have one place that I go. I'm not getting a report here, extracting that data, uploading it here, and playing that whole game.
SPEAKER_00Humans don't need to be in the business of copy and paste anymore. Right. That's like that's an incredibly unproductive use of uh of a human's capacity. Right. Our belief is that so what we do is we design all of our automation, all of our insights, all of our enrichment, all of our automation that sits on top of it. With the notion of what would a human do? What are the next three actions that the human we're serving, the persona we're serving in that moment, what would they do? And can we automate that intelligently for them to further free them up for conversations like this one?
SPEAKER_02Mm-hmm. Mm-hmm.
SPEAKER_00That's how you make operators, superhuman operators, an hours to free them up to do what they do best.
SPEAKER_01And I would imagine that in the sales environment, there's churn, um, as in any department, but sales can get pretty churny. Um that means probably onboarding for new new reps is pretty quick because there's one tool that they're dealing with primarily, so they're not having to go and figure out all the proprietary stack that was built. Interesting.
SPEAKER_00Yeah. We're seeing on on the enablement front or the onboarding front, you know, our customers on the average are cutting their onboarding time by 50%.
SPEAKER_01Wow. That's internal onboarding or that's onboarding clients?
SPEAKER_00That's their internal onboarding to productivity for their go-to-market teams. I mean, he he we of course use our own product, but our SDRs are are booking meetings in productive on their third day. Yeah.
SPEAKER_01As compared to what, industry standard, a couple of weeks maybe?
SPEAKER_00Yeah, but it's about three to four weeks.
SPEAKER_01Yeah.
SPEAKER_00Yeah. And then and if you think about, you know, a 50% reduction to productivity time, when you're scaling on the back of a productivity model led by sales, one, it's costly. And you always have to overhire because you're chasing a six to nine month product you know ramp time. And so if you can save that by 50% and get to max productivity faster, while you're also increasing the fit the productivity, average productivity of a seller by 50, 50% to 100%. So somewhere between 50% to doubling your productivity per head on the average. When you get those two levers for productivity, you really are you you dramatically reduce the amount of hiring you have to expense, you have to lay out to reach the same or better top line goals.
SPEAKER_01And I would imagine that just think about it, it just kind of makes sense.
SPEAKER_00It's the you know, all the intelligent automation is there to feed them signals so they spend time with the right prospects, you know, drive dynamically driving ICP territories, dynamically filling up those accounts with the right contacts, automatically showing them the moment that they should contact that person because we see the external signals, and then really feeding them the personalized outreach and all the intelligence on the account, automating the value, the enriching the value hypothesis, and giving them a ready-made pitch on what to do and what to say how to say it in that moment that they're supposed to reach out to them. You just remove a lot of the toil and you maximize a lot of conversion. I'm thinking about all these searching is unlocked at every interaction along the sales site.
SPEAKER_01I'm thinking about all these sales books that you know all these salespeople have read out their career that give them systems on follow-up and you know, all that like out the window, whole different paradox.
SPEAKER_00That's all automated, right? Well, it's all automated. And and by the way, it's not the those things are still great. I mean, the we have built we have built the sales frameworks into the system. And so as our customers set up Aura Cell and choose the frameworks that matter for their organization, um, and and by the way, you can choose different frameworks and different sales processes for different motions. So PLG motion can be different from uh high velocity sales like commercial motion, different from a large enterprise, very complex motion. All those things can coexist and it dynamically applied automated at the right moment. And then it's coaching like the value-based selling frameworks. The coaching is derived from the best practices of those sales frameworks that our customers are choosing. So it's like having your best trained sales leader on the shoulder of every sales rep.
SPEAKER_01This is incredible. So one of the stats that always struck me, I'm not from a sales background, but it was how little amount of time a salesperson spent on the phone. And it was surprisingly low. You think, okay, it's a salesperson, they're on the phone a lot. No, they're updating the CRM, they're sending the email and preparing the proposal or whatever. This is that that increased productivity you're talking about is because the salesperson isn't doing the things that usually were the parts of the job they didn't like, but that the sales manager was always like, dude, you gotta get this done. Update the CRM, put your notes in the yeah. And now this is all being handled automatically.
SPEAKER_00So I imagine that's Yeah, the industry stat, by the way, what you're talking about is is 20 is 24 to 30 percent. So an average B2B seller will spill be in a productive selling activity talking to a prospect, either in a meeting, on a call, whatever, 24 to 30 percent of their life. That means you're paying them. So whatever you're spending per head on your sales team, you're wasting 70% of it with regard to productivity models.
SPEAKER_01And this is going back to that stat you shared earlier.
SPEAKER_00Yeah. So the objective is to free them up to do what they do best as close to 100% of the time as you can. And and you really touched on another another aspect of this, which is the emotional unlock. Those that toil, that manual toil, that manual activity, those are the parts of the job that every seller hates the most. Frick shit. Every marketer hates the most. Yep. Every SDR hates the most, every CSM hates the most. You know who hates it just as much as they do? The managers have to chase them to do it. And you're wasting the cycles of those managers too. Yeah, and the and the execs above them who have to chase the managers to get it done. The ripple effect of toil on productivity and emotional drag just goes through the organization like a tidal wave.
SPEAKER_01Interesting. The whole paradigm of the sales environment's gonna change. You're gonna need fewer people, they're gonna be better supported at higher momentum, higher speed. Incredible. Now, let's move on to the third thing that you talked about, which was this kind of breakthrough that you guys are having with the um agentic. I don't know if you can share the example you were telling me earlier, but um like it's kind of mind-blowing as you as a listener, if as you guys pay attention to what he's about to say, like I want you to think about how many people would have been involved and how much time would have been necessary to execute something that's now natural language initiated, go grab a cup of coffee.
SPEAKER_00Yeah, sure. So I'll give a couple examples. What Chris, what you're referring to is our conversation ahead of this meeting, which um so Oracle, we are we are about to ship our agent builder. And to put that into context, what does it mean? Well, because we're an AI native platform and the architecture already has embedded within our platform services an agentic workflow engine, you already can go into the Oracle platform and and build workflows that have agentic properties. And that is powerful. You know, it's very powerful. You can there's deep web research married together with AI logic research and and actions that are templated, and it's it's great. What we're shipping now is different, though. What we're shipping now is the ability, I'll give you a couple examples so it's like concrete for your listeners. One example, which um I just walked into a room at eight o'clock last night here in the in the office, and then a couple engineers and my co-founder and CTO were um, you know, asking what they're working on, and they demoed it to me. And and it was fantastic, you know, and and with two lines of just natural language prompts, meaning, hey, yeah. So this is the actual prompt. Hey, Oracle, tell me which of my users, which which users are the top three users of my product, how they use the product, and rec and recommend to them something that they might get more val additional value out of in the platform. And then build an automated sequence to share that information with them, expose and expose knowledge videos to teach them how to use it. So, you know, a couple sentences, natural language, like you might ask me to go do something. From there, Orcel's agent builder pulled in post hoc feeds, evaluated all the users' usage, ranked it by power users against features, derived the the logic and reasoning to understand what value would be unlocked in context of that user's business of our platform with those features, created a message around that, an outreach message around a message that was a sequence that Orcel executed to send that user a message, and then looked at what they're not using, again married it against the value hypothesis of that that our customer's core business, and then derived the reasoning for how they might benefit from understanding another capability in the platform, explained it to them, and then uh and then from there grabbed a knowledge-based video and embedded it. Now, the other thing that happened here was and we watched their run on the screen uh in Oracle in editor mode, is in the middle of all that, the our Oracle agent builder started writing code to go out and discover other fragmented data sources that were relevant to answering the question. So think about the fact that we pulled in post hoc data. We have value hypothesis information and other structured data in our CRM, of course. So it's using structured data from two different sources, and then based on that user, it went out and looked at the persona, and then it went out and used our agents to go gather information about external signals that would further inform it on what that person might find valuable. And then it wrote a connector into a data warehouse that's separate from our unstructured lake house, where additional data was stored. And it wrote that connector on the fly, gathered the user information, prompted where it didn't have it, established the connection, pulled in other unstructured data as part of its research and reasoning, and then came to a conclusion, executed it in an eight-step sequence, and with no with zero user interaction.
SPEAKER_01And while that's happening, the competition is saying, hey guys, on Tuesday we need to do a meeting. Okay, we need to plan this thing out, make sure the devs are gonna be there because we're gonna have some stuff for them, cueing it. Like you're talking about whatever just happened while you guys sat at that conference table. The competition is taking a few weeks just to get off, like get started. And correct.
SPEAKER_00Yeah. I mean, think about the old way of doing that. You would you would go on a journey, probably were a data engineer to ask them to pull together three different data, three or four different data sources.
SPEAKER_01But they've got a queue. They can't stop and do like I'll get to it later, kind of thing. Yeah.
SPEAKER_00And then you, you know, that would be served up to an exec somewhere, some list would get handed to a CS team and a sales team. They would then write out outreach based on that. Maybe they'd put it in a sequencer, maybe they wouldn't. Probably half of the org would actually execute the request. Yeah. And and then they'd get busy with contact switching on something else and you know, go do something else. And by the way, the the the when that you when that message goes out, it's not just about the outreach of the message, the interaction continues. So when that it that message is responded to, our agent continues the dialogue for as long as until it derives an action that it has to involve a human, all of that hits, notifies the human attached to the account. All of that hits a timeline in the account, so anybody involved in the team can see it. And at any point a human can step in and take over. But if the human doesn't, it's going to continue to work and engage. Um, in this way, it kind of goes to that like context switching, drop balls, lack of follow-up kind of movement. Yeah, yeah. Now, like human has the power to supersede at any point in time, but if you want to let it continue to go, it will. Um, like you know, and and like go like another example of extending that that workflow out is scheduling. It's just simply like, you know, can we would you like to have a meeting with one of our field deployed four deployed engineers to learn more about it in real time beyond this video? And if they say they come back and they say, sure, I'd love to, like, great. And it and it takes over the calendaring action, interaction, again, personalized, it's gonna feel like a human interaction to the end user on the other side, and then it'll go tap the right resource in our organization with that meeting happens and needs a human, and and off we go. And so that was one example. Another example, which is pretty cool, which I felt like was was really interesting, was is a RevOps example. And in this case, we told the agent because Oracle knows about the profile of the customers in our platform, we know we've sucked in their case studies, we know what they sell, what problems they solve, who they sell to, what their buyer personas are, ICP competitors, etc. Because we know all this information already, you know, now in Oracle, and if you were setting it up for the first time, like if a RevOps person wanted to establish a sales process, Oracle has an opinion on what sales process best practices would look like based on your company. And so now instead of thinking about going through this long design process and setting everything up in your system, a RevOps person, we did this demo last week. A RevOps person uh simply goes into Oracle and says, design a sales stage process and recommend sales frameworks that would best optimize outcomes for my company. That's it. You give that prompt, we run the research logic and and show you a visual of the sales stages and the sales frameworks, and it might be one, it might be three. It depends on your business that coexist. And then if you say, Great, go, Oracle goes to work building it and configuring it in the platform for you, that's it.
SPEAKER_01Dude, this is just it's not fair.
SPEAKER_00It's incre it's really the this is what I mean by unleashing the power of an AI native platform. The productivity just wipples throughout.
SPEAKER_01So for the listeners, I mean, obviously, this type of uh you know experience is occurring across other departments, but you know, the the easiest place to get big buy-in is show me the numbers, right? Like, is it impacting the revenue? And this is obviously uh uh mechanisms that will certainly do that. So for the people who are listening, because aren't our audience is all strata, obviously, but we do have a lot of uh lower middle market executives that listen to this um who probably hear this and it this sounds like magic to them. How do they get a peek behind the curtain and see some of that magic with Auracell?
SPEAKER_00Yeah, I mean it it it can feel like magic sometimes. Um so we you know we just reach out and we're happy to give you a demo. We um we do have, you know, there's a there's a short explainer demo that's on the new website coming up.
SPEAKER_01We'll have that in the show notes. Okay.
SPEAKER_00Yeah, if you want to check that out, you can hit the home page and click on it. And um you can schedule a meeting with any of our Oracle team right there live. Yeah, well, we still send human star meetings. We do use uh we do use our uh another agent we're about to ship soon in March, is our autonomous SDR agent. So we're using that internally. And our SDRs are just 100% on the phone now through our voice dialer. Wow. We removed all the other work from them. Yeah.
SPEAKER_01I'm interested in that for our our endeavors as well. So we'll have that.
SPEAKER_00But if you book it, if you book a demo, a human will show up, I promise.
SPEAKER_01Yeah. So we'll we'll have um links to that certainly in the show notes. But as far as like you sharing perspectives, do you like do you have time to even post on any of the social platforms or blog or anything for the company?
SPEAKER_00Man, I could be better at this. You know me too. I try. But uh so yes, I'll make a commitment to be better at it. What's best in cloud?
SPEAKER_01Okay. Where could people pay attention to it? Because we know what's happening in the marketplace here at Chief AI Officer, and what you guys are doing is advanced, but still accessible to companies that aren't, you know, all in on AI. I the way that you've explained things, I get it. I could not even know how all this stuff is working as a business owner, yet still have access to what I would consider cutting-edge, you know, capabilities of generative AI for my sales environment. So like as a as a listener who may not be as deep into it as you or I, I think that if they were to get more of your perspective, it would be easier for them to translate that to the rest of the team and say, guys, we got to do this, right? So, where do they pay attention to kind of how you're looking at this and how you're explaining it and the experiences that you're having talking to other businesses about it?
SPEAKER_00Great question. I am most active on LinkedIn. Um that would be the end the short answer.
SPEAKER_01Yeah, we'll put that, we'll put your LinkedIn handle in the show notes as well. Um, Jason, this is this is awesome. Like I'm kind of like the kid in in at Christmas kind of vibe, because every time I talk to somebody who's doing something cool on the podcast, I'm like, oh, I want to do that too. I mean, not not build the product, but use the product, right? So I'm actually gonna have our uh head of enterprise sales reach out and just go through the process as a customer and it'd be great. Yeah, what you're doing is pretty cool stuff. So thanks for taking the time out. I know that uh with as much travel as you're doing, with both of us having startups that are starting to take off, it's um tough to get people on the on for an hour on a uh a podcast, but I appreciate you sharing this with the community. And um any closing remarks or anything that you think we need to wrap this up with?
SPEAKER_00I think that I would just underscore again, if you're not if you're not doing this in a big way, assume that everybody's playing with AI at some point.
SPEAKER_01Yes.
SPEAKER_00You go to you go to a dinner party and everybody wants to tell you that they find out that you're in in in the industry and they want to tell you about how they use Chat GPT. You know, so everybody's playing with AI. So of course you have to assume that your competitors are. And again, I would just underscore that that now is the opportunity, now is the opportunistic time to really jump in and consider AI native approaches across the business and all of your workloads and workflows, because I do believe it's that it is the moment to create a gap. A really unfair gap in whatever it is that you do with your business. And you're right. The our technology and the way that we've built it is meant to deliver kind of this magical moment for all of the personas that we serve and their respective workflows. And it and it's intended to be automated in a way that it doesn't require you to think about the infrastructure behind it. And that makes it accessible to everyone. Um, so that is part of our design practice, it's part of our the way we built the platform. Um, so I'm glad to hear you say that. Yeah, I hope that that part of this conversation makes it a little less intimidating for those listeners who are considering doing more but nervous about jumping in or you know, taking an incremental approach to get started and just challenge themselves, like that company, that big company that I talked about before, is challenging themselves. You know, you can do that in any stage, whether you're a small, medium, or large business, uh, young or old. And uh other than that, I'd just say thank you, Chris. Thank you for having me on. It's always a pleasure to have a conversation with you. I think we could just kick around all of these stories and ideas for hours. And so this is a you know, I I very much enjoy uh joining your awesome.
SPEAKER_01Well, thank you again, Jason. And safe travels, I know you've got a bunch of business travel coming up. And uh for all of our listeners, my advice as always, go use AI. Thanks everybody, we'll see you on the next one. Thanks for tuning in to using AI at work. Don't forget to subscribe for more conversations about how to use AI at work. And a special thank you to our sponsor, Chief AI Officer, for empowering businesses with AI education and training. Visit their website for free AI readiness assessment and AI strategy guide to help you get started using AI at work. It's www.chiefaiofficer.com. Follow us on Twitter at the handle usingAI at work, and visit www.usingai at work.com for free resources to help you harness AI in your role.