Cynario.AI | Lender Policy Research & Marketing - a Software Walkthrough

[00:00] Hi and welcome to Broker Tools, where we unpack the tools, systems, and strategies that help brokers optimize the way they work. I'm Katie, your host, and today we are catching up with Michael from Scenario. Scenario is the platform designed to help brokers model, analyze, and stress test financial scenarios, giving you a deeper insight into deals, cash flow, and risk before you commit. In this episode, we are going to explore how scenarios AI and enabled tools are helping brokers make smarter decisions faster. From policy research and comparison analysis to showing you lender options that you may have not considered, if you want to move beyond spreadsheets and gut feeling decisions into datadriven AI supported deal structuring, then this conversation is for you. Michael, welcome to the pod. >> What an introduction. My gosh, we got a lot to live up to to with that. All right, no pressure. >> You know, it's it's it's all true. >> It is true. Absolutely true. Well, I hope I live up to the truth. Let's let's

[01:02] see how we go. >> Which is I guess the thing. Um because we before we started doing the pod part, we always have like a before chat and we were really talking about the entrepreneurial journey that everybody goes on um before they start building out their thing. Um what was your entrepreneurial journey into scenario? >> Well my I I guess co which is an interesting I guess subject for a lot of people but co was is probably the reason why scenario was here or why I've done done scenario. So co forced me to to pivot out of another company that I had um didn't really align with the with co um and it and it brought me into finance. I'd always had an interest in it never had the time um like a lot of people co gave us a lot of time. So I came into mortgage broking 2021 uh new to industry, no experience, very excited to go and then it found myself spinning my wheels a lot trying to understand policy, learn policy, lenders change the policy. Um and like we were talking about earlier on finding different solutions. My ears pricricked up. AI had had sort of just started to to come out.

[02:04] Chat GPT was obviously leading the way. And I had a very naive idea that I could sort of build something to help my my journey to write some deals, understand policy. Um, and that has now transformed from from that into an enterprisegrade platform. I haven't written a loan in about three years. And um, yeah, now we're we're well away with with scenario and working with lenders. It's exciting. >> Yeah. And and to add to the excitement, the reason you and I are talking is because you were added into sales tracker and Heather and I had a conversation about how you were popped into there. >> Yes. Yeah. No, it was Yeah. Very exciting. So we Yeah, we started working on it trying to keep it as quiet as we could. um sort of like 3/4 of the way through last year. Um but yeah, really excited and I'm I'm sort of very passionate about working or looking at what other platforms are doing and and rather than trying to keep on rebuilding the wheel, it's like how can platforms um sort of work to work together in a more cohesive manner um to improve the outcomes for brokers. And it sort of it was a natural progression between us and and sales tracker that if we're if we're now looking to do um policy research

[03:07] doing it in an environment that puts it right inside the client like the client file um brokers don't have to come off sales tracker come like come back in it creates a smoother faster experience. Um yeah so I was really excited about that integration. It's it's going really well. >> Yeah. And I guess for those who are not coming from the podcast with Heather um and learning what sales tracker is um it is a CRM platform um that helps brokers capture their lead and management process. But in that process after the fact finds then it you know if you're looking for a lender policy that's where scenario can help you. >> That's right. So so within sales tracker it's called policy AI. So um sales tracker I won't steal there. Thunder are releasing a number of different AIs throughout their their CRM. Um we're like working with them closely on the policy sort of AI as a a chat interface within within sales tracker. So they can activate it within the platform, use it within the platform. Um and we just power it from all the data data intelligence in the back end. >> Nice. And this is really mostly specific to the resi mortgage space for lender

[04:12] policy. >> Yeah, it is. Um I'll I'll say currently um sort of you know we're we're it's it's amazing to think that you know scenario launched eight months ago and where we've come in sort of eight eight or nine months has been astronomical what what we're doing now we couldn't do when we first started um so yes we are focused towards res residential at the moment however we are sort of to build out into asset looking at commercial is an interesting beast given how gray and I guess limited some of the policy is in the commercial space but I think what we're looking at is whether AI is the right is the right tool um to to help brokers and if we can bring AI into it then we'll certainly look at solutions that can build out um different opportunities. >> Yeah. And of course we all have to like nail one before we expand. >> Correct. Exactly. Run before you can is it walk? No. Walk before you can run. I feel I feel at the moment we're running before we're walking. It's a it's AI is moving so so quickly um that every time we come up with a new new concept or a new product idea that we're sort of developing. Um it's that we've already got three more that we're thinking of.

[05:15] It's just it's a exciting space to be in. No rest for the wicked, >> which is I guess the exciting part because you're never going to rest because there's always something going on when it comes to the data side of it because I guess that's the next main concern when people have AI is how this going to either take my job or um my client's data, how am I safe? >> Yeah. In so yeah, data security is really really big. Um within the policy space, we're we're fortunate that we don't need any PII data or Yeah. personally identifiable information within the platform for it to run. Um, and I think that's a really big key and but also something across any tech platform that a broker is using um is to really think about what data they're providing and then how that platform is using that data. Is it sovereign? Is it staying in in Australia? Where's it hosted? Is it being deleted? Um I think there's now a lot of hype around AI similar to social media. um when Facebook and Instagram first came out, we were all very excited to throw all our photos up onto the platforms and

[06:17] then the penny dropped that now they have all of our our photos up in the platform and in a yeah similar way with security and data um is really thinking about how platforms are using the data that you're providing. Um yeah, as I say for us because we're dealing with the lender data. So it's more on their side more than anything else is they've been asking us like how are you hosting our data? What are you doing to our data? So we've got very strict protocols on the back end and and we're fortunate that um lenders are comfortable with what we're doing. >> Nice. And so ultimately when it comes to lender research when a a broker is coming in there are they entering data? I mean for for all intents and purposes scenario is a standalone product. It does not have to have um sales tracker as part of it. It's just a beautiful integration that um has been made available to those who do have sales tracker. >> Exactly. Correct. >> Um and so if someone was coming straight into scenario >> Yeah. >> what would they do? >> Well, probably is I could probably show

[07:21] you if I can share my screen. Okay. >> So, this is this is the platform as a broker would um would come into it. Um and within the platform and we can touch on both. Um we've now we've got um policy research with residential um and now we've also launched out our automated marketing suite um as well through another AI. We've given both our AIS different personas. So we have um Charlie which is residential policy and Alex that looks after marketing and the reason we did the or looked at the personas was more around how brokers engage with AI. I think AI has come to market so quickly that not many people really know how to engage with generative AI to get the answers that they need. Um so when we first did a pilot we just had a logo and it and some of the questions that brokers are asking were in their defense they didn't know were horrible like best home loan was one that came in and of course AI will always give you an answer but it's but that's not even a question you could ask a BDM. So when we brought personas into it, it was hey Charlie can you tell me the difference between X and Y or you know what's um hey Charlie what's

[08:23] Bendiggo bank's policy on X. So it became a lot more conversational which is what large language models need to perform. Um so as an as an example if we go uh what lenders and I always struggle to spell sometimes so pretty pretty simple most obviously most brokers will know this but effectively what what we do is the AI will go away hit all the lenders then and then come back. So the idea behind the platform um isn't necessarily to provide you with that specific one lender. It won't provide um credit advice. It's about providing guidance. And this is where sort of came from for me being new to industry is how can I take my lender panel of you know 30 40 however many lenders and narrow that search faster to find the lenders that will meet the the policy the lending criteria for for a client before getting into rates and everything else. If it doesn't meet policy, it's not going to be be a deal. um and how we've sort of built this and I know there's a lot of talk around hallucinations with data um within AI >> and and it was a massive learning curve when we when I first came up with the idea because I'm not I'm not techy I have a lot of the big ideas but um I

[09:26] can't >> um so when we we how we built out the system now is we isolate all the lender data within the system so if you ask a question about um Suncor for instance it will not give you an an answer back on say bank west so we've isolated the data in a way um that now we can we can start to sort of produce sort of comparison tables without that those hallucinations. Um so that sort of gives yeah gives an idea on sort of how how they can use use the system. Um and it can be across anything or residential. Um our biggest sort of I guess challenge and what we're working directly with lenders is is um optimizing their data. Um, for a lot of lenders, majority of lenders, this is really the first time that AI has been overlaid over their data in more more of a way, more of a comprehensive way than say a chatbot, which is effectively, you know, scraping PDFs and putting a an AI layer over the top. We've got multiple ingestion techniques in the back end to really optimize the data and structure it in a way to get the most most out of it. Um so from a lender perspective a lot of lenders are now starting to realize that

[10:29] a lot of the data within their broker portals actually need to provide more uh we had a case right at the beginning when we launched where a broker asked which lenders will allow me to write my own home loan as a broker and I won't name the lender but out of all the lenders on the platform there was only one lender that actually has it written into their policy that yes we do reach out to the BDM to discuss it. So it's not necessarily that the platform is bad if it comes back with one lender. A lot in a lot of cases it's it doesn't have the data in in the system and it's not making it up which is which is really good. Um but our biggest yeah focus now is to go back to lenders and go right the more data you can provide into the platform. The more comprehensive answer a broker is going to get the better the deal submission they're going to provide and so forth. So it's it works across the entire ecosystem versus just it's just policy research. It's got a far broader sort of appeal. Yeah. And it's really about providing opportunities that you may not have thought of because the data is there to support it. >> Yeah. And and we we found that sort of when we're running um some pilots, this

[11:32] would have been oh gosh um what now probably October 24 um we're running some pilots with with a group of brokers and and across cross-section of sort of inexperienced brokers like like me um and then some very high level experienced brokers. And even the experienced ones were finding lenders within the platform that they'd never never worked with before, didn't know their policy before. Um, one which I'd have loved to got a snippet of the the commission on it. Um, but found a found a deal for a client that he was going to flag but by putting into the system found a lender that could actually write um could actually do it within their policy. So it's it's a real education piece and it's also providing a lot more visibility to lenders outside of their STEM distribution channels within an aggregator because we are aggregator agnostic. We're um solely for broker um working with lenders but we're not aligned to any particular aggregator. >> Yeah. And having I guess this whole um non-aggregator service means that I call it aggregator agnostic. So, you know, >> it doesn't matter what kind of broker

[12:36] belief you come from. Um, it all like this type of service works for you. >> Yeah. Yeah. And I and I think being agnostic is is is important. Um, we don't allow lenders to to sponsor the platform for instance. Um, we put the onus back in terms of how how lenders are presented. This is probably a prime case of like, you know, why is Sonor um above Bank West? Um it's not alphabetical. Um we don't allow our lenders to sponsor the platform. It is based on how contextually relevant their data is to the question for so for example the better the the the better the data we have in the system from the lenders will support a better out output which will rank them rank them higher. So there's no way for you know for for a lender to come and sponsor the platform to be number one. I feel if we did that we have a direct conflict about what we're providing for brokers. Um so it is definitely a for all broker um platform. >> Um and I feel that's that's that's important for any anyone in in AI any any platform to really um own that in terms of if it's a if it's broker

[13:40] related it needs it has to be neutral. >> Yeah. And when people are using this outside of this what else do you take them through >> in terms of from a policy or or other products within the within the platform? >> Well I guess this is really all about the journey that a person might go through. So obviously you'll come in, do your scenario, pick a uh lender that works for you. Is there anything else that somebody else might be doing within scenario um to support their business and growth? >> Yes, probably. Um so our latest release takes takes it completely away from policy actually and into more marketing which has been to sort of build that out. Um I will say on the policy side and where it kind of where it works well with someone like sales tracker is to be able to continue that workflow from a policy in terms of client information identify the lender and then you can sort of build build that workflow. So I feel that's where integrations work work really well. Um if we sidebar and go to say let's go for marketing. So very very easy. We've got um Alex and Charlie. Um

[14:45] I'll do what I I'll show you quite a cool uh cool one that I did just before which is okay. So what we've built built out and this is this was AI generated what um what are we now probably about an hour ago. Um I did this one just before we jumped on. Um so what we've what we were looking at is how can we how can we leverage AI to improve workflows. Um as I was saying I was you know new to industry coming in. One thing I did notice is marketing is something that is exceptionally difficult for a lot of brokers. um not only in trying to how to market but also having the time to do it. So we we were thinking how can we sort of bring that into the platform. So within scenario now a broker can link all of these platforms directly um to scenario. So Instagram, their Facebook page, LinkedIn page, Google business and website within the brand settings. Actually I'll show you show you this. Let's have a look at this. >> Yeah. >> Um so within the brand brand settings they can add in their a primary and secondary brand color. They can add in and then the crazy one is they can also add in their profile image >> if they want. >> And then from there we can generate

[15:47] customiz customized content. Now in the back end of the system we've also integrated the AC's financial products and services marketing guidelines. Quite a mouthful. Um but because that is something I've seen a lot on on socials is some of the things that brokers post might not necessarily be that complaint sort of over promising. Um, so we put in a compliance layer. Obviously, it's still on the broker to check it. >> Human, >> sorry, >> we call it like human in the loop in the tech world. >> Always. And it's a massive thing. I I look at um AI from a like an 8020 perspective is if I can get AI to sort of do 80% of the grunt work up front and there is a 20% human oversight to make this work, then I I feel that's where it is. anyone that that wants AI to just take over everything 100% I think they're asking for problems [laughter] down the line but yeah so what we can do that so we can create all the content it it changes the content slightly as well because your your audience is slightly different on Facebook as it is to um to Instagram so it'll slightly tweak the wording based on the audience um goo uh

[16:52] Google business profile heavily underutilized by brokers I feel um in terms of sort of building organic ratings through through Google so we we managed to to API into there. Um, and then the other really cool one is it does a long form article which then they can instantly publish to their website um through WordPress. And I think the reason that that's good is is in terms of just organic SEO. The more content you're actually providing, keeping your website active, the better. And it it sort of builds out full articles. That's not a bad bad image of me sitting in front of the, you know, the Sydney Opera House. Um, they can also edit the content. So if they want to edit anything, put in different call to actions, change hashtags, all that sort of thing. And then the other thing, let's try it and see what happens. So if I click here, I can regenerate it and go uh make it let's go make it nighttime. And then let's I love doing live demonstrations, but I got no idea what's going going to happen. But the idea of regeneration, so you can sort of tweak the image um if you like as well. Obviously image generation, this is something that we couldn't do um god like six months ago. We were playing

[17:55] with it and it was just the time it would take. There we go. So now I'm down down at Darling Harour at at nighttime. >> Oh, nice. >> So it's a way that you could like because it does across multiple platforms. They literally can hit a bro can hit a button and it'll automatically post to Instagram, Facebook or all the different um platforms as they sort of go through. Um they can also download the image as well. So they can create their own image image library to have on their computer. Um and they can also copy the content as well if they prefer just just text content. So we're thinking you know how can we leverage AI to make brokers lives easier. Um and it's been exciting with the marketing side because you know obviously policies definitely down the I guess client solution but now marketing sort of starts to step into well this is now becoming a business solution um as well a lot more fun. Um, so that's our that's our latest. You know, there's a few we're working on a few other projects in the background that we may have to I think do another podcast um to talk through, but this is our latest release that we're sort of building. Um, and no, not not video yet. I have got asked

[18:57] quite a few times, are we doing video? >> Not yet. But >> but the word yet seems to come up a lot in what I say. So, >> well, you know, it's more important to beta test and thoroughly check it because as we all know, AI makes mistakes. >> Um, >> yes. >> And you're in the finance industry like this is not the zone to >> arms. [laughter] >> Well, it's fun on the the policy side. It's why we've actually hardcoded out interest rates um from lenders because I feel at the moment I I feel interest rates belong sort of on the aggregator platforms with everything and and we're relying on lender rate cards to come through and as you say if it misses a comparison rate or we can start getting into that gray area of are we providing guidance or are we providing um like credit advice. Um so importantly we whilst we're we're trying to get more data around say um product information from an interest rate perspective we we've held back um off that AI certainly got the capability um but it's more

[20:02] we've got to be sort of careful about where we sit in terms of from like compliance and guidance and advice and that sort of >> yeah and I guess how would that affect I guess credit analyst type roles because can you do a workshop a scenario? Um well it's interesting because now we're actually I guess moving from what we're doing for brokers um is now we're actually building out AI for lenders. Um so now that we've sort of before a lender comes on platform um we set up an isolated environment we um ingest all their data and then we give it back to them to stress test. Um mainly because we want them to realize about sort of what's missing what we can improve on to to make it more comprehensive for brokers. But where that's led to now is now lenders going, "Well, if if you if you're already managing and hosting our data and we're comfortable with that, can you could you provide us with a solution to help our BDM teams and and our credit teams?" So, we're in the process of building out for a few I can't say who at the moment, but um we're in the process of bu building out the core lenders to to help I guess broker channel from that side of the ecosystem as well. Um because you you

[21:04] know, we've got scenario now for for brokers, but then some brokers are still say going to rely on their their BDM and a call back. But if we can sort of pull that technology to make like to help BDM response time, then that improves it from that side as well. So it's really as we were talking about before how fragmented the industry can be. >> Yeah. >> We're really looking at and now and sort of how can we leverage AI to actually sort of start to bring those pieces of the puzzle together. >> Nice. And so I guess from a credit analyst point of view, you're always going to need a human in the loop. >> Oh abs. Absolutely. Yeah. Yeah. Defin definitely not. And I say this, the lender is definitely not looking to like how we can replace a team. It's how how can we enrich and and empower the team um that's there and and increase productivity because I was talking to a lender um last week and I said, "Well, how how does your credit team currently manage this?" I said, "Well, a deal comes in and they're literally going through their their their highle PDF to sort of make sure it fits." Like that's not that's not an efficient way to to scale an organization and why SLAs's can continually blow out. So, so it's not

[22:09] necessarily right and we're going to bring in a solution that's going to replace that team. So, we're going to bring in a solution that's going to make that team, you know, 5x or or 6x their productivity, which is there therefore going to improve the your business outcome. So, yeah, definitely more about empowering than replacement, >> which is I guess the gift of what um all is happening within AI. Um if you were to I guess address what's happening in the future of scenario and I guess AI uh what would [clears throat] you say is happening next? >> So so much [laughter] >> where to start and and the and the scape we spoke about before in is in terms of what we can can actually do now and then if we had this conversation in a four months time be like oh my gosh now we can do now we can do this. Um I I see it really as a um efficiency and productivity I think are two words that they're definitely thrown around around a lot and it's you know the sales buds word with with AI but I feel that's where that's where AI can really start to um sort of make headway within within

[23:12] the mortgage industry especially um you know you've got consumers and and and customers that are expecting insights faster. Um it's getting more and more competitive um within the broker channel. So I see any brokers that start to adopt and and adapt into AI technology are going to be so far ahead um in in a few years time. Sim similar to what happened I think with ecom you know when when it was brick and mortar stores um and then ecom came in there was a certain group that embraced it and ran with it and now have very successful businesses and then there's other ones that went no brick and mortar and this is just a fad >> and they're not here anymore. Yeah. And I see that's where that's where AI is is going to take this is people that get on board. It doesn't have to be in huge ways. I think we touched on this before we came on live is sort of the the amount of apps and the I guess the amount of hype around technology and then it becoming almost all too hard because you don't know where to start. And I think that sort of dip the toe in the water whether that's you know scenario whether that's HubSpot whether that whatever platform it is is sort of understanding what it can provide and

[24:15] just starting with something and then the flow on will be a natural progression. Um for the ones that don't um you're going to be you're a brick and mortar store. It's it's you know technology is going to run away. >> Yeah. And and and with time it happens. I guess my favorite recommendations for people who are beginning in any kind of uh CRM um or AI automation process is to just clean up your workflow like as in start at the beginning of how do you get a lead in and manage that particular lead and this is where scenario works best because you'll probably have gathered some data already from your client about what their personal circumstances are what the goals they're trying to have and then you can already do the pre-ressearch in scenario around that type of lender policy that might already match and then you go back into your CRM obviously update your notes um you know because you know data matters but then all the automation people are throwing a word around the word AI and automations and they're syncing them

[25:17] together um but I did a separate video on AI automations so if anybody wants to watch that go for it but um it's that part where if you just do some of the simple at the beginning you can just speed up with time. >> Oh, incredibly over time. I say once if if your if your workflow is out of sync, it doesn't matter how many apps you bring in or how how many like you know how much technologies it will not it it'll probably hinder more than anything else if you haven't got your actual workflow down pat. And so on just on that with with sort of broken notes and things um something you can do within scenario is when I come down here. So I'm just moving things around. Um you can actually download a a copy of the um the chat history. So so in terms of from a broken perspective is you can you can do this download and it's PDF timestamped which then you can insert straight into your um sort of CRM broker notes. So, we're trying, as you say, from those workflow efficiencies. It's like, well, that's that's where we can sort of start to to help. It's like here's you've done your research, here are the lenders into your CRM, which is

[26:20] where it works nicely, obviously with with 2.0. >> Perfect. And do you have other integrations that you work with? >> We're working on a few at the moment. Um, unfortunately, there's I've got NDAs in place at the moment, so I can't say too much. Um, we the reason that we've built this as a proprietary platform is we're 100% API capable. Um it's obviously a limitation from say a traditional like chatbot because you've got that you've got you don't own the tech you're sort of relying on another platform whereas everything we did and built is is out. So we are like talking to to some other other players in industry about how we could potentially um provide API integrations in um because it's I think it's a natural pathway um and I'm not I'm not scared even from from us talking to other platforms if they if they've got a solution that sort of meets um into our workflow that helps brokers. There's nothing to say that that we wouldn't integrate into into scenario either. I think that's that's where technology is a wonderful thing is that we've got the ability to really start to hone in and and reduce that fragmentation across the industry.

[27:22] >> Nice. Nice. I'm always a fan of a web hook. Do you know what I mean? Like hit a button. [laughter] >> They're definitely fun. >> What is there anything else you wanted to go over or show? >> Gosh. Um I'm trying to think now. Um look the the marketing side is probably the most the the the I guess our latest sort of um release. You know policy is something we're building on. I do get asked a lot in terms of what what lenders um are on platform. All the majors are on and we are sort of in in the process now of of onboarding more across different um you know panels. Um so that's hopefully coming over over the next few weeks. There'll be some major announcements with some other lenders dropping into the platform. No. >> Um um importantly, we you know, sales pitch, 21day free trial, no credit card. Um I'd much prefer brokers to actually get on, try it, experience it, um with no risk. Um that's that's an important part of what we're what we're doing is building out a platform that is actually going to work. I love feedback. Love feedback to um from brokers and good and

[28:26] bad. Good feedback is nice. is good for my ego. But if we don't get the the the hard to prove feedback, whether it's there's an issue with with lender data that like there's something not right, that's what helps us to improve improve the system. Um and the actually the really cool tech which um is only available in scenarios uh is the ability to email um you can email our AI versus even coming onto the platform. So we spent two and a half years building this out this beautiful platform. Um and then and again about workflows we're going well >> one thing that I'm noticing especially attending a lot of the conferences around app fatigue because I've come in saying right you need scenario for policy and then you you know you need your CRM platform for this and there's all the broker portals. So we looked at well how can we actually bring bring that back into what a broker's already using. So now instead of coming on to platform, a broker can email our AI just like that email of BDM, ask the same question they would in platform and get a response within 60 seconds back to their inbox and then they can communicate just like they would with the BDM over email

[29:29] record of it. So So that's Charlie.ai. If any brokers want to try that try that technology out, they're welcome to. But that's a really Yeah, that's a really cool feature we sort of built out for that. >> I love it. Yeah. So obviously we've spoken a lot about policy but again your other key feature is marketing. Did you want to go over some of those cool I mean obviously we've talked about the chat marketing how you can do the AI integrations and have images created but then there's this other part I think. >> Yes. So you could probably more so probably going on to the on the website as well. So if I just this will give a sort of a better idea from a a website perspective. So we talked about sort of social media platforms and be able to to do Instagram and Facebook what it can do. Everything on this page is completely AI generated through through scenario. Every image, every blog article. Um so this is where it can become exceptionally powerful from a website perspective to start build I guess digital authority. Um and especially from an organic SEO perspective. The more you're updating your website and keeping it live with content, the the better the rankings as

[30:33] well. So this is something that we've built in currently only available for WordPress websites. We are working um on the other platforms as well. It's just how good their their APIs are. Um but this is something that >> yeah brokers can only do through um scenario and it and it builds off the same image that um the the original sort of where where's it gone? >> Oh, so like the one that you had in your profile picture. >> No, that's so that's so um that's Charlie. That's one of our our AIS which I I assure everyone she's not real as I have to keep reminding my wife a lot of. Uh, sorry. What I meant was in your platform when you went into your settings. >> Oh, yes. That one photo, not the not the one. >> Where are we? This one here. That one. >> Yeah. So, in your settings, you created a profile within scenario. It takes the image from that. >> It t Yes. Yeah. To generate these images here. So, yeah. Takes my my profile image, puts it here. Um, and then also then generates a bigger long form article with a a larger image as well, which that then goes straight into the

[31:34] the WordPress. So we are looking at other platforms and how we can bring and I guess you know like cross mapping to other socials as well. Um these are the majors. Obviously Tik Tok's more video focused. I'm not going to say we we we're not going to do video. It's more of a at the moment it's a not yet. >> Not yet. >> Yeah. But it's it's fascinating how quickly especially with um likes of Nano Banana and some of the the video models. It's it is fascinating what is being projected at the moment. >> Yeah. [snorts] So, watch watch this space. We'll have to do another another podcast soon. >> Yeah, always. Um, if people want to learn more about Scenario and what you offer, where should they go and what should they do? >> Okay, so here's the the plug. Scenario.ai. Kept it very simple. C Y N A R IO. Um, play on words there.ai. Um, we are in the process of rebranding our entire website. So, that will hopefully launch over the next u next few weeks. Um, but that'll have all the information. It's got a live video so they can actually have a look at how the

[32:36] platform works. We haven't sped it up every all the videos on there are in real time. Um and then if they want to try um 21day free trial, no credit card, full access um on platform to um Charlie for policy research. Alex, they can link up all their accounts and actually try that for 21 days as well. Um and yeah, provide provide the feedback. That's what we're here for. I think any platform um in this space wants feedback. Um, you know, feedback is what builds builds it and makes it better. >> Yeah, nothing like it. Um, thank you, Michael, for joining us on this pod chat. Um, I really appreciate it. Um, for those who of you who are enjoying this conversation, if you do have comments, please feel free to put them down below. If you want us to host another podcast on something else, feel free to share out. Um, we will talk forever on AI. Um, it's it's our jam. [laughter] Down that rabbit hole we go. >> Oh my gosh, the rabbit holes we go down. Anyway, um, thanks again, Michael, for joining me. Um, I appreciate you.

[33:40] >> More than welcome. Thanks for having me. >> You're welcome. Bye. I