Reploy Ai: Huge GEM in the AI Agent Space ($RAI)

This month has been a really big month for AI and crypto. Now you might think, oh, are we gonna talk about another AI project? Well, yes we are because this one is super important because these guys aren't an abstract AI agent model that's not gonna be released for you know sometime next year. These guys already have a working API into their model that already works and has huge implications. We're actually talking about three of them today. It applies to programmers, it applies to traders, and lastly applies for entire companies that want to make money in crypto. So the project that we will talk about is Reploy. They're building a world-class AI architecture for native Web3 products. But wait Michael, we already have OpenAI and DeepSeek. Why do we need Reploy? Exactly, I think that's a really good question. So I would view this almost like, let's say for example you're going to a doctor. Yeah. Okay, I have a heart problem. Alright, I feel like maybe there's something wrong there. I go to my family doctor, general practitioner, I'll be like, yo bro, something's wrong. Yeah. And then you'll be like, operate? Would you like me to operate on you? No, I want to say a specialist. So that is the specialist. So Reploy is like the specialist. So when you go and you talk to someone like DeepSeek, that's the general one. It knows a little bit of everything. It's trained on every single bit of text that they can find. But it's not specialized. It doesn't really know the in-depth of crypto. It's not focused on crypto and it's not like super tuned to crypto. Which is why you want a crypto specific one. So the crypto specific one maybe it's trained more on the data from smart contract information. So it knows a little bit more how to program specifically for responsibility rather than shoving in bits of Python or JavaScript ideology there. So that's that's where it's really at. So this is your specialist for crypto that once you finish with the general ones, you go to a specialist to do that. So in this video we're going to talk about everything that why Reploy is really important, why we're excited for it, but also stay to the end because we actually did a deep dive into Reploy and there are some upcoming features that are exciting, but also there's some of the limitations as well which we'll talk towards the end of this video. So why we're talking about this video now is because Reploy does have a token. They have the RAI token. Currently it's priced at $2.40. It kind of kind of pulled back a bit after the AI hype is gone, but what we really think is that because they have an actual product with a use case, this can be a very powerful kind of initiator for the next cycle when people actually do start to use it like Reploy. With that of course everything covered here is my personal opinion, not financial advice. Let's get started. So to start this video off, I think we really need to establish something that's important. So Ron, do you know how much an AI engineer gets paid these days? Here you go. This is the full source of how much a Web3 developer makes. 102k to 188k per year. Wow. And then you have Ethereum Solidity developers averaging 150k a year. Or plus, right? With machine learning and crypto, that's a 200k plus salary for these guys. So why I say this is because these guys get paid a lot. So if you can increase the efficiency or effectively if you can replace a few of them, you will be saving a lot of money. Which is where Reploy can actually make its biggest impact. I think this is the number one feature for Reploy is its Reploy editor. So this is directly for people like programmers, for people who want to have a little bit of exposure, or even launch their own token. So what it does is it basically allows you to just type in plain text, make me a contract, that does staking. And you can see what the video does is it just automatically generates a staking contract for you. It's like no code required. And the best part about this is that the way Web3 works is that you want to reuse as much good code as possible. You don't want to come up with something new. You just want to use code that other people have been written and validated. Which is why kind of a model like this actually makes sense. Because at the end of the day, it's trained on existing material, and then it can regurgitate that out, and then say, Hey look, I got this for you boss. And then it has none of the flaws that sometimes you see in other contracts because it's battle-tested. So if you can regurgitate battle-tested code for you, then you basically save a lot of time making these contracts. Maybe that's why their name is Reploy. Oh, Reploy. Oh! So that's actually what makes it very powerful. Now a lot of people don't really understand that what you need for something like this is you don't need a general model. You need a model that is extremely well-trained on smart contracts that are validated and it knows why it does this. Like why does it need smart math? Because we have potential collapse of tokens before because of looping or anything like that. So basically if you want to generate these contracts, and if you want to generate them well, then Reploy already has a tool for that, which is their smart editor for programmers. So that's the first one. So it's kind of designed there to, A, for kind of two purposes. One, if you're already a developer in crypto, they can use it to help you write code and save you time. So if you can save half the time of a senior engineer, that's $100K a year, right? Or if you're new to launching tokens and you just want to do it yourself, you can YOLO do it yourself without hiring a smart contract engineer. That's actually very helpful because, you know, over the past year, we've seen celebrities, we've seen politicians making their own token, right? But of course they're not the one who made it. There's a developer behind them. And I think nine out of ten times, those devs actually bundled the supply for themselves and then they end up rugging. Yeah. That's why technically speaking, if you're a smart KOL, what you do is, even if you hire a developer, you should run that code on your own. Yeah. Then you're like, oh, hey. Yeah. You can double check. It's just an additional way to validate something that's going on. So they have a few models already and this is kind of the comparison chart. So right now they have plus and pro models. What they have is they have essentially part editor, but they have custom models and AI constructors that are kind of the innovator here. And because it's trained already on crypto data, even though the model is smaller. So you look at something like GPT or something like DeepSeq, they're very general. Here they're trained specifically on blockchain data, which actually makes them very powerful for a blockchain applications. So this goes back to our specialist idea. So the equivalent here is that if you're looking at all these models, like let's say, for example, the open AI models or DeepSeq models, they might be very good at quality and then they might be very good at analysis for science and maths. There's actually like a, this is like a really great website. I've been looking at this like nonstop to compare which models are better. But one measurement they don't have and they don't show here is how good they are for crypto. Yeah. For this one, this is a crypto specific model. So this is why years down the road when Web3 is super popular and everyone wants to do it, you'll see this model ranking higher for crypto content than anything else out there. So next up is trading. So number two feature is trading. And yet again, this AI is more geared towards trading. It has kind of more webs, more access to data out there. So one example that they showed here is that if you ask, say a traditional LOM from Web2 about like, what's Ethereum trading at and what it's going for, its data is slightly outdated, right? But here with Replay 0.5, Argentica, sorry, I can't pronounce things today. But with Argentica, it's designed especially for trading. And yet again, it can give that live information that it needs. And yet again, I was showing Ron a little bit today, you know, how to automate things. And yet again, a lot of times a trader will make bots that will rely and need information. And this is what their Reploy Oracle is. It's essentially providing that data, but in a very easy readable access and with direct API access for it, which allows it to kind of just feed that information into a trade bot. The key point here is because it's smaller parameters, it actually runs faster. And because this model runs faster, it can essentially get data. It can get data and make this bot even more competitive. So I think that's kind of the big difference here. Like a lot of people, they're thinking, Oh, why don't I just use OpenAI? But OpenAI is not optimized for trading. You want less than 400 millisecond latency. You want that to be fast. You want to out-compete everyone else on the market. On top of that, they actually have crypto specific functions here that can call upon. And then again, you can get Ethereum prices and you can beat everyone for your trade. So you can beat everyone else. Yeah, I think as a trader, this feature is really powerful, especially if it gets to a point where that model can identify entry model patterns, right? Because as a trader and I myself do this is I just look at the chart and see if there's any familiar entry model that is appearing. But the problem is it takes a lot of time to form and sometimes you're sleeping, sometimes you're away and then it forms, but you're sleeping, you're away. So you don't take that entry. So I think having this and then pair that with a notification system, that's going to be very powerful. Exactly. And lastly, and most powerfully are the AI agents. So this directly allows powerful AI agents that can be used. So because they're their own AI model, they can allow that direct access that we've been talking about, integrate all these features and start running those bots. So this is actually a video of their stuff already running and some of the ideas that can do. But at the end of the day, this is where the agents take control and you don't have to do anything. That's the end result. Now, of course, this is a wait list, so it's still in progress and you can kind of really test it out. But what's available already is the Fisher, their basically the AI models and their kind of just smart chat agent is already ready. So lastly, strengths and advantages. So strength of this is that they built their own language model with their own model with 7 and 14 billion parameters and scaling that. And yet again, it doesn't mean that more is better. It just means it's very specific. And that means that's kind of the secret sauce. That's their mode. So instead of being a general doctor, they're specific to that one problem, which is Web 3, which makes it really powerful, fast and more powerful. Then what they also have is they have kind of the infrastructure set up for developers to deploy in here. Now, there are some disadvantages though. So we did try a little bit. So actually tried to make a few requests to their API and it works. But there's the kind of the script specific ones, say for example, blockchain queries and responses, that's still coming and it's coming in progress. So there's still a few functionalities that's in progress and you still have to wait for. I think it's kind of like everything else out here. It's they can show you the little, the tiny little breadcrumbs. So once you get to the house, they're like, oh, it's in progress until Q1 2025. So it's coming very soon. But once you can try that out, I think that's going to be very powerful, especially when it comes to Argentica, which allows you to trade and gives you that trading information. And what's good about them right now is that the API keys can already be activated. So you can create your own key and start already running and checking things out. So you can just copy this and actually go technically don't copy mine, please. But what's happening right now is that there's multiple plans for how you use your keys and how it's funded. So say, for example, we can upgrade to the plus plan and pay with your credit card and pay the for this service and you can pay with Ryan as well. And this is for developer. This is like initially it might be for developers, but think about it. If you're a developer and you're getting paid 200K a year, your company will gladly pay $80 a month to make you slightly better. Even if it's just like 5%, 10% better, it's a deal. It's a steal, right? So you can actually, this is how much their plan is, but it's already a revenue generating system and they already can buy the pro plans as well. So they can do that. They can also get additional, you know, more powerful access to it. I can see traders buying these keys when they need it because if you're setting up for and looking for those opportunities, they can just run that model, look for the opportunity, notify, go trade, right? That's basically what it is. Now they have a revenue share model, which is what the token is for. So once they start making money, the revenue goes towards the token buybacks. Yeah, it's crazy. The payout is actually also in USDT. So really, really good looking nice. And that's why we're looking at it now. I feel like they have a good product. They had a hype, but now at the same time, they found the support as well. So, and again, not financial advice. All right. So with that, guys, thank you guys so much for tuning in today's episode. All right. I hope you learned. I hope I didn't nerd you out too much, Ron. I love this. I love this. I feel like we need to learn these so that AI doesn't come for our job. Yeah. I think Ron's professionally afraid. You've been like, can I reveal this? Like, even when you're slightly tipsy and drunk, you're like, Michael, AI is coming for me. I said that? Yeah, you said that. Yeah, you did. You don't remember? You're like, oh, I don't want to get replaced by AI. Oh, in the Uber. Yeah, in the Uber. Exactly. So, so, so, yeah. So this is why we're being kept up to date. And the threat is real though, Ron. Yeah, it's real. Very, very real. It's very, very real. And we'll show you guys some stuff that we're working on, how we're using AI as well. If you guys like that, make sure you subscribe to this channel. But we want to make your life easier too and save you a lot of time in crypto. So definitely, definitely subscribe and watch our next video when it comes out. Peace. Shalom.