Ruvi AI's presale surges 50% as BlockDAG raises $342 million

Artificial intelligence projects have once again captured the spotlight, with Ruvi AI's presale generating significant buzz. The project recently experienced a 50% price surge in one phase, accumulating a total of $2.3 million in presale funds. Projections of up to 66x returns post-launch have fueled excitement and increased coverage about its future price potential.

In contrast, BlockDAG (BDAG) is demonstrating consistent traction with over $342 million already raised and confirmed listings across 20 global exchanges. Unlike Ruvi AI, which relies heavily on speculation, BDAG’s strategic presale approach is translating directly into large-scale engagement and measurable outcomes.

Ruvi AI, positioning itself as a bridge between blockchain and advanced AI features, combines auto-trading, predictive tools, and generative capabilities under one platform. The current hype cycle has generated significant interest in getting early exposure based on these speculative figures. However, much of the discussion around Ruvi AI remains rooted in assumptions, with limited transparency about the platform's roadmap and milestones. While the project's outreach through influencers and digital marketing is gaining traction, the lack of a working product poses risks once market sentiment weakens.

BlockDAG, on the other hand, is showcasing visible progress. The presale has exceeded $342 million, with over 24 billion BDAG coins sold across 29 batches. The batch 29 price stands at $0.0016, available until August 11th. Early supporters have already experienced a 2,660% rise in value since the initial batch. BlockDAG’s listing deals on 20 top exchanges confirm widespread access and high liquidity potential, setting the project up for scalability post-GLOBAL LAUNCH Release.

An additional sign of traction is the project’s unique buyer battles, a daily presale event featuring a 50 million BDAG pool. If the total isn’t fully acquired in a day, the remaining tokens are granted to the top spender. This setup combines reward incentives with competition, leading to over $50 million in cumulative buyer battle participation so far. By gamifying purchase volumes, BlockDAG motivates community action through daily leaderboard recognition, reflecting social proof, engagement, and measurable progress beyond the usual presale mechanics.

With both listings and buyer involvement accelerating, BlockDAG is offering more than plans; it’s delivering systems that engage and retain community momentum. While Ruvi AI’s rise has been quick, supported by a notable 50% price increase and bold projections, much of it rests on future expectations rather than current delivery. With no working product and limited access to detailed roadmap milestones, long-term confidence depends heavily on external sentiment.

BlockDAG, in contrast, is already executing. Its crypto presale structure is actively driving participation, with the buyer battles alone pulling in over $50 million. With major exchange listings already secured and a robust system fueling consistent engagement, BDAG’s progress is anchored in active systems, not projections. While hype may capture initial excitement, structured delivery and scalable systems tend to build lasting value. Between the two, BlockDAG appears to have laid down a stronger operational foundation.

There’s no denying that Ruvi AI has captured attention, and current forecasts for Ruvi AI’s price prediction have sparked considerable interest. But that momentum still depends on continued market enthusiasm until tangible delivery arrives. On the flip side, BlockDAG is already functioning on a large scale. With $342 million raised, 20 confirmed exchange partnerships, and daily buyer battles attracting significant capital, the project is providing real mechanisms that convert interest into ongoing traction. Rather than relying on hype, BlockDAG is showing measurable delivery. For those seeking signals backed by structure and activity, this is one project actively building the foundation it needs for long-term relevance.