In a significant move for Web3 social applications, MBD, a crypto-focused AI startup, has raised $3 million in a strategic pre-seed funding round. Co-led by Mask Network and Polymorphic Capital, the round includes backing from big names like a16z crypto CSX, Forward Research, Social Graph Ventures, and WAGMI. With support from Amazon Web Services and Google Cloud AI Startup Programs, MBD aims to bridge the gap between traditional Web2 recommendations and Web3’s decentralized future by delivering a fast, high-quality, and personalized content engine for blockchain-based social apps. 🚀
This post explores MBD's vision to bring sophisticated AI-powered recommender systems to Web3, how their technology compares to Web2 giants, and what it means for the future of decentralized social media.
Key Highlights 🌐
Why Recommender Systems Matter in Web3 Social 🧩
In the Web2 world, platforms like TikTok and Facebook keep users engaged with highly personalized recommendation engines. However, Web3 social platforms face unique challenges due to the vast and fragmented nature of on-chain data. While decentralized social networks like Farcaster, Zora, and Lens allow builders access to open social graphs, creating an engaging user experience requires more than data access—it demands real-time, high-quality content recommendations and robust moderation systems.
Here’s where MBD steps in:
with a specialized AI-powered content engine, MBD provides decentralized social networks with the ability to deliver dynamic, hyper-personalized content to each user. By harnessing on-chain data in real-time, MBD’s models can overcome Web3’s "cold start" problem and deliver content tailored to users’ interests, driving engagement on a scale previously only achievable by Web2 giants.
MBD’s Flagship Product: AI APIs for Web3 Developers ⚙️
MBD’s core offering is a set of machine-learning APIs that make it easy for Web3 developers to build highly engaging and relevant content feeds. These APIs support everything from personalized NFT recommendations to DeFi transaction insights, and they leverage both on-chain and off-chain data for an optimized user experience.
Key features include:
Real-Time Personalization: MBD’s models update dynamically, scoring over 50 content categories in real-time as users interact with blockchain networks.
Fast Response Times: The AI inference layer serves recommendations in under 150 milliseconds, handling billions of requests with ease.
No-Code Feed Builder: Accessible to developers of all levels, the feed builder allows anyone to create custom feeds filtered by dApps, topics, authors, and more.
Since launching in late 2023 with a focus on Farcaster, MBD has already onboarded hundreds of developers and processes over 100,000 monthly API requests in its public beta, demonstrating both demand and the scalability of its system.
Tackling Content Moderation in Web3 🔍
Decentralized social platforms face unique challenges when it comes to moderation. Without centralized oversight, these platforms are more susceptible to spam, farming, and malicious activity. MBD’s classification models, fine-tuned on Web3 data from platforms like Base, Ethereum, and Arweave, are designed to address these challenges.
With accuracy on par with leading AI models like OpenAI’s, but at a fraction of the cost, MBD’s moderation engine filters out bad actors while preserving the open nature of decentralized social media. This approach provides a scalable, community-driven moderation solution that aligns with Web3’s ethos of permissionless participation.
AI-Powered Recommendations with a Web3 Twist 🔄
MBD’s AI models are built to handle the unique data landscape of blockchain. While Web2 AI models like ChatGPT serve general tasks, MBD’s models are crypto-native, designed specifically for on-chain data.
Here’s how MBD’s approach differs:
Hyper-Personalization: MBD’s models track on-chain activities, using these signals to generate user-specific recommendations for NFTs, DeFi protocols, and social connections.
Real-Time Updates: The models refresh with every on-chain interaction, ensuring recommendations are always up-to-date.
Improved Coverage and Relevancy: MBD’s latest generation of ranking models has achieved a 3x improvement in relevance and a 10x increase in content coverage compared to popular Web2 feeds.
For Web3 developers, this means they can build apps with the same level of personalization and engagement as Web2 platforms, tailored to the unique requirements of the blockchain ecosystem.
Roadmap: Scaling the Future of Web3 Social 📅
Looking ahead, MBD has ambitious plans to expand its reach and drive adoption of its decentralized recommender systems. Here are the next steps:
Expanding Partnerships: MBD is actively partnering with more crypto consumer applications to bring hyper-personalized content to their platforms. Starting with Farcaster, MBD is scaling its models to support additional ecosystems across Web3.
Advanced Use Cases: Plans include deeper support for DeFi, personalized risk management, and innovative content recommendations, moving closer to what the team calls “social epistemology”—a new design space for transparent, community-driven social media algorithms.
Building Modular Intelligence Layers: MBD aims to be the intelligence layer for Web3, offering modular tools for developers to build, scale, and optimize social apps powered by on-chain data.
Final Thoughts 🌐
MBD’s $3 million funding and unique approach to AI-powered recommendations could be a game-changer for Web3 social apps. By bridging the gaps between user personalization, moderation, and the vastness of on-chain data, MBD brings crypto consumer applications closer to mainstream adoption. With real-time content engines on par with Web2 giants, MBD’s technology positions it as a vital infrastructure layer for the future of decentralized social networks.
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NOTE: This article is not a paid or sponsored post. It is intended solely for educational purposes. As always, please conduct thorough research (DYOR) before making any investment decisions in the cryptocurrency market.
