Recall Airdrop

Problem Solved

Modern AI agents lack a way to prove their reliability and expertise to the world. With potentially “50 billion agents online by 2030,” there’s a pressing need for a trust layer so we know which AI agents are competent and aligned with human needs. Traditional AI benchmarks are centralized or opaque, and AI models operate in silos without reputations. Recall tackles this by introducing on-chain, crowdsourced competitions where agents face real challenges (like trading strategies, Q&A, etc.) in a transparent arena. Every agent’s actions and performance are immutably recorded, allowing anyone to verify results.

This approach establishes provable reputation for agents over time and incentivizes them to improve. Unique features include a blockchain-based “memory” for agents to store knowledge and cryptoeconomic rewards for honest participation. In effect, Recall turns AI development into a provably fair game: the best agents earn on-chain credibility and rewards, solving the trust and discovery problem in the burgeoning multi-agent economy.

Tokenomics

While exact supply and distribution aren’t public yet (as the project is still in testnet), the token’s utility is clear. All agent actions on Recall’s network require spending tokens or credits. In practice, users obtain Recall testnet tokens from the faucet and then convert them to “credits” via the Recall Portal. This hints at a two-tier token model: the RECALL token fuels the network (for governance, staking, or gas fees), while credits (purchased with tokens) are used for operational costs like competition entry fees or data storage.

Once mainnet launches, we can expect a fixed supply and allocation split between the team, investors, and community. Given the large backing (~$40M raised) and emphasis on community incentives, a significant portion may go to community rewards (airdrop, competitions). Early users are already earning Fragments (points) in testnet, which are said to translate to future token rewards. This suggests token distribution will heavily favor active participants.

Additionally, to promote credible neutrality, the Recall Foundation will likely oversee token allocation to ensure no single entity controls the network. However, investors and team (from 3Box/Textile) will hold a notable stake, so community governance mechanisms will be key to gradually decentralize control.

Perspectives

Recall’s long-term vision is to become the intelligence layer of the internet for AI agents. In practical terms, if autonomous agents truly proliferate, Recall could serve as their collective memory, app store, and proving ground.

The project’s roadmap hints at expansion in several areas. First, more competitions across diverse domains are coming – after the initial crypto trading challenge, we might see AI agents competing in language tasks, gaming, scientific research, or real-world IoT scenarios. Each competition adds to a growing library of benchmarks and on-chain knowledge. Second, technical expansion: the team is integrating with popular AI frameworks (LangChain, Model Context Protocol, etc.) to onboard developers, and they could explore dedicated sidechains or scaling solutions to handle billions of agents (their custom chain already uses a Filecoin/EVM hybrid approach under the hood).

There’s also the prospect of an open marketplace where agents not only compete but also buy/sell “alpha” (valuable data or strategies) among themselves on-chain. Given early involvement of leaders from Protocol Labs and Near in Recall’s events, future collaboration with other ecosystems (for storage, compute, or identity) is likely. Overall, Recall’s market fit seems strong if the AI agent trend continues – it positions itself as a crucial infrastructure bridging AI and blockchain. The long-term success will depend on whether autonomous agents find real adoption and if Recall can maintain a thriving, developer-friendly network before big tech or other projects catch up.

Founders and Team

Recall is helmed by a highly experienced team that formed from the merge of Textile and 3Box Labs - two pioneers in decentralized data. Andrew Hill, former CEO of Textile, now leads Recall Labs as co-founder & CEO. He brings a track record of building Web3 infrastructure (Textile’s products like Tableland and Powergate integrated IPFS/Filecoin). Alongside him is Michael Sena, co-founder of 3Box Labs (the team behind Ceramic Network), who now drives Recall’s product and strategy. This combined team has deep expertise in decentralized storage, databases, and identity, exactly the skillset needed to build an on-chain AI data network.  

The merger between Textile and 3Box Labs to create Recall means the team isn’t a fresh startup but a unification of two veteran groups – they’ve previously delivered production networks and secured major partnerships. Supporting Hill and Sena is a roster of engineers and researchers, while the governance and community efforts of the project are overseen by the Recall Foundation (a non-profit steward), adding credibility to the initiative.

In terms of capacity to deliver, the founders have raised significant capital and navigated Web3’s challenges before. Their visibility in the space (e.g. Andrew Hill speaking at major events, partnerships with Filecoin’s ecosystem) indicates they can attract talent and users. Overall, the team’s pedigree bodes well for executing Recall’s roadmap.

Funding

Recall emerged with a strong funding base for a project at this stage. The combined entity (3Box Labs + Textile) has raised at least $42 million from venture backers since 2019. Notable investors include Union Square Ventures (USV), CoinFund, and Multicoin Capital – firms that originally backed Ceramic and Textile. In addition, community sources report participation from Coinbase Ventures, Animoca Brands, Jump Crypto and others in recent rounds, which aligns with the high total raise. This means Recall has plenty of runway to build out its network and incentivize early users.

The project has already allocated a $25,000 USDC prize pool for its first competition and launched an extensive points program – indicating funds are being used to bootstrap the ecosystem. In March 2025, the team established the Recall Foundation to steward the network with a focus on long-term sustainability. This suggests that some funding is earmarked for grants, community rewards, and maintaining infrastructure beyond just core development. 

With backing from top-tier VCs and strategic investors, Recall likely has access to not just money but also advisory support and integrations across the industry. The downside of heavy VC funding is potential token supply overhang (investors will eventually expect returns), but the presence of a foundation and the emphasis on community points imply that Recall’s funding will be used in a user-aligned way.

Community

Within the first month of Recall’s public testnet, over 60,000 people tried it out, generating 400k+ on-chain transactions on Recall’s network – a strong sign of early interest. The project’s Twitter (X) account amassed around 225,000 followers, and the Discord grew to 125,000 members virtually overnight thanks to the “Surge” points campaign. This makes Recall’s community one of the fastest-growing in the crypto AI space. Much of this growth is driven by airdrop hunters and enthusiasts attracted by the points program.

Sentiment on crypto Twitter and Telegram is highly bullish – many users call Recall a top upcoming airdrop, with some speculating rewards “up to $5k” for active participants. Hashtags and guides about Recall are trending in airdrop circles, indicating strong grassroots marketing (albeit incentive-driven).

The team hosted events like ETHDenver Signals (featuring prominent figures like Juan Benet), which added legitimacy and attracted AI developers. Over 1,000 developer teams applied to the first AlphaWave competition, showing that it’s not just social media noise – builders are interested too. The presence of real coding activity (agents being built, hackathons, etc.) alongside the usual meme/GM chatter is a healthy sign. That said, sustaining community interest long-term will require delivering updates; airdrop chasers are fickle and will leave if they sense no imminent rewards.

Competitors

Recall operates in a crowded AI x crypto field with projects like Fetch.ai, SingularityNET, Ocean Protocol, Autonolas, and others tackling similar challenges around decentralized agents, AI services, and data markets. However, most focus on marketplaces, tooling, or infrastructure layers, while Recall centers on verifiable performance through public competitions. Rather than simply enabling agent interactions, Recall actively ranks and rewards them based on how they perform in real-world challenges.

This transparent, merit-based approach creates a clear trust layer – something missing in most rivals. Traditional players like Kaggle or Web2 AI platforms offer evaluation but lack crypto incentives and composability. On-chain AI agent protocols exist but rarely emphasize reputation or cross-agent memory. Recall’s edge lies in combining a neutral blockchain, competition layer, and agent memory system, carving a niche others haven’t. That said, the space is getting noisy, and maintaining differentiation as “the proving ground” for agents will depend on constant execution and meaningful competition design.