Written by: Dima Khanarin
Compiled by: 深潮 TechFlow
The field of Crypto and AI integration is rapidly evolving. After the conclusion of Devcon, I compiled a map covering all known projects to help everyone better understand the current state of this field.
This map categorizes projects into the following three categories:
Applications (Apps)
Middleware
Infrastructure (Infra)
Each category includes funding data and launched token information.
1. Applications (31 projects, total funding over $240 million, 8 tokens launched, total FDV over $300 million):
1.1) DeFi applications
6 projects, funding of $1 million, currently no tokens launched.
Including @rug_ai, @RPS_Labs, etc.
1.2) Chatbots
4 projects, 1 token launched, total FDV over $10 million.
For example, @Libertai_DAI, etc.
1.3) Payment applications
6 projects, funding of $33 million, currently no tokens launched.
Representative projects include:
@PaymanAI (funding of $13.8 million);
@trySkyfire (funding of $9.5 million);
@BitteProtocol (funding of $7.5 million), etc.
1.4) AI agents and influencers
More than 10 projects, with 10+ tokens launched, total FDV over $300 million.
Including TT, ai16z, Zerebro, @centienceio, etc.
1.5) Engineering and security
4 projects, funding of $33 million, 2 tokens launched, total FDV over $200 million.
For example:
@Chain_GPT ($CGPT, FDV of $12 million);
@FortaNetwork ($FORT, FDV of $10 million);
@MetaTrustLabs (funding of $10 million), etc.
1.6) Consumer applications
6 projects, funding of $12 million, 2 tokens launched, total FDV over $10 million.
Including:
@aiarena_ ($NRN, FDV of $8 million);
@bottoproject ($BOTTO, FDV of $60 million), etc.
1.7) Intelligent tools
4 projects, funding of $163 million, 2 tokens launched, total FDV over $200 million.
For example, Arkham Intel ($ARKM, FDV of $2 billion), Kaito, Dune, and Messari.
2. Middleware (106 projects, total funding over $800 million, 25 tokens launched, total FDV over $1.8 billion):
2.1) Training and collaboration
16 projects, funding of $120 million, 4 tokens launched, total FDV over $10 billion.
Including well-known Bittensor and Sentient, as well as @assisterr, @Pluralis__, etc.
Tradable tokens include:
@Dither_Solana ($DITH, FDV of $10 million);
@hyper_tensor ($TENSOR, FDV of $25 million);
@communeaidotorg ($COMAI, FDV of $200 million).
2.2) Inference services
17 projects, funding of $5.7 million, 2 tokens launched, total FDV over $5 million.
For example:
Allora Network (funding of $35 million);
@OpenGradient (funding of $8.5 million);
@hyperbolic_labs (Funding of $7 million);
And small teams like @openex_network ($OEX, FDV of $45 million).
2.3) Data platforms and monetization
23 projects, funding of $240 million, 7 tokens launched, total FDV over $1 billion.
With many well-funded protocols:
Story Protocol (raised $134.3 million);
Space and Time (raised $50 million);
@SaharaLabsAI (raised $43 million);
Ocean Protocol ($OCEAN, FDV of $500 million);
Vana (raised $25 million);
Hivemapper ($HONEY, FDV of $500 million).
2.4) Privacy protection
14 projects, funding of $250 million, 2 tokens launched, total FDV over $800 million.
For example:
Zama (funding of $82.3 million);
Oasis Protocol ($ROSE, FDV of $800 million), etc.
2.5) Agent platforms
24 projects, funding of $17.5 million, 6 tokens launched, total FDV over $6.5 billion.
Including:
Fetch AI ($FET, FDV of $3.5 billion);
@Spectral_Labs ($SPEC, FDV of $1 billion);
@virtuals_io ($VIRTUAL, FDV of $450 million);
@autonolas ($OLAS, FDV of $850 million);
@MorpheusAIs ($MOR, FDV of $800 million).
2.6) Research
3 projects, funding of $5 million, currently no tokens launched.
These projects focus on cutting-edge research in AI and blockchain, with representative teams including @NousResearch, @physynAI, and @peri_labs.
2.7) Data collection and labeling
9 projects, funding of $30 million, 1 token launched, total FDV over $120 million.
Representative projects include:
@getmasafi ($MASA, FDV of $12.6 million);
@din_lol_ (funding of $8 million);
@KivaAi (funding of $7 million).
3. Infrastructure (41 projects, total funding over $1 billion, 24 tokens launched, total fully diluted valuation (FDV) over $42 billion)
3.1) Computing resources (Compute)
22 projects, funding of $212 million, 14 tokens launched, total FDV over $1.1 billion.
Representative projects include:
Gensyn (funding of $5 million);
Render ($RENDER, FDV of $4 billion);
@HiveDistributed (funding of $13 million);
@PhalaNetwork ($PHA, FDV of $12.5 million);
Aethir ($ATH, FDV of $2.6 billion);
@fluence_project ($FLT, FDV of $250 million);
@SpheronFDN (funding of $7 million);
@akashnet ($AKT, FDV of $1 billion);
@nosana_ai ($NOS, FDV of $33 million);
@Neura_io ($ANKR, FDV of $34.2 million);
@RunOnFlux ($FLUX, FDV of $25 million), etc.
3.2) AI-specific chains (AI Chains)
10 projects, funding of $357 million, 4 tokens launched, total FDV over $9 billion.
Representative projects include:
@OG_network (funding of $325 million);
Autonomys (funding of $33 million);
io.net ($IO, FDV of $1.8 billion);
@golemproject ($GLM, FDV of $370 million);
Ora ($ORAI, FDV of $12 million).
3.3) Data storage (Data Storage)
8 projects, funding of $374 million, 5 tokens launched, total FDV over $10 billion.
Representative projects include:
GenesysGk (funding of $43 million);
@storj ($STORJ, FDV of $21 million);
Ceramic Network (funding of $30 million);
@Rivalz_AI (funding of $11 million);
@AIOZNetwork ($AIOZ, FDV of $900 million);
@ArweaveEco ($AR, FDV of $1.2 billion).
3.4) Proof of Humanity
This category is represented by WorldCoin, which raised $115 million, with the token $WLD and a total FDV of up to $2.2 billion.
Why am I doing this massive analysis?
My intention is to help VCs and crypto enthusiasts discover potential hot tokens while also hoping to deconstruct the current market craze:
Is funding in this field sufficient?
Are there strong protocols supporting each category?
Besides AI concept coins, is there real market appeal?
From the current situation, the answer is mostly negative:
Funding is still insufficient—$2 billion is negligible for a rapidly developing field.
In AI stack development, it's very difficult to compete with centralized labs.
The market appeal of most projects remains at the speculative stage, with no mature applications in sight.
Currently, funding is mainly concentrated in infrastructure and middleware—but this will change as the ecosystem develops.
I agree with a16z's view: in the coming years, value will gradually shift to the application layer.
In the end, the entire Crypto x AI economy will be cross-chain, supported by @EverclearOrg.
