A picture that gives you a quick overview of 178 crypto AI projects

Author: Dima Khanarin

Compiled by: Deep Tide TechFlow

The combination of Crypto and AI 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 the projects into the following three categories:

• Applications (Apps)

• Middleware

• Infrastructure (Infra)

Each category includes funding data and information on launched tokens.

1. Applications (31 projects, total funding over $240 million, 8 tokens launched, total FDV over $3 billion):

1.1) DeFi Applications

• 6 projects, funding $1 million, currently no tokens launched.

• Includes @rugai, @RPSLabs, 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 $33 million, currently no tokens launched.

• Representative projects include:

@PaymanAI (funding $13.8 million);

@trySkyfire (funding $9.5 million);

@BitteProtocol (funding $7.5 million), etc.

1.4) AI Agents and Influencers

• Over 10 projects, 10+ tokens launched, total FDV over $3 billion.

• Includes TT, ai16z, Zerebro, @centienceio, etc.

1.5) Engineering and Security

• 4 projects, funding $33 million, 2 tokens launched, total FDV over $20 million.

• For example:

@Chain_GPT ($CGPT, FDV $120 million);

@FortaNetwork ($FORT, FDV $100 million);

@MetaTrustLabs (funding $10 million), etc.

1.6) Consumer Applications

• 6 projects, funding $12 million, 2 tokens launched, total FDV over $10 million.

• Includes:

@aiarena_ ($NRN, FDV $80 million);

@bottoproject ($BOTTO, FDV $60 million), etc.

1.7) Smart Tools

• 4 projects, funding $163 million, 2 tokens launched, total FDV over $2 billion.

• For example, Arkham Intel ($ARKM, FDV $2 billion), Kaito, Dune, and Messari.

2. Middleware (106 projects, total funding over $800 million, 25 tokens launched, total FDV over $18 billion):

2.1) Training and Collaboration

• 16 projects, funding $120 million, 4 tokens launched, total FDV over $10 billion.

• Includes well-known Bittensor and Sentient, as well as @assisterr, @Pluralis__, etc.

• Tradeable tokens include:

@Dither_Solana ($DITH, FDV $10 million);

@hyper_tensor ($TENSOR, FDV $25 million);

@communeaidotorg ($COMAI, FDV $200 million).

2.2) Inference Services

• 17 projects, funding $57 million, 2 tokens launched, total FDV over $5 million.

• For example:

Allora Network (funding $35 million);

@OpenGradient (funding $8.5 million);

@hyperbolic_labs (funding $7 million);

and smaller teams like @openex_network ($OEX, FDV $45 million).

2.3) Data Platforms and Monetization

• 23 projects, funding $240 million, 7 tokens launched, total FDV over $1 billion.

• Home to many well-funded protocols:

Story Protocol (raised $134.3 million);

Space and Time (raised $50 million);

@SaharaLabsAI (raised $43 million);

Ocean Protocol ($OCEAN, $500 million FDV);

Vana (raised $25 million);

Hivemapper ($HONEY, $500 million FDV).

2.4) Privacy Protection

• 14 projects, funding $250 million, 2 tokens launched, total FDV over $800 million.

• For example:

Zama (funding $82.3 million);

Oasis Protocol ($ROSE, FDV $800 million), etc.

2.5) Agent Platforms

• 24 projects, funding $175 million, 6 tokens launched, total FDV over $6.5 billion.

• Includes:

Fetch AI ($FET, FDV $3.5 billion);

@Spectral_Labs ($SPEC, FDV $1 billion);

@virtuals_io ($VIRTUAL, FDV $450 million);

@autonolas ($OLAS, FDV $850 million);

@MorpheusAIs ($MOR, FDV $800 million).

2.6) Research

• 3 projects, funding $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 Annotation

• 9 projects, funding $30 million, 1 token launched, total FDV over $12 million.

• Representative projects include:

@getmasafi ($MASA, FDV $126 million);

@dinlol (funding $8 million);

@KivaAi (funding $7 million).

3. Infrastructure (41 projects, total funding over $1 billion, 24 tokens launched, total fully diluted valuation (FDV) over $42 billion)

3.1) Compute Resources

• 22 projects, funding $212 million, 14 tokens launched, total FDV over $11 billion.

• Representative projects include:

Gensyn (funding $50 million);

Render ($RENDER, FDV $4 billion);

@HiveDistributed (funding $13 million);

@PhalaNetwork ($PHA, FDV $125 million);

Aethir ($ATH, FDV $2.6 billion);

@fluence_project ($FLT, FDV $250 million);

@SpheronFDN ($7 million);

@akashnet ($AKT, FDV $1 billion);

@nosana_ai ($NOS, FDV $33 million);

@Neura_io ($ANKR, FDV $34.2 million);

@RunOnFlux ($FLUX, FDV $25 million), etc.

3.2) AI Chains

• 10 projects, funding $357 million, 4 tokens launched, total FDV over $9 billion.

• Representative projects include:

@OG_network (funding $325 million);

Autonomys (funding $33 million);

io.net ($IO, FDV $1.8 billion);

@golemproject ($GLM, FDV $370 million);

Ora ($ORAI, FDV $120 million).

3.3) Data Storage

• 8 projects, funding $374 million, 5 tokens launched, total FDV over $1 billion.

• Representative projects include:

GenesysGk (funding $43 million);

@storj ($STORJ, FDV $210 million);

Ceramic Network (funding $30 million);

@Rivalz_AI ($11 million);

@AIOZNetwork ($AIOZ, FDV $900 million);

@ArweaveEco ($AR, FDV $1.2 billion).

3.4) Proof of Humanity

• This category is represented by WorldCoin, funding $115 million, token $WLD, total FDV up to $2.2 billion.

Why did I undertake this massive analysis?

My intention is to help venture capitalists (VCs) and crypto enthusiasts discover potential hot tokens while also hoping to deconstruct the current market frenzy:

• Is there sufficient funding in this field?

• Are there strong protocols supporting each category?

• Besides AI concept coins, is there real market appeal?

From the current situation, the answers are mostly negative:

• Funding is still insufficient—$2 billion is trivial for a rapidly developing field.

• Competing with centralized labs in AI stack development is very challenging.

• The market appeal of most projects remains at the speculative stage, with no mature applications yet.

Currently, funding is primarily 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 towards the application layer.

Finally, the entire Crypto x AI economy will be cross-chain and supported by @EverclearOrg.