One of the largest issues with the crypto imo is that the people building the apps and tools do not trade.
One of the largest issues with the crypto imo is that the people building the apps and tools do not trade.
CEO
FOMO
Paul Erlanger
One of the largest issues with the crypto imo is that the people building the apps and tools do not trade.
mobula
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How Fomo protects first-time crypto users at the Data layer
The crypto internet has a noise problem. YouTube searches for "next 100x coin" return walls of influencers paid to promote tokens they've already dumped. Twitter isn't better coordinated shilling, undisclosed promotions, insider manipulation dressed up as alpha.
Paul Erlanger and Se Yong Park built FOMO to fix that.
Both former dYdX colleagues Erlanger as Head of Business Development, Park as Head of Ecosystem at Eclipse they co-founded FOMO Labs Inc.
in New York in late 2024 alongside Prashan Dharmasena. Their thesis: crypto's next ten million users won't come from better trading terminals.
They'll come from a product that makes discovery, onboarding, and execution "as easy as shopping on Amazon" a social feed powered by on-chain data from real traders, not influencers who get paid to lie.
Think Robinhood for on-chain assets, with a social layer closer to Strava than to Bloomberg. Their own analogy: "fomo's vision is to build not just a trading tool but a trusted social network around crypto, similar to how Strava built a community around fitness."
Erlanger frames the competitive positioning directly: "I think the non-custodial experience will win, and that's kind of our advantage to Robinhood." The app launched in May 2025. Apple Pay was added one month later volume went from zero to $3 million per day overnight.
By November: a $17M Series A led by Benchmark, 140 angels including Raj Gokal (Solana co-founder), Marc Boiron (Polygon Labs CEO), and Balaji Srinivasan. At the time of writing: 120,000+ users, $20–40M in daily volume, $150K in daily revenue.
Of those users, 15,000 had never touched crypto before they came in through Apple Pay.
That last number matters for everything that follows.
The problem Fomo meet
FOMO made a specific promise: the feed is more trustworthy than the noise.
A promise about data quality is only as good as the provider behind it. FOMO's previous trending and search infrastructure aggregated token signals from raw volume data.
Volume-based trending is reasonable for a professional terminal where users know that momentum can be manufactured. FOMO's users are not those people. Fifteen thousand of them had never opened a blockchain explorer in their lives.
What raw volume signals surface is exactly what bad actors optimize for: wash trading, coordinated bot activity, manufactured momentum. Tokens designed to look like they're trending so that retail clicks in and gets rugged. One App Store reviewer put it plainly:
constant rug pulls and scams hosted, which is not by any means this app's fault but just adds to the difficulty of being profitable as a beginner. (source)
The scam wasn't in some external app FOMO couldn't control. It was in the feed FOMO had told its users to trust instead.
Why Context Changes Everything
Imagine if Robinhood's Top Movers tab consistently surfaced fraudulent penny stocks to first-time investors. Or if Strava routed runners through dangerous areas with no warning. The app would be actively weaponizing the trust it spent years building.
That's the exact shape of the problem here.
On a professional trading terminal, a scam token in trending is an inconvenience. The user checks the contract, spots 80% concentration in three wallets, and moves on. Data infrastructure surfaces tokens the user evaluates them. That works because the user has the skills.
On FOMO, the contract is different. The entire value proposition is that the app does the filtering.
As they describe it:
"fomo consolidates all the important information about an asset on one page, making your research process trivially easy"** and **"the platform flags when a token is potentially malicious with warnings to protect users". It was built for people who cannot evaluate contracts or read holder distributions. That's the point. Scam prevention is listed as one of FOMO's five core product pillars in their public documentation alongside funding, discovery, fragmentation, and education .
Not a footnote. A founding conviction. The trust that makes FOMO valuable is exactly what makes a compromised feed dangerous. A previous provider that returned raw volume signals without security enrichment wasn't a technical debt problem. It was the product contradicting itself at the infrastructure layer.
Conclusion
Surfacing scam tokens in a trending feed designed for first-time users wasn't a data quality edge case - it was the product contradicting its own founding promise at the infrastructure layer. Every user who opened the trending tab was trusting a guarantee the backend couldn't keep. The fix wasn't a new feature. It was a provider switch. Mobula's native security fields mean filtering happens before data reaches FOMO's interface. The feed is now what it was always supposed to be: signal, not noise. For apps built on trust, the data infrastructure is the product.
How Mobula Solves the Problem at the Infrastructure Level
the structural difference is where filtering happens. fomo's previous setup surfaced tokens and left quality evaluation to the data consumer. mobula embeds security signals directly into every token response, at the data layer, before anything reaches fomo's interface.
every token returned by mobula's search and trending endpoints carries these fields natively
https://docs.mobula.io/guides/query-newly-listed-tokens-onchain
| Field | What it detects |
|---|---|
| bundlersCount / bundlersHoldings | Bulk buys in the opening seconds to manufacture momentum |
| snipersCount / snipersHoldings | First-block bots designed to front-run and dump on retail |
| insidersCount / insidersHoldings | Coordinated pre-launch insider wallet concentration |
| devHoldings | Supply still held by the deployer wallet |
| top10Holdings | Concentration risk across the top 10 holders |
| liquidity | Actual depth of the liquidity pool |
| labels | Native wallet classification: sniper, bundler, insider |
Not a secondary API call. Not an external risk layer bolted on. Present in the base response for every token - in search, in trending, in the real-time stream - on every chain Mobula covers.
Three endpoints power FOMO's discovery stack:
GET /api/1/market/trending trending tokens with the full security payload.
FOMO applies threshold logic on bundlersHoldings, snipersHoldings, devHoldings, and liquidity before anything reaches the user's screen.
GET /api/1/search - Universal Search, cross-chain by name, symbol, or address, with the same security enrichment attached to every result.
wss://pulse-v2-api.mobula.io real-time discovery feed with configurable filter logic per view
1{2"views": [{3"name": "fomo-trending",4"sortBy": "volume_1h",5"filters": {6"bundlersHoldings": { "lte": 15 },7"snipersHoldings": { "lte": 10 },8"devHoldings": { "lte": 20 },9"liquidity": { "gte": 20000 }10}11}]12}
Tokens with more than 15% of supply held by bundlers blocked.
More than 10% held by snipers blocked.
Developer still holding more than 20% blocked.
Less than $20,000 in liquidity blocked.
All of this happens before the token is considered for the trending feed.
Quality thresholds enforced at the infrastructure level not by users who don't know they need to enforce them.
4157A1
How Fomo protects first-time crypto users at the Data layer
The crypto internet has a noise problem. YouTube searches for "next 100x coin" return walls of influencers paid to promote tokens they've already dumped. Twitter isn't better coordinated shilling, undisclosed promotions, insider manipulation dressed up as alpha.
Paul Erlanger and Se Yong Park built FOMO to fix that.
Both former dYdX colleagues Erlanger as Head of Business Development, Park as Head of Ecosystem at Eclipse they co-founded FOMO Labs Inc.
in New York in late 2024 alongside Prashan Dharmasena. Their thesis: crypto's next ten million users won't come from better trading terminals.
They'll come from a product that makes discovery, onboarding, and execution "as easy as shopping on Amazon" a social feed powered by on-chain data from real traders, not influencers who get paid to lie.
Think Robinhood for on-chain assets, with a social layer closer to Strava than to Bloomberg. Their own analogy: "fomo's vision is to build not just a trading tool but a trusted social network around crypto, similar to how Strava built a community around fitness."
Erlanger frames the competitive positioning directly: "I think the non-custodial experience will win, and that's kind of our advantage to Robinhood." The app launched in May 2025. Apple Pay was added one month later volume went from zero to $3 million per day overnight.
By November: a $17M Series A led by Benchmark, 140 angels including Raj Gokal (Solana co-founder), Marc Boiron (Polygon Labs CEO), and Balaji Srinivasan. At the time of writing: 120,000+ users, $20–40M in daily volume, $150K in daily revenue.
Of those users, 15,000 had never touched crypto before they came in through Apple Pay.
That last number matters for everything that follows.
The problem Fomo meet
FOMO made a specific promise: the feed is more trustworthy than the noise.
A promise about data quality is only as good as the provider behind it. FOMO's previous trending and search infrastructure aggregated token signals from raw volume data.
Volume-based trending is reasonable for a professional terminal where users know that momentum can be manufactured. FOMO's users are not those people. Fifteen thousand of them had never opened a blockchain explorer in their lives.
What raw volume signals surface is exactly what bad actors optimize for: wash trading, coordinated bot activity, manufactured momentum. Tokens designed to look like they're trending so that retail clicks in and gets rugged. One App Store reviewer put it plainly:
constant rug pulls and scams hosted, which is not by any means this app's fault but just adds to the difficulty of being profitable as a beginner. (source)
The scam wasn't in some external app FOMO couldn't control. It was in the feed FOMO had told its users to trust instead.
Why Context Changes Everything
Imagine if Robinhood's Top Movers tab consistently surfaced fraudulent penny stocks to first-time investors. Or if Strava routed runners through dangerous areas with no warning. The app would be actively weaponizing the trust it spent years building.
That's the exact shape of the problem here.
On a professional trading terminal, a scam token in trending is an inconvenience. The user checks the contract, spots 80% concentration in three wallets, and moves on. Data infrastructure surfaces tokens the user evaluates them. That works because the user has the skills.
On FOMO, the contract is different. The entire value proposition is that the app does the filtering.
As they describe it:
"fomo consolidates all the important information about an asset on one page, making your research process trivially easy"** and **"the platform flags when a token is potentially malicious with warnings to protect users". It was built for people who cannot evaluate contracts or read holder distributions. That's the point. Scam prevention is listed as one of FOMO's five core product pillars in their public documentation alongside funding, discovery, fragmentation, and education .
Not a footnote. A founding conviction. The trust that makes FOMO valuable is exactly what makes a compromised feed dangerous. A previous provider that returned raw volume signals without security enrichment wasn't a technical debt problem. It was the product contradicting itself at the infrastructure layer.
Conclusion
Surfacing scam tokens in a trending feed designed for first-time users wasn't a data quality edge case - it was the product contradicting its own founding promise at the infrastructure layer. Every user who opened the trending tab was trusting a guarantee the backend couldn't keep. The fix wasn't a new feature. It was a provider switch. Mobula's native security fields mean filtering happens before data reaches FOMO's interface. The feed is now what it was always supposed to be: signal, not noise. For apps built on trust, the data infrastructure is the product.
How Mobula Solves the Problem at the Infrastructure Level
the structural difference is where filtering happens. fomo's previous setup surfaced tokens and left quality evaluation to the data consumer. mobula embeds security signals directly into every token response, at the data layer, before anything reaches fomo's interface.
every token returned by mobula's search and trending endpoints carries these fields natively
https://docs.mobula.io/guides/query-newly-listed-tokens-onchain:
| Field | What it detects |
|---|---|
| bundlersCount / bundlersHoldings | Bulk buys in the opening seconds to manufacture momentum |
| snipersCount / snipersHoldings | First-block bots designed to front-run and dump on retail |
| insidersCount / insidersHoldings | Coordinated pre-launch insider wallet concentration |
| devHoldings | Supply still held by the deployer wallet |
| top10Holdings | Concentration risk across the top 10 holders |
| liquidity | Actual depth of the liquidity pool |
| labels | Native wallet classification: sniper, bundler, insider |
Not a secondary API call. Not an external risk layer bolted on. Present in the base response for every token - in search, in trending, in the real-time stream - on every chain Mobula covers.
Three endpoints power FOMO's discovery stack:
GET /api/1/market/trending trending tokens with the full security payload.
FOMO applies threshold logic on bundlersHoldings, snipersHoldings, devHoldings, and liquidity before anything reaches the user's screen.
GET /api/1/search - Universal Search, cross-chain by name, symbol, or address, with the same security enrichment attached to every result.
wss://pulse-v2-api.mobula.io real-time discovery feed with configurable filter logic per view
1{2"views": [{3"name": "fomo-trending",4"sortBy": "volume_1h",5"filters": {6"bundlersHoldings": { "lte": 15 },7"snipersHoldings": { "lte": 10 },8"devHoldings": { "lte": 20 },9"liquidity": { "gte": 20000 }10}11}]12}
Tokens with more than 15% of supply held by bundlers blocked.
More than 10% held by snipers blocked.
Developer still holding more than 20% blocked.
Less than $20,000 in liquidity blocked.
All of this happens before the token is considered for the trending feed.
Quality thresholds enforced at the infrastructure level not by users who don't know they need to enforce them.
The crypto internet has a noise problem. YouTube searches for "next 100x coin" return walls of influencers paid to promote tokens they've already dumped. Twitter isn't better coordinated shilling, undisclosed promotions, insider manipulation dressed up as alpha.
Paul Erlanger and Se Yong Park built FOMO to fix that.
Both former dYdX colleagues Erlanger as Head of Business Development, Park as Head of Ecosystem at Eclipse they co-founded FOMO Labs Inc.
in New York in late 2024 alongside Prashan Dharmasena. Their thesis: crypto's next ten million users won't come from better trading terminals.
They'll come from a product that makes discovery, onboarding, and execution "as easy as shopping on Amazon" a social feed powered by on-chain data from real traders, not influencers who get paid to lie.
Think Robinhood for on-chain assets, with a social layer closer to Strava than to Bloomberg. Their own analogy: "fomo's vision is to build not just a trading tool but a trusted social network around crypto, similar to how Strava built a community around fitness."
Erlanger frames the competitive positioning directly: "I think the non-custodial experience will win, and that's kind of our advantage to Robinhood." The app launched in May 2025. Apple Pay was added one month later volume went from zero to $3 million per day overnight.
By November: a $17M Series A led by Benchmark, 140 angels including Raj Gokal (Solana co-founder), Marc Boiron (Polygon Labs CEO), and Balaji Srinivasan. At the time of writing: 120,000+ users, $20–40M in daily volume, $150K in daily revenue.
Of those users, 15,000 had never touched crypto before they came in through Apple Pay.
That last number matters for everything that follows.
How Mobula Solves the Problem at the Infrastructure Level
the structural difference is where filtering happens. fomo's previous setup surfaced tokens and left quality evaluation to the data consumer. mobula embeds security signals directly into every token response, at the data layer, before anything reaches fomo's interface.
every token returned by mobula's search and trending endpoints carries these fields natively
https://docs.mobula.io/guides/query-newly-listed-tokens-onchain:
| Field | What it detects |
|---|---|
| bundlersCount / bundlersHoldings | Bulk buys in the opening seconds to manufacture momentum |
| snipersCount / snipersHoldings | First-block bots designed to front-run and dump on retail |
| insidersCount / insidersHoldings | Coordinated pre-launch insider wallet concentration |
| devHoldings | Supply still held by the deployer wallet |
| top10Holdings | Concentration risk across the top 10 holders |
| liquidity | Actual depth of the liquidity pool |
| labels | Native wallet classification: sniper, bundler, insider |
Why Context Changes Everything
Imagine if Robinhood's Top Movers tab consistently surfaced fraudulent penny stocks to first-time investors. Or if Strava routed runners through dangerous areas with no warning. The app would be actively weaponizing the trust it spent years building.
That's the exact shape of the problem here.
On a professional trading terminal, a scam token in trending is an inconvenience. The user checks the contract, spots 80% concentration in three wallets, and moves on. Data infrastructure surfaces tokens the user evaluates them. That works because the user has the skills.
On FOMO, the contract is different. The entire value proposition is that the app does the filtering.
As they describe it:
"fomo consolidates all the important information about an asset on one page, making your research process trivially easy"** and **"the platform flags when a token is potentially malicious with warnings to protect users". It was built for people who cannot evaluate contracts or read holder distributions. That's the point. Scam prevention is listed as one of FOMO's five core product pillars in their public documentation alongside funding, discovery, fragmentation, and education .
Not a footnote. A founding conviction. The trust that makes FOMO valuable is exactly what makes a compromised feed dangerous. A previous provider that returned raw volume signals without security enrichment wasn't a technical debt problem. It was the product contradicting itself at the infrastructure layer.
The Problem Fomo meet
FOMO made a specific promise: the feed is more trustworthy than the noise.
A promise about data quality is only as good as the provider behind it. FOMO's previous trending and search infrastructure aggregated token signals from raw volume data.
Volume-based trending is reasonable for a professional terminal where users know that momentum can be manufactured. FOMO's users are not those people. Fifteen thousand of them had never opened a blockchain explorer in their lives.
What raw volume signals surface is exactly what bad actors optimize for: wash trading, coordinated bot activity, manufactured momentum. Tokens designed to look like they're trending so that retail clicks in and gets rugged. One App Store reviewer put it plainly:
constant rug pulls and scams hosted, which is not by any means this app's fault but just adds to the difficulty of being profitable as a beginner. (source)
The scam wasn't in some external app FOMO couldn't control. It was in the feed FOMO had told its users to trust instead.
Not a secondary API call. Not an external risk layer bolted on. Present in the base response for every token - in search, in trending, in the real-time stream - on every chain Mobula covers.
Three endpoints power FOMO's discovery stack:
GET /api/1/market/trending trending tokens with the full security payload.
FOMO applies threshold logic on bundlersHoldings, snipersHoldings, devHoldings, and liquidity before anything reaches the user's screen.
GET /api/1/search - Universal Search, cross-chain by name, symbol, or address, with the same security enrichment attached to every result.
wss://pulse-v2-api.mobula.io real-time discovery feed with configurable filter logic per view
1{2"views": [{3"name": "fomo-trending",4"sortBy": "volume_1h",5"filters": {6"bundlersHoldings": { "lte": 15 },7"snipersHoldings": { "lte": 10 },8"devHoldings": { "lte": 20 },9"liquidity": { "gte": 20000 }10}11}]12}
Tokens with more than 15% of supply held by bundlers blocked.
More than 10% held by snipers blocked.
Developer still holding more than 20% blocked.
Less than $20,000 in liquidity blocked.
All of this happens before the token is considered for the trending feed.
Quality thresholds enforced at the infrastructure level not by users who don't know they need to enforce them.
Conclusion
Surfacing scam tokens in a trending feed designed for first-time users wasn't a data quality edge case - it was the product contradicting its own founding promise at the infrastructure layer. Every user who opened the trending tab was trusting a guarantee the backend couldn't keep. The fix wasn't a new feature. It was a provider switch. Mobula's native security fields mean filtering happens before data reaches FOMO's interface. The feed is now what it was always supposed to be: signal, not noise. For apps built on trust, the data infrastructure is the product.
How Fomo Protects First-Time Crypto Users at the Data Layer