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Assemble AI (NS3) / ASSEMBLE

Assemble AI (NS3) / ASSEMBLE (ASM) — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

Assemble AI (NS3) / ASSEMBLE (ASM) — an AI/Other | Consumer project (a web/mobile “crypto news super app”), token (symbol: ASM).

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

  • What it is: a “crypto news super app” (NS3) — aggregates news/data and delivers short summaries and “insights”.
  • Who it’s for: retail and professional market participants, crypto companies/media (per the white paper).
  • Why onchain/token: the $ASM token is used for rewards for activity (sharing/quizzes) and payment for “news boosting” (a PR mechanic).
  • What you can actually touch (Tier‑1): the NS3 web and iOS/Android applications (see links_* → App / Demo).

How it works (very briefly)

  1. The user does: reads the feed/searches for news, takes quizzes, shares news via referral links.
  2. The system does: collects data from sources, cleans/structures it, then LLM models form a summary/analysis/sentiment and other blocks (per the white paper).
  3. The user gets: a summary and an “insight” on a news item + (optionally) an $ASM reward for activity.
  4. Where the blockchain is: onchain — the $ASM token (Ethereum ERC‑20 and Base) and transactions related to paying out/using the token.
  5. Token role (if any): rewards for participation + a payment asset for “news boosting” campaigns.

Quick links: AI thesis fit

Project passport

Field Value
Project name Assemble AI (NS3) / ASSEMBLE
Also known as (aliases) NS3; News3; Assemble Protocol; Assemble AI
Logo (logo) ../assets/115_assemble-protocol_logo.png
Token symbol (ticker) ASM
Category AI/Other | Consumer
Primary chain (chain) Base
Type EVM
Network status mainnet
Consensus (consensus) L2 (Optimistic Rollup, Base on Ethereum)
Launch date (launch_date) 2024
Project status (status) active
Token (standard) ERC-20
Token contract Ethereum: 0x2565ae0385659badcada1031db704442e1b69982; Base: 0x3b53604113B5677291BFc0bc255379E7a796559b
Token model (token_type) utility (rewards + boosting)
Max supply total 3,000,000,000 ASM (white paper); ERC‑20 supply 1,500,000,000 ASM (Etherscan)
Issuance fixed (capped)
Tokenomics (tokenomics, brief) Community Reward 500M, AI infra Dev 600M; investor/reserve 150M+150M; team/advisors 100M (vesting per the docs)
Governance company / offchain
Admins/keys —
Audit — (no public audit found)
Bug bounty —
Team (team) Assemble AI (Joshua Park — CEO, per the white paper)
Funding (investors/funding) —
AI component (ai_component) LLM news analysis + summaries
Use‑case (use_case) crypto news insights super app
DecAI Fit — AI thesis fit 4/6 — medium alignment with the Decentralized AI thesis
DecAI Fit component summary 3 / 1 / 1 / 3
Last verified 2026-02-11

General project overview

NS3 (News3) is a “crypto news super app” that aggregates news/market data and, on top of it, generates short summaries and analytical “insights” (summary, sentiment, “market psychology”, historical analogies, etc.) using LLM models.

The white paper states that the product is aimed at retail/pro participants, as well as crypto companies and media that value the speed and clarity of information in a volatile market.

Features/modules

  • Feed/search/personalization of news (web + mobile).
  • AI summaries and AI analysis of a news item (summary + additional “insight” blocks).
  • Multilingual support (12 languages claimed in the white paper).
  • Reward mechanics: $ASM rewards for sharing news and participating in quizzes.
  • News boosting: a PR mechanic where companies pay for a reward pool in $ASM to promote materials (per the tokenomics).

Typical scenarios

  • Scenario 1 (reader): opens a news item → receives a summary/insight → decides whether to read the original source/follow the asset.
  • Scenario 2 (active user): shares a news item via a referral link and/or takes a quiz → receives rewards in $ASM (per the ecosystem rules).
  • Scenario 3 (company): launches a “news boosting” campaign by funding a reward pool in $ASM → users receive rewards for sharing/quizzes.

Getting started (wallet/network)

  • What you need: the web (ns3.ai) or the mobile application (iOS/Android).
  • Network/chain: a wallet is not required for reading/using the AI functions; for operations with $ASM — an EVM wallet (Ethereum/Base).
  • Fees: network fees for onchain operations with $ASM (gas on the selected network).

Architecture/tech (non‑AI)

  • Components: the web/mobile client, an offchain data pipeline (content collection/processing), offchain AI inference; onchain — the $ASM token (Ethereum/Base).
  • Participant roles: users (readers/reward participants), companies (boosting), the project team (platform operator).
  • Where logic runs: the AI logic and delivery of “insights” — offchain; onchain — settlements/accounting around the token and its use.
  • Dependencies: news and market data sources; LLM providers; EVM networks (Ethereum/Base) and their infrastructure (RPC/explorers).

Token/economics (expanded, no forecasts)

  • Token utility: $ASM — rewards for sharing/quizzes and a payment asset for “news boosting”.
  • Protocol necessity drivers: the token is integrated into the reward and boosting mechanics of NS3; without the token these mechanics could be replaced with offchain points/stablecoins, so “irreplaceability” is not proven in Tier‑1.
  • Who pays fees: users/companies for onchain operations with $ASM.
  • Where fees go: — (not described in Tier‑1).
  • Issuance/burn: cap: total 3B (white paper tokenomics); ERC‑20 1.5B already in circulation (the docs note the distribution of the ERC‑20 in 2020–2024).
  • Security/incentive mechanisms: incentives are described via rewards for sharing/quizzes; the roadmap separately mentions anti‑fraud measures (against multi‑accounts/bots).
  • Distribution and token issuance schedule: Community Reward 500M (monthly vesting over 5 years), AI infra Dev 600M (monthly vesting over 5 years), Investor 150M (1y lock + 4y monthly), Reserve 150M (5y monthly), Team/Advisors 100M (1y lock + 4y monthly), ERC‑20 1.5B “already in circulation”.
  • Treasury: the Reserve (150M) is claimed as a fund for listings/marketing/partnerships/reserve; a detailed control model — not found.

Governance

  • Who makes decisions: the team/company (no onchain DAO is described).
  • How protocol parameters change: via application releases and backend/model updates.
  • Where decisions are discussed/made: docs/social media/repositories (no formal governance procedure found).
  • Keys/multisig: —.

Security and incidents

  • Audits: no audit/report was found in the open Tier‑1 sources (Etherscan states that the audit is not submitted).
  • Bug bounty: —.
  • Incidents: — (not found).
  • Threat model: risks of quality/hallucinations of the LLM analytics, risks of manipulation via “investment strategy” blocks, risks of reward farming (bots/multi‑accounts), token risks (listings/vesting/concentration), offchain infrastructure risks.

Project status and timeline

  • Current status: the product is available (web + mobile); the $ASM token exists on Ethereum and Base.
  • Key releases/milestones: per the roadmap: the full version release (web/mobile) is claimed for 2024 Q4; in 2025 — rewards/quiz/news flash, etc.
  • Roadmap: there is a public roadmap (see links_*), including a Point‑to‑$ASM swap and upgrades of the models/search.

Ecosystem/integrations

  • Integrations: web/mobile applications; EVM networks (Ethereum/Base) for the token; external data/news sources (lists of sources are given on the website).
  • Partners: — (not highlighted in Tier‑1).
  • Where it’s actually used: the NS3 web/app for reading and AI insights; reward/boosting mechanics — per the tokenomics.

AI component of the project

  • What is real AI here? LLM model(s) that form summaries and analytical blocks (“insight”) on news/data (described in the white paper: data collection → NLP/TF‑IDF → LLM inference).
  • What is truly onchain? the $ASM token (Ethereum/Base) and the transactions related to it (rewards/boosting).
  • Why is a token needed? rewards for sharing/quizzes and payment for “news boosting” campaigns; at the same time, Tier‑1 does not prove that the system is impossible without its own token.
  • Red flags (based on the information found): possible AI‑washing (many marketing claims without quality metrics), token‑washing (the token is replaceable with stablecoins/points), hallucination/advice risk (including “investment strategy” in the examples), a conflict of claims about the specific LLM model: the website mentions “GPT‑5.2”, while the white paper describes “OpenAI o3‑mini”.

DecAI Fit component summary

  • DecAI Fit: 4/6 — medium alignment with the Decentralized AI thesis
Component Level Score
AI reality high 3
Onchain necessity low 1
Token necessity low/medium 1
Evidence Tier‑1 present 3
Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

  • AI_0 (decision): 0
  • Claim (one line): there is a roadmap with AI upgrades, but AI is already claimed as a working component (see AI_1/AI_2/AI_4), so AI_0 as “intent only” does not apply
  • Evidence: Tier‑1 — https://docs.ns3.ai/roadmap
  • Why sufficient / why not (one line): by the operational definition, AI_0=1 is set only when AI_1..AI_4 = 0
  • Conflict note (if any): —

AI_1 — what the AI does (1/0)

  • AI_1 (decision): 1
  • Claim (one line): LLM agent(s) create summaries/insights on news and data (sentiment, historical cases, ripple effect, etc.)
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/solutions-and-key-features, https://docs.ns3.ai/white-paper/how-it-work
  • Why sufficient / why not (one line): the white paper describes the functions of the AI agent and the stages of insight generation
  • Conflict note (if any): —

AI_2 — demos/examples (1/0)

  • AI_2 (decision): 1
  • Claim (one line): the web and mobile applications are available with public “insight” examples
  • Evidence: Tier‑1 — https://ns3.ai/, https://apps.apple.com/us/app/ns3-crypto-breaking-news/id6572281552, https://play.google.com/store/apps/details?id=com.sta1.front
  • Why sufficient / why not (one line): there are public interfaces and examples of using the product
  • Conflict note (if any): —

AI_3 — metrics/quality (1/0)

  • AI_3 (decision): 0
  • Metrics: —
  • Context (version/date/how measured): —
  • Evidence: Tier‑1 — —
  • Why sufficient / why not (one line): there are no reproducible quality metrics in Tier‑1 (accuracy/errors/latency, etc.)
  • Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

  • AI_4 (decision): 1
  • Claim (one line): the pipeline is described: data collection → NLP/TF‑IDF → source search/polling → LLM inference → continuous learning
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/how-it-work
  • Why sufficient / why not (one line): the white paper provides a technical description of the components and processing stages
  • Conflict note (if any): different Tier‑1 pages contain different claims about the specific LLM model (o3‑mini vs GPT‑5.2 on the marketing page)

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

  • OC_1 (decision): 1
  • Chain: Ethereum mainnet; Base mainnet
  • Addresses/identifiers: Ethereum (ERC‑20) 0x2565ae0385659badcada1031db704442e1b69982; Base 0x3b53604113B5677291BFc0bc255379E7a796559b
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics, https://etherscan.io/token/0x2565ae0385659badcada1031db704442e1b69982, https://basescan.org/token/0x3b53604113B5677291BFc0bc255379E7a796559b
  • Why sufficient / why not (one line): the contract addresses and networks are listed in the official tokenomics section
  • Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

  • OC_2 (decision): 0
  • What useful logic is onchain: Tier‑1 does not describe onchain modules/contracts other than the token itself (rewards/boosting are described as a mechanic, but without a separate onchain architecture)
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics
  • Why sufficient / why not (one line): there are no verifiable artifacts of onchain logic “on top of the token”
  • Conflict note (if any): —

OC_3 — onchain is critical (1/0)

  • OC_3 (decision): 0
  • “Replace the blockchain” test: the application (news aggregation and AI insights) can work without a blockchain; onchain adds a rewards/boosting layer, but its criticality for the core of the product is not proven
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/solutions-and-key-features, https://docs.ns3.ai/white-paper/tokenomics
  • Why sufficient / why not (one line): Tier‑1 does not claim that the product “breaks” without the blockchain
  • Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

  • TK_0 (decision): 0
  • Claim (one line): the project has a token, $ASM
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics, https://etherscan.io/token/0x2565ae0385659badcada1031db704442e1b69982
  • Why sufficient / why not (one line): the token is described in the white paper and exists onchain
  • Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

  • TK_1 (decision): 1
  • Claim (one line): companies pay $ASM for “news boosting” (creating a reward pool for a material)
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics
  • Why sufficient / why not (one line): the tokenomics explicitly describe payments in ASM for the boosting mechanic
  • Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

  • TK_2 (decision): 1
  • Claim (one line): users receive $ASM as rewards for sharing news and participating in quizzes
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics, https://docs.ns3.ai/roadmap
  • Why sufficient / why not (one line): the tokenomics describe the reward mechanic; the roadmap confirms the launch of the rewards systems
  • Conflict note (if any): —

TK_3 — governance (1/0)

  • TK_3 (decision): 0
  • Claim (one line): governance via the token is not described in Tier‑1
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/tokenomics
  • Why sufficient / why not (one line): the tokenomics describe utility/rewards/boosting, but not governance
  • Conflict note (if any): —

TK_4 — token is replaceable (1/0)

  • TK_4 (decision): 1
  • Claim (one line): rewards/boosting can be implemented via offchain points or stablecoins without loss of the application’s basic AI function
  • Evidence: Tier‑1 — https://docs.ns3.ai/white-paper/solutions-and-key-features, https://docs.ns3.ai/white-paper/tokenomics
  • Why sufficient / why not (one line): Tier‑1 does not prove the irreplaceability of the token for the core functions (AI analytics/news)
  • Conflict note (if any): —

Evidence (table)

Tier Source What it proves
Tier‑1 http://about.ns3.ai the NS3 product as an “AI‑powered crypto news super app”, availability of web/iOS/Android, the list of claimed AI features
Tier‑1 https://docs.ns3.ai/white-paper positioning of NS3, target users, basic definitions
Tier‑1 https://docs.ns3.ai/white-paper/solutions-and-key-features the list of AI functions (summary, breaking news, sentiment, etc.) and the claimed principles (neutral, fair articles)
Tier‑1 https://docs.ns3.ai/white-paper/how-it-work a technical description of the pipeline (data collection, NLP/TF‑IDF, LLM inference, continuous learning) and the claimed model integration
Tier‑1 https://docs.ns3.ai/white-paper/tokenomics the utility of the $ASM token, networks/contracts (Ethereum/Base), distribution and vesting
Tier‑1 https://docs.ns3.ai/roadmap the roadmap and confirmation of the reward mechanics/model upgrades/anti‑fraud and the “point‑to‑$ASM swap”
Tier‑1 https://ns3.ai/ the web demo of the product
Tier‑1 https://apps.apple.com/us/app/ns3-crypto-breaking-news/id6572281552 the iOS application (a demo of the existing product)
Tier‑1 https://play.google.com/store/apps/details?id=com.sta1.front the Android application (a demo of the existing product)
Tier‑1 https://etherscan.io/token/0x2565ae0385659badcada1031db704442e1b69982 the onchain $ASM contract on Ethereum and the supply parameters
Tier‑1 https://basescan.org/token/0x3b53604113B5677291BFc0bc255379E7a796559b the onchain $ASM contract on Base
Tier‑2 — —
Tier‑3 — —

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