Fetch.ai / ASI Alliance

What it does

The Artificial Superintelligence Alliance is what happens when three separate crypto-AI projects decide they are stronger together, then one of them leaves in a lawsuit.

Fetch.ai, SingularityNET and Ocean Protocol announced their merger in March 2024 under the ASI Alliance banner, unifying under the FET tokenTokenA digital unit of value or access rights tracked on a blockchain. Tokens can represent ownership in a project, a right to use a service, a share of future revenue, or simply a tradable asset with no underlying claim.Like a physical poker chip a casino issues. The chip itself has no value. What makes it worth something is what it lets you do at the casino, what the casino has promised, and how much other people will pay you for it.Read more →. CUDOS joined in October 2024, contributing 30 validators and compute infrastructure. Ocean Protocol withdrew in October 2025, alleging governance failures, rushed token migration steps and strategic misalignment. Fetch.ai responded with a lawsuit in November 2025 claiming Ocean’s foundation had converted 661 million OCEAN tokens into 286 million FET and sold roughly 263 million FET (over 10% of circulating supplyCirculating SupplyThe number of tokens currently in circulation and tradeable on the open market. Differs from total supply (which includes locked or unvested tokens) and max supply (the upper limit, if there is one).Like the number of cars on the road today versus the number ever produced. Some are in showrooms, some in junkyards, some still at the factory. Only the ones on the road count toward what people are actually driving.Read more →) on the open market without disclosure. The dispute was settled in late 2025, with Ocean agreeing to return 286 million FET (then worth approximately $120 million) and Fetch.ai dropping all legal claims. GeoStaking, a validatorValidatorA computer that runs the full blockchain protocol, verifies transactions, and proposes new blocks. Validators are the workers that keep a Proof of Stake network running, and they earn rewards for doing the work correctly.Like a notary public who witnesses and stamps legal documents. Validators witness transactions, check they follow the rules, and stamp them into the permanent record. A notary who commits fraud loses their license. Validators work the same way, except the license is staked tokens that get slashed on misbehaviour.Read more → node connected to Fetch.ai, mediated the talks. Fetch.ai CEO Humayun Sheikh agreed to cover all legal costs once the tokens were recovered.

What remains is a federated alliance of three entities: Fetch.ai (autonomous AI agents), SingularityNET (AI services marketplace), and CUDOS (cloud compute). The core technology is Fetch.ai’s Cosmos SDKSDKSoftware Development Kit. A collection of code libraries, documentation, and tools that lets developers integrate a service into their applications without writing everything from scratch. SDKs are how projects become easy to build with.Like a plug-and-play kit for building furniture. You don't have to mill your own wood, forge your own screws, or design the joinery from scratch. The kit gives you pre-cut parts and instructions so you can assemble the thing in an afternoon.Read more → blockchain (Fetchhub-4) running up to 70 validators with CometBFT consensus. The uAgents Python framework lets developers build autonomous agents that register on-chain via the Almanac contract. Agentverse provides a no-code browser-based deployment platform. SingularityNET offers a marketplace for publishing and consuming AI services across Ethereum and Cardano. The alliance is also building ASI Chain, a new blockDAG Layer 1 using MeTTa (a cognitive programming language from the OpenCog Hyperon AGI framework) compiled into Rholang. ASI Chain entered DevNet in November 2025.

The leadership: Humayun Sheikh (Fetch.ai founder, DeepMind founding investor) is Chairman of the Governing Council. Ben Goertzel (SingularityNET founder, credited with coining the term “Artificial General Intelligence,” over 150 research publications) is CEO. Together they drive strategy for an alliance that claims “300-plus experts” but publishes no verifiable headcount.

The entity structure is complex. Fetch.ai Foundation (co-founded with Bosch), SingularityNET Foundation (Netherlands), and CUDOS (UK) each remain independent legal entities within the alliance. Total disclosed funding: $61.9 million, including a $40 million Series C led by DWF Labs in March 2023 at a $250 million valuation. The original FET launched via Binance Launchpad IEO in February 2019 ($6 million raised in 10 seconds).

Value proposition

Three layers, each at a different stage of maturity.

Start with the agent framework, which is the most tangible. uAgents (1,551 GitHub stars, Apache 2.0) is a functional Python framework for building autonomous AI agents. Agents register on-chain, discover each other through the Almanac contract, and transact in FET. Agentverse removes the coding barrier with one-click deployment templates. This is the “AI agents on blockchain” thesis in its most accessible form, and Fetch.ai has a first-mover advantage (uAgents launched in 2022).

The AI services marketplace is older but less proven. SingularityNET has been offering a marketplace for AI services since 2017. Developers can publish and consume AI models. The OpenCog Hyperon AGI framework is Goertzel’s long-running open-source AGI research project. Genuinely ambitious. Usage volumes are not publicly disclosed, which is a problem for a marketplace that has been live for years.

Compute and inferenceInferenceRunning a trained AI model to produce an answer. Inference is what happens when you type a prompt into ChatGPT and get a response. The model takes your input, computes a best guess, and returns it.Like asking an expert for their opinion. The training was the decades they spent becoming an expert. The inference is the 30 seconds it takes them to answer your specific question.Read more → is the newest layer. ASI Cloud exited beta in December 2025, claiming prices roughly 50% cheaper than AWS. ASI-1 Mini is positioned as the “first Web3-native LLMLLMLarge Language Model. A neural network trained on vast amounts of text to predict the next word in a sequence. Modern LLMs (GPT, Claude, Llama, Qwen, DeepSeek) generate human-quality text and are the foundation of most modern AI products.Like an autocomplete that read every book ever written. It has no memory of individual texts but it has absorbed the patterns of language so deeply that it can generate paragraphs that sound human. The skill is statistical, not conscious.Read more →,” a modelModelA trained neural network that takes inputs (text, images, audio) and produces outputs (more text, classifications, generated content). In DeAI the model is the thing that actually does the work.Like a very experienced apprentice who has spent years watching thousands of masters make furniture. They can't explain how they know when a joint is right, but they can make a chair that looks and functions like a Chippendale. The training is invisible. The output is what matters.Read more → with four reasoning modes powered by FET payments. Neither product publishes usage metrics.

The counter-narrative is simple. Strip away the “Artificial Superintelligence” branding and you have a collection of AI-adjacent tools at different stages of development, operated by a federated alliance that has already lost one member in a lawsuit. The products that generate actual revenue (ASI Cloud, ASI-1 Mini) are centrally operated by Fetch.ai Inc. The decentralisation is at the base layerL1Layer 1. A base blockchain that runs its own consensus mechanism, executes transactions, and settles its own state. Bitcoin, Ethereum, NEAR, and Solana are all L1s. Anything built on top of an L1 is technically a Layer 2 or higher.Like the foundation of a building. Nothing else can exist on top until the foundation is solid. Different L1s make different tradeoffs for what kind of building they can support.Read more → (Cosmos chain, stakingStakingLocking up a cryptocurrency to help secure a blockchain network, usually in exchange for rewards. The locked tokens act as a security deposit that can be taken away if the staker misbehaves.Like putting down a large rental deposit for an apartment. You get the money back if you behave, you earn interest while it's locked, and the landlord takes it if you trash the place.Read more →, governance). The application layer is a company running servers.

For the sovereignty thesis: the open-source agent framework and the permissionless base layer have substantive merit. But the core AI products are centralised services. You are trusting Fetch.ai Inc. with your inference workloads, not running them on decentralised infrastructure.

Tokenomics

FET is one of the most complex tokens in the space because it absorbed three other token communities.

The merger converted existing holders at fixed ratios: 1 AGIX = 0.433350 FET, 1 OCEAN = 0.433226 FET, 1 CUDOS at 118.344:1 (with a 5% fee and 3-10 month vestingVestingA schedule that locks up tokens allocated to insiders, investors, and team members, releasing them gradually over months or years. Vesting prevents insiders from dumping on public buyers immediately after launch.Like a new employee's stock options at a startup. You don't get all the shares on day one. They unlock over four years so you stick around and do the work rather than cashing out and leaving.Read more →). Total supply post-merger: 2.71 billion FET. Circulating supply: 2.26 billion (83.3%). The full unlock schedule extends to 2050.

Distribution of the merged supply:

• AGIX migration (SingularityNET holders): 32.95%
• OCEAN migration (Ocean Protocol holders): 23.22%
• Founders: 8.77% (cliffCliffA waiting period at the start of a token vesting schedule during which no tokens unlock at all. After the cliff ends, tokens begin releasing according to the vesting schedule.Like a probationary period at a new job. You don't get your stock options on day one. You wait 12 months to prove you'll stick around, then everything starts unlocking normally.Read more → vesting to 2050)
• Foundation: 8.77% (Fetch.ai Foundation, co-founded with Bosch)
• Future releases: 7.63% (reserved, schedule to 2050)
• MiningProof of WorkThe original blockchain consensus mechanism where miners compete to solve computationally expensive puzzles. The winner proposes the next block and earns the rewards. Proof of Work secures Bitcoin and most pre-2020 chains.Like a lottery that runs every 10 minutes where the tickets cost electricity. Whoever spends the most electricity buying lottery tickets has the best chance of winning that round's prize. Nobody can fake the result because the proof of their work is verifiable by everyone.Read more →/staking rewards: 6.57%
• Private sale: 5.08% (fully unlocked)
• Advisors: 4.38% (cliff vesting)
• Public sale (Binance Launchpad IEO): 2.49%

The AGIX and OCEAN migration allocations (56.17% combined) are not new insider supply; they represent conversion of existing communities. But the roughly 600 million FET minted to absorb OCEAN holders did dilute existing FET holders. Ocean Protocol sold approximately 263 million of those FET on the open market, leading to a lawsuit that was settled in late 2025 with Ocean returning 286 million FET to the Fetch community.

The Earn and Burn mechanism launched in January 2026 with a first burn of 5 million FET. Ecosystem fees from ASI Cloud, ASI-1 Mini and other products buy and burnBurnPermanently removing tokens from circulation by sending them to an address that no one controls. Burns reduce total supply, which (all else equal) makes each remaining token worth more of the network's value.Like a company buying back its own shares and shredding them. The company's total value stays the same, but each remaining share now represents a slightly bigger slice of that value.Read more → FET. Five million FET is 0.18% of supply. Symbolic, not structural. The Fetch.ai Foundation also claims to have executed a $50 million FET buybackBuybackUsing protocol revenue to purchase tokens on the open market, usually to burn them or return them to a treasury. Buybacks convert business income into upward pressure on the token by reducing circulating supply.Like a public company using profits to repurchase and retire its own shares. The cash leaves the company's balance sheet, the share count drops, and every remaining shareholder owns a slightly bigger slice of the same business.Read more → in June 2025, which, if accurate, would be a more meaningful signal — though no independent on-chain verification of this figure has been published.

Staking yields 5.5-8% APY with a standard Cosmos 21-day unbonding period. Estimated 480-560 million FET staked (21-25% of circulating supply). Standard Cosmos slashing: 5% for double-signing, 0.01% for downtime.

FET is down 96% from the all-time high of $3.45 from March 2024. Listed on Binance, Coinbase, Kraken, OKX, Bybit and others. See live data above for current pricing.

How to participate

Stake FET. Delegate to validators on Fetchhub-4. Earn 5.5-8% APY. Use the ASI Alliance WalletWalletSoftware that stores the private keys needed to control tokens on a blockchain. A wallet does not actually hold any tokens. The tokens live on the chain. The wallet holds the keys that prove you own them.Like the key to a safe deposit box. The key doesn't contain your valuables. The valuables sit in the bank's vault. The key is what proves you're allowed to open the box and take them.Read more → (browser extension) or any Cosmos-compatible wallet (Keplr, Cosmostation). No minimum stake; keep at least 1 FET undelegated for transaction fees. Twenty-one-day unbonding period. Choose validators carefully; top validators (Kiln at 143 million FET, Binance Staking at 60 million FET) hold disproportionate stake.

Build agents. The most interesting participation mode. Write autonomous AI agents in Python using the uAgents framework. Deploy on Agentverse (no-code, browser-based) or self-host. Register agents on the Almanac contract (requires FET, renewed every 48 hours). Access ASI-1 Mini LLM for agent intelligence. Requires Python skills and understanding of the agent architecture.

Use products. ASI Cloud for GPUGPUGraphics Processing Unit. Originally designed to render video game graphics, GPUs turned out to be exceptionally good at the massively parallel math that AI models need. Modern AI training and inference runs almost entirely on GPUs.Like a factory with 10,000 workers doing the same simple task in parallel, versus a CPU which is more like 10 workers each doing different complex tasks. AI training involves doing simple math a million times per second on a million numbers, which is exactly what the GPU factory is designed for.Read more → inference (reportedly 50% cheaper than AWS, but unverified). ASI-1 Mini for LLM access via APIAPIApplication Programming Interface. A structured way for one piece of software to talk to another. In DeAI, APIs let applications request inference from a model without running the model themselves.Like a waiter in a restaurant. You don't walk into the kitchen and cook your own meal. You tell the waiter what you want, they tell the kitchen, the kitchen cooks it, and the waiter brings it back. The API is the waiter.Read more →. Browse and consume AI services on the SingularityNET marketplace. Pay in FET.

Validate. Run a validator node on Fetchhub-4. Maximum 70 slots. Requires substantial FET stake (competitive; top validators hold 30 million-plus FET), server infrastructure and DevOps expertise. High barrier to entry.

Governance. Vote on alliance proposals using staked FET. Proposals have included the CUDOS merger approval and tokenomics changes. A proposed Paal.ai merger (900 million PAAL tokens converting to FET at 6.24:1 with 180-day vesting) was withdrawn in November 2024 after community backlash over the conversion ratio, causing PAAL to drop 70%.

Contribute. Open-source repos across three GitHub organisations (fetchai, singnet, oceanprotocol). Innovation Lab partnership with Imperial College London backed by a $10 million fund. Hackathon participation. Apache 2.0 licensing on core repos.

Honest assessment

What works

Start with the uAgents framework, which is the most mature open-source agent framework in the DeAI space. Functional, well-documented, Apache 2.0, actively maintained (last commit March 2026). Fetchhub-4 runs reliably as a Cosmos SDK chain with IBC interoperability, and 371 public repositories across three GitHub organisations is a substantial open-source footprint.

Team credibility is real. Goertzel is a credible AGI research figure with 150-plus publications. Sheikh is a DeepMind founding investor. The Innovation Lab with Imperial College London, backed by a $10 million fund, is a serious academic partnership, not a PR announcement. The Earn and Burn mechanism is nascent, but it establishes a deflationary counter before the product revenue justifies it. ASI-1 Mini, whatever you think of the “first Web3-native LLM” framing, is a concrete product at the intersection of AI and crypto.

What does not work

The merger has been a governance catastrophe. Ocean Protocol’s exit, the sale of 263 million FET on the open market, and the resulting lawsuit (since settled, with 286 million FET returned) are not growing pains. They are structural failures in alliance governance. The “Artificial Superintelligence” branding is aspirational to the point of misleading. The constituent projects are building AI agents, marketplaces and compute infrastructure. Valuable, yes. A path to superintelligence? No.

Usage metrics are notably opaque. No public dashboard for transaction counts, active users or revenue. ASI Cloud exited beta in December 2025 but publishes no adoption data. SingularityNET’s marketplace has been live since 2017 and still doesn’t disclose usage volumes. For a project of this market cap, this lack of transparency is not a gap. It’s a choice.

ASI Chain (blockDAG with MeTTa/Rholang) is in DevNet with no mainnet timeline. The complexity of running three separate technical platforms (Cosmos chain, Ethereum/Cardano marketplace, DevNet blockDAG) under one token creates integration challenges and a confusing user experience.

The risk

Alliance fragmentation is the defining risk. Ocean Protocol already left. If SingularityNET departed, the alliance narrative collapses entirely. Ocean’s lawsuit has been settled (286 million FET returned), removing the immediate legal overhang, but the episode exposed governance vulnerabilities that remain unaddressed.

Down 96% from the all-time high. The merger was announced at a combined “valuation” of $7.5 billion. That gap between hype valuation and current reality represents real losses for holders who bought the merger narrative.

Key person dependency is acute. Sheikh and Goertzel are essential to the alliance. Goertzel’s broad research interests (AGI, robotics, philosophy, OpenCog Hyperon) raise focus risk, and the federated structure means each foundation retains independent governance, creating potential for further misalignment.

Core revenue-generating products (ASI Cloud, ASI-1 Mini, Agentverse) are centrally operated by Fetch.ai Inc. This contradicts the decentralisation narrative. A 70-validator cap on Fetchhub-4, with top validators holding 143 million FET, creates concentration at the infrastructure level too.

My position

I don’t hold FET. The governance failures demonstrated by the Ocean Protocol exit, the opaque usage metrics, and the 96% price decline from the merger-hype peak make this a wait-and-see proposition. The uAgents framework is worth exploring as a developer tool. But “wait-and-see” here means: show me a public revenue dashboard, show me governance that doesn’t end in lawsuits, then we’ll talk.

Freedom Score: 50/100

The ASI Alliance scores 50/100 (D grade). Full methodology at Freedom Score Methodology.

Infrastructure decentralisation (9/20): Fetchhub-4 runs on Cosmos SDK with CometBFT consensus, capped at 70 validator slots. Permissionless in theory, but the small validator set and high capital requirements create concentration. Top validators (Kiln: 143M FET, Binance Staking: 60M FET) hold disproportionate influence. The 30 CUDOS validators added some diversity. Core value-adding products (Agentverse, ASI Cloud, ASI-1 Mini) are centrally hosted by Fetch.ai Inc. SingularityNET marketplace relies on centralised infrastructure for service discovery. ASI Chain is still in DevNet.

Governance decentralisation (8/20): On-chain governanceDAODecentralised Autonomous Organisation. A way to coordinate decisions and manage a treasury using token-weighted voting instead of a traditional company structure. Token holders propose and vote on changes directly.Like a shareholder-run company where every shareholder can vote on every decision, the votes are public, and the company can't do anything the shareholders don't approve. The coordination is messier than a normal company but nobody has unilateral control.Read more → via FET token voting exists for major decisions (merger approvals, new members). The CUDOS merger went through a community vote; the Paal.ai proposal was withdrawn before voting after community backlash. However, the Governing Council (Sheikh as Chairman, Goertzel as CEO) holds outsized influence. Ocean Protocol’s exit exposed governance failures: Ocean alleged the governance “didn’t match the original decentralised vision” and cited rushed decision-making. Each foundation retains independent governance, enabling strategic decisions without full community consent. The lawsuit (since settled) demonstrated governance dysfunction.

Token distribution fairness (7/15): Original FET launched via Binance Launchpad IEO ($6M raised, February 2019). Original insider allocations (founders 8.77%, foundation 8.77%, advisors 4.38%, private sale 5.08%) total roughly 27%. The AGIX and OCEAN migration allocations (56.17% combined) represent community conversion, not new insider supply. However, the Ocean Protocol controversy revealed that Ocean Foundation converted 661M OCEAN into 286M FET and sold 263M FET without disclosure, a dispute settled in late 2025 with the 286M FET returned. CUDOS merger included a 5% fee. The claimed $50M buyback was presented as a positive signal, though no on-chain verification has been independently confirmed.

Censorship resistance (8/15): The Cosmos SDK base layer is permissionless. IBC enables cross-chain interoperability. ERC-20 token on Ethereum provides additional resistance via Ethereum’s validator set. However, the application layer has significant vectors: Agentverse is centrally hosted (Fetch.ai can deplatform agents), ASI Cloud and ASI-1 Mini are centrally operated, and the SingularityNET marketplace has curation capabilities. Agent registration requires renewal every 48 hours via the Almanac contract, creating dependency.

Data sovereignty (8/15): Ocean Protocol’s compute-to-data paradigm was the alliance’s strongest data sovereignty feature, enabling computation on data without the data leaving the provider’s infrastructure. Ocean Protocol withdrew in October 2025, removing this capability. The uAgents framework gives developers control over agent logic and data. However, ASI Cloud and ASI-1 Mini are centrally hosted; user queries pass through Fetch.ai’s infrastructure. No ZKZKZero Knowledge. A class of cryptographic proofs that let you prove something is true without revealing any of the underlying information. ZK lets a network verify a transaction without seeing the transaction's contents.Like proving you know the password to a safe by demonstrating you can open it, without ever saying the password out loud. The verifier learns that you know the password and nothing more.Read more → proofs or advanced privacy-preserving features in the core stack.

Open source and transparency (10/15): Strong open-source foundation: 371 public repos across three GitHub organisations (fetchai: 91, singnet: 186, oceanprotocol: 94). Core infrastructure (uAgents, fetchd, cosmpy, SingularityNET daemon) is Apache 2.0. Active development continues. However, ASI-1 Mini model weightsParametersThe internal numbers (weights and biases) inside a neural network that get adjusted during training. A 70-billion-parameter model has 70 billion adjustable internal numbers encoding everything it has learned.Like the synapses in a human brain. Each parameter is a tiny dial that gets nudged a little during training. With enough dials, the network can represent surprisingly complex patterns. The total parameter count is roughly how much "brain" the model has.Read more → are not confirmed open source, ASI Cloud infrastructure is not open, and ASI Chain implementation details are limited. The Ocean exit revealed a lack of transparency in token operations. Usage metrics are not publicly reported.

Path to improvement

Three changes would materially increase the ASI Alliance’s score:

1. Publish transparent usage metrics. No public dashboard for ASI Cloud adoption, SingularityNET marketplace volumes, agent deployments or revenue. This is indefensible for a project at this scale. A real-time metrics dashboard would be the single biggest credibility signal. Akash publishes quarterly Messari reports and tracks on-chain revenue. The ASI Alliance publishes nothing.
2. Publish a post-mortem and reform governance. The Ocean lawsuit is settled and the 286 million FET returned, but the alliance hasn’t published a post-mortem or implemented governance reforms. Clear exit procedures, transparent treasury operations and community veto mechanisms would address the structural failures the episode exposed.
3. Open-source ASI-1 Mini and ASI Cloud. The core AI products are centrally operated and not open source. Open-sourcing ASI-1 Mini model weights and the ASI Cloud orchestration layer would align the products with the open-source credentials of the underlying infrastructure. The “decentralised AIDeAIDecentralised AI. An umbrella term for blockchain-based projects that build AI infrastructure (compute, data, inference, models, agents) without a single central provider controlling the system.Like the difference between streaming a movie from Netflix and sharing it via BitTorrent. Netflix is fast and polished but one company controls what you can watch and what you pay. BitTorrent is messier but no single operator can shut you out.Read more →” narrative can’t hold when the AI itself is proprietary.

Returns Score: 55/100

FET scores 55/100 (C grade). Full methodology at Returns Score Methodology.

Token utility (14/20): FET is the staking token for Fetchhub-4 validators, the governance token for alliance-wide decisions, and the payment token for agent services and ASI Cloud compute. Those are three genuine utility layers, which is more than most projects in this space can claim. The complication is the merger. Three separate communities (Fetch.ai, SingularityNET, and CUDOS) were funnelled into one token, and the AGIX and CUDOS migration ratios created confusion about what FET actually represents. The utility is real but the identity is muddled.

Value accrual (8/20): The merger has made value accrual mechanics hard to evaluate, and the evidence so far is not encouraging. Ocean Protocol’s withdrawal and sale of 263 million FET on the open market demonstrated that the alliance structure can actively destroy value rather than create it. The settlement returned 286 million FET, partially unwinding the damage, but the episode set a precedent. ASI Cloud and ASI-1 Mini generate revenue, but both are centrally operated by Fetch.ai Inc. The fees flow to a company, and the relationship between that company revenue and FET token value is not transparent. The claimed $50 million buyback was presented as a positive signal, but even if verified, a one-off buyback is not a sustainable accrual mechanism.

Supply dynamics (10/20): The 2.71 billion cap absorbed three separate token supplies via migration, which is inherently dilutive to original FET holders who did not sign up for the additional supply. Ocean Protocol sold 263 million FET (over 10% of circulating supply) without disclosure, a supply shock of extraordinary magnitude. The settlement returned 286 million FET, but the sell pressure already hit the market. CUDOS migration included a 5% fee. The structural risk here is not the cap itself but the precedent that alliance membership can introduce surprise supply events.

Revenue sustainability (10/25): The uAgents framework is functional and has first-mover advantage in the agent space. Agentverse removes the developer barrier. ASI Cloud claims 50% cheaper than AWS. ASI-1 Mini offers inference with FET payments. The product breadth is real: multiple revenue-generating surfaces exist, and the framework has been live long enough to accumulate a developer base. The problem is that none of these products publish usage metrics. For a project that has been building since 2017, the absence of public revenue data, marketplace volumes, or active user counts is a deliberate choice, and not one that inspires confidence. Revenue likely exists at some scale, but without transparency the market will price it conservatively.

LiquidityLiquidityHow easily a token can be bought or sold without moving the price. High liquidity means you can enter or exit large positions quickly at the quoted price. Low liquidity means even small trades can swing the market.Like the difference between selling a house and selling a share of Apple stock. The house might be worth more on paper, but finding a buyer at that price takes weeks. The Apple share converts to cash in one click.Read more → and access (13/15): This is FET’s strongest dimension. Major CEX listings across Binance, Coinbase, Kraken, and others provide genuine institutional-grade liquidity. Strong daily volume means you can enter and exit meaningful positions without moving the market. The Binance Launchpad IEO origin gives the token deep exchange relationships. For all the project’s problems, you can at least trade it properly.

Path to improvement

Three changes would materially increase the ASI Alliance’s returns score:

1. Publish auditable revenue metrics for all products. ASI Cloud, ASI-1 Mini, Agentverse, and SingularityNET marketplace should each have public dashboards showing active users, transaction volumes, and revenue. The market can’t value what it can’t measure, and the persistent opacity is being priced as a risk premium.
2. Establish a transparent, recurring buyback-and-burn funded by platform revenue. The $50 million buyback was a one-off. A monthly or quarterly burn funded by a fixed percentage of ASI Cloud and marketplace fees would create predictable deflationary pressure and demonstrate that product revenue flows to token holders, not just to Fetch.ai Inc’s balance sheet.
3. Publish a governance post-mortem. The Ocean lawsuit has been settled and the 286 million FET returned, removing the immediate legal overhang. But the alliance hasn’t published a transparent account of what happened or what governance reforms will prevent a recurrence. Without that, the governance risk discount persists.