We are launching Endure: a decentralized risk intelligence network on Bittensor $TAO, SN30. Risk should not depend on static reports, closed committees, or reputation alone. Endure turns risk intelligence into a competitive, continuously scored network. Forge, the first native lending market for $TAO, launches soon.

Before Forge or Endure have even launched, people are already choosing to build alongside us. That is what Forge's TVL commitments and the partnerships forming across the Bittensor ecosystem actually represent: not capital chasing a return, but conviction in the loop this is designed to create. Once Forge is live, more than 50% of its revenue is planned for Endure Alpha buybacks, strengthening the incentives behind the network, attracting better contributors, and producing better risk intelligence over time. $TAO SN30.

Endure Quality and Resilience Equity Vault is not picking stocks on a hunch. Every stock considered for the vault is scored across five things: how profitable and well-run the business is (30% weight), how strong and low-risk its finances are (20%), how well the stock has been performing lately (25%), how reasonably it is priced (15%), and how well it tends to hold up when markets fall (10%). Nothing gets in on one strong number. A stock has to hold up across quality, strength, momentum, valuation, and downside risk at once, which is exactly the kind of resilience the vault is named for. Explore the vault: app.pros-per.xyz/?view=detai…

There should be accountability for mistakes, and on Endure, there will be. Miners will earn emissions proportional to their score, which means low-accuracy miners will earn close to nothing. The accountability will not be symbolic or reputational. It will be the emission curve itself. Over time, the protocol is designed to extend this further: miners staking capital directly against their own submissions, giving downstream users a direct economic signal that the miner actually believes its own output. $TAO SN30.

A single team shares one set of assumptions across everything it produces, so when those assumptions are wrong, every output built on them is wrong together. There is no internal correction mechanism. A network of hundreds of independent miners with diverse methodologies does not share that failure mode. Different assumptions fail differently, and the aggregation finds the signal that survives across them, structurally more robust than anything a single team could produce. This is not a philosophical preference. It is how uncorrelated errors behave mathematically. $TAO SN 30.

A risk intelligence network gets better the more it is used. Every product that will consume Endure's signal adds real market behavior to score against, which means better-calibrated miners and a more accurate signal over time. Early partners are not just customers. They are the first source of real outcomes that make the network worth building on. Forge is the first, and conversations with others are already underway. The earlier a product joins, the more it influences what the network becomes. $TAO SN30.

Endure Quality and Resilience Equity Vault is live on Prosper. The strategy leans on a broad-market core, 60% in VTI, with 35% split across a diversified sleeve of individually selected stocks, names like AAPL, MU, DXCM, and ROST among them, weighed on profitability, resilience, valuation, momentum, and downside risk, and the remaining 5% in SGOV. The vault is being curated by hand for now, rebalances periodically, and is not capital protected; share value may fall. You can deposit USDC starting from just 1 USDC, with no lock-up and prices updating daily. Management runs 0.5% annualized, with a 20% performance fee. Explore the vault: app.pros-per.xyz/?view=detai…

On Endure tesnet, a miner's score is not just this round's result. It is smoothed with an exponential moving average over a 5-round half-life, so one lucky round does not suddenly put you at the top, and one unlucky round does not suddenly drop you out. But that protection does not extend to silence: the EMA is absence-aware, so skipping a round does not preserve your current standing, it counts against it, the same as if you had submitted and scored poorly. Consistency is what actually gets rewarded, not a good score from rounds ago that you stopped defending. $TAO SN30.

We’re officially live on Prosper Endure is the first subnet on Bittensor curating a Vault on Pharos blockchain. - Our strategy: Endure Quality and Resilience Equity Vault - Our p{VAULT}: pCARP You can now follow our onchain performance and watch the market around the strategy develop in real time. → app.pros-per.xyz/?view=detai…

It's time ⚓️ @ProsperTicker

Miners on Endure will be ranked by demonstrated accuracy, not tenure, firm size, or prior clients. Reputation can help a consumer decide how much trust to place in a signal, but it will not decide the network's ranking. A miner with superior submissions outranks an established firm with average submissions. This inverts how credit rating agencies have always worked, where the entry barrier is existence itself, licensing, corporate relationships, and historical coverage, rather than current accuracy. On Endure, the cost of being new is paid in observed performance, not years of incumbency. $TAO SN30.

On Endure testnet, scoring runs on one function, applied to every prediction: how close were you, and which way did you miss. Inside a grace band around the real outcome, a miner scores 1.0. Beyond a cutoff, 0.0. Between the two, the score falls linearly. The cutoff is not symmetric. Missing in the dangerous direction costs more than missing safely. For drawdown and volatility, telling a consumer the token is calmer than it turns out to be is the dangerous miss. For price and liquidity, claiming there was more of either than there really was is the dangerous miss. In every case, the safe direction gets three times more room before it is penalized. A risk model that treated both directions the same would not be doing its job. The asymmetry is the point. $TAO SN30.

Endure testnet is still open, and every submission right now is helping shape how the network scores risk going forward. If you have not tried mining or validating yet, this is the moment to get in early. $TAO SN30.

Once on mainnet, when Forge earns, @EndureNet ($TAO SN30) grows. That's the loop.

Target and context define what is being assessed and under what regime. Schema is what makes that assessment usable. A schema is the bundle of outputs, invariants, and scoring logic that governs an assessment. For the current vertical, Alpha Risk V1, that schema is risk.v1.subnet_alpha. It fixes four scored outputs, max drawdown, realized volatility, TWAP price, and liquidity depth, each predicted over two horizons: five days and thirty days. Four outputs times two horizons is eight scored values per subnet per round. A submission missing any pair is rejected before it is scored. Two miners submitting under the same schema are directly comparable. Two miners submitting under different schemas are not, their outputs are scored and aggregated separately. The schema is the contract. $TAO SN30.

Want to join Endure testnet but not sure where to start, or have questions about how to participate? Our Discord community is there to help. → discord.gg/cSWdVDH4ug $TAO SN30.

Endure testnet is live Miners can now submit structured Alpha collateral risk recommendations, and validators can score them against realized market behavior. The incentive and validator mechanisms are running on netuid 504 under the risk.v1.subnet_alpha schema. Full documentation for validators and miners is in the docs. Read them: docs.endure.network/build/mi… Github: github.com/endure-network/en… $TAO SN30.

Every assessment on Endure will be identified by three axes: target, context, and schema. We covered target already. Now, context. A context is the regime an assessment will be produced under. For the first vertical, Alpha Risk V1, that context will be risk.v1. It will pin the horizons an assessment resolves over and what "risk" means for this vertical: objectively resolvable market observables, measured over a forward window. Context exists as its own axis because the same target can carry a different risk profile depending on how it is being used. A subnet token assessed for a five-day volatility horizon is a different question than the same token assessed for a thirty-day drawdown horizon, and both differ from how that token would be assessed inside a lending or margining context. Separating context from target keeps those distinctions explicit instead of collapsing them into one number. $TAO SN30.

A design partner is not just an early user. Once Endure is live, they will consume its risk intelligence in a real context, against real decisions. In doing so, they will surface what useful risk intelligence looks like in practice: which outputs matter, which schemas need refinement, and where the signal is strong enough to act on. That feedback will feed directly into how the network develops: sharper schemas, wider coverage, and more accurate intelligence over time. For the partner, it will mean access to a risk layer that adapts to their needs before it is widely available. For the network, it will mean real outcomes to score against and real conditions to refine the intelligence under. Both sides get something the other cannot build alone. $TAO SN30

Once Endure and Forge are live, every action inside that loop will become something Endure can score against real market behavior. Usage becomes revenue, revenue becomes buybacks, buybacks strengthen incentives, and stronger incentives attract the contributors who make risk intelligence better over time. $TAO SN30.

The dominant model in risk intelligence is concentration: a few analysts, shared assumptions, correlated outputs, and when the consensus is wrong, it is wrong at scale. A handful of credit rating agencies using similar assumptions to rate mortgage securities showed what that looks like in 2008: the ratings did not just miss individually, they missed together. Endure is being built on the opposite premise: no credentialing, no whitelist, no minimum firm size. Hundreds of independent miners with diverse methodologies will compete simultaneously, all scored against real outcomes. When market conditions shift, some models will fail, and others will adapt. The network will continue producing accurate intelligence throughout. That is the structural advantage of open over closed. Not a philosophical preference, but a documented failure mode that concentration produces and diversity prevents. $TAO SN30.