Forge

Endure is live on mainnet, and now you can check it yourself. The new dashboard follows SN30 on mainnet: network state, miner commits, and consensus accuracy, each backed by a source you can verify. Explore it: dashboard.endure.network Risk, with receipts. Because risk intelligence should be something you can check, not something you have to trust. $TAO SN30.

The Endure-Forge flywheel is starting to take shape. @ForgeLending, the first product built to run on Endure, has already attracted more than $4M in TVL commitments ahead of mainnet. Score Alpha will be the first collateral asset listed, once the audits are complete. The risk intelligence layer will score against real market behavior once Forge is live. Here is the loop those numbers are feeding into: Product usage will generate protocol revenue, and more than 50% of that revenue is planned for Endure Alpha buybacks, strengthening network incentives, attracting better contributors, and producing better risk intelligence over time. Risk intelligence that compounds. $TAO SN30

Quick update: Forge testnet has been a much stronger signal than expected. What started as a testnet release turned into hundreds of users, heavy traffic, and direct community interaction with the core primitive: borrowing TAO against Alpha collateral. That traction shows real curiosity and demand around Bittensor-native credit, and it gives the team live feedback on how users interact with Alpha-backed lending before broader rollout. @ForgeLending is the first proving ground for this market. It is where demand becomes visible, user behavior gets tested, and the risk questions become concrete: which Alpha markets should be accepted as collateral, how much exposure is safe, and how quickly should parameters adapt as liquidity, volatility, and drawdowns change? That is where Endure comes in. Endure is being built as the risk-intelligence layer behind Forge, but the long-term vision is broader than one lending market. The goal is to create an intelligence market where risk models compete, get benchmarked, and improve over time. In that world, raw market data is not enough. The valuable output is evidence-backed judgment: which signals matter, which models were early, which recommendations were accurate, and which insights were actually useful when conditions changed. For Forge, the current work is moving toward a lending V1 path where miners will be able to submit structured Alpha collateral risk recommendations and validators will be able to score them against realized market behavior. Recent progress has focused on turning that path into an executable subnet loop: Forge lending registry selection, reveal validation, Alpha collateral whitelist gates, lending market-data fixtures, real mainnet drawdown windows, miner submission flows, lending consensus logic, and validator hardening around state, pacing, config, and schema handling. Over the next phase, Endure should move closer to producing the types of outputs a lending market actually needs: safer pricing inputs, collateral-factor guidance, risk tiers, cap recommendations, liquidation assumptions, and eventually more adaptive risk parameters for Forge. At the same time, the team is working on the harder research problem: how to benchmark risk intelligence itself. That means thinking in terms of SOTA, baselines, and measurable improvement. Not just “did the model produce an answer?” but “did the model beat a naive benchmark, did it stay calibrated under stress, and did it turn noisy information into a decision that held up against future outcomes?” This is where concepts like Validated Insight Rate become important: measuring how reliably raw information turns into evidence-backed decisions. The potential is a network that can identify which models are consistently early, accurate, calibrated, and economically useful. Forge showed demand far beyond expectations for Alpha-backed TAO borrowing. Endure is building the market that can score the risk behind it.

Have you heard about @ForgeLending ? They are enabling Alpha collateralized lending. So lets say a SN team has to fund operations, they can simply borrow TAO against their alpha. They keep the upside potential and event 75% of alpha token yield.