Bittensor subnet analytics, evidence-first.
TAO is Bittensor's native token. Subnet tokens are specific bets inside the network — each with its own AMM pool, emissions, builders, and risk. dTaoAnalytics is a private, not-for-profit workbench for examining that complexity: which subnets carry evidence, which look fragile, and where liquidity or costs make a position not worth holding.
Why this exists
The hard part is not buying TAO. It is choosing the right subnets.
Bittensor has many subnet tokens, each with its own AMM pool, emissions, liquidity, builders, and risk profile. Some attract real capital and useful demand. Others are too thin, too noisy, or already breaking. dTaoAnalytics makes that allocation decision clearer by holding three things in tension on every page.
Evidence first
Track which signals actually predict subnet returns.
Indicators are tested against a labeled outcome ledger that compounds daily. A claim is only useful if it survives that test.
Liquidity aware
A good idea is worthless in a thin pool.
Pool depth and slippage are first-class inputs to every recommendation, not a footnote you discover after entering the position.
Cost honest
Strategies are benchmarked, then held to a net-of-cost bar.
Performance is compared against passive TAO and Bittensor baselines. Net-of-cost reporting — fees, slippage, turnover — is the bar system strategies must clear before earning capital authority.
How it fits together
A five-step loop, one page per step.
Each product page answers one question in the investment loop. Walk it once, return to it whenever the regime changes. The full guide is on Learn dTaoAnalytics (~12 min read). The indicator side of the loop is on Methodology.
Live emissions
Every block, TAO flows to specialised AI subnets.
Each circle is one subnet, sized by its share of TAO flowing into subnet pools in the last 24h. Color marks the share tier. Click a subnet to open its detail page.
Built with provenance
A private research workbench on its own Bittensor data pipeline.
Own-node data, block-level provenance where practical, and a labeled outcome ledger that lets the methodology be tested rather than asserted. Evidence first, liquidity aware, cost honest — on every page.
Read the approachDirect Subtensor data pipeline.
Every collector decision matched against the outcome that followed.
Block context and freshness on every metric where practical.
Start with the Market Room.
Open the zone roster to see which subnets are tradable, which look attractive, and which are breaking. Then read this week's research for the editorial overlay.