Trading activity:
Reported 24-hour volume equals 0.19% of market capitalization. The local markets snapshot lists Uniswap V3 (Ethereum) among venues with observed trading activity.
YearBull indicators:
YearBull Rank #80,604. Bull Score 57/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h 0.00% · 7d 0.00% · 30d 0.00%.
Values are descriptive and should be read together rather than as a price forecast.
Read the YearBull methodology.
Snapshot date: 2026-10-27.Data history: 66 daily observations available in the latest 90-day window.
Methodology responsibility:
YearBull’s analytical methodology and presentation rules are developed and maintained by
Alan Zelvin, Founder & Lead Crypto Researcher.
This note identifies responsibility for the methodology; it does not attribute authorship of this data snapshot.
What is Powerloom (POWER)?
Source description
“Powerloom is the next-gen data layer for onchain consumer applications like DeFi, GameFi, NFTs, and more. It powers Web3 data apps that don’t want to spend millions of dollars on building or maintaining data access systems, RPC subscriptions, and data SaaS subscriptions. Powerloom helps them reduce operational costs, optimizing instead for scalability, flexibility, and agility. Every data point in every dataset generated by Powerloom is peer-validated, backed by consensus, and present on IPFS for complete transparency and trust.”
This source-supplied description may contain old, promotional, or unverified claims and is not YearBull editorial analysis.
Official links and contract records appear in Key Facts. Project details can change, so verify current information with the project.
Powerloom (POWER) FAQ
How does Powerloom position itself for onchain consumer applications?
Powerloom says it serves applications across DeFi, GameFi, NFTs, and related Web3 categories. Its stated role is to provide a data layer for products that need dependable access to onchain activity without building and maintaining extensive internal infrastructure. The project presents this approach as a way for application teams to focus on their products while reducing the operational burden associated with data access.
What costs does Powerloom claim to help Web3 applications reduce?
The project states that teams can avoid or reduce spending on several data-access requirements, including large-scale infrastructure, RPC subscriptions, and data SaaS subscriptions. Powerloom positions its platform as an alternative to assembling and maintaining these components independently. The claimed benefits are lower operational costs, greater scalability, and more flexibility as an application’s data needs change.
How does Powerloom describe its approach to validating data?
Powerloom presents each data point in its datasets as peer-validated and backed by consensus. In practical terms, the project says multiple participants help establish confidence in the data rather than relying solely on one party. This is a project-level claim about its validation model; the precise participant requirements, consensus design, and dispute-handling process are not specified here.
Why does Powerloom use IPFS for its datasets?
The project says its datasets are present on IPFS, linking that arrangement to transparency and trust. IPFS is a distributed content-addressing system, so placing material there can make records easier to reference independently of a single hosting location. Powerloom’s stated rationale is to make its data more openly verifiable, although the exact retention, pinning, and update procedures are not specified.
What operational qualities does Powerloom emphasize for Web3 data applications?
Powerloom positions scalability, flexibility, and agility as central operating goals. These qualities are presented as useful for applications whose onchain data requirements may grow or change across areas such as DeFi, GameFi, and NFTs. The project’s stated model aims to reduce the need for teams to build every data-access component themselves, though specific performance targets and service-level commitments are not stated.
Powerloom metric comparison
This comparison is a stored snapshot generated 2026-10-23 06:31 UTC from 207 daily observations available from 2025-12-30 through 2026-10-23. It is separate from the latest analytical cards above. Percentiles compare the snapshot value with that day's analytical universe; a higher percentile means a larger observed value, not necessarily a better investment characteristic.
Metric
Snapshot
30d before
90d before
Change vs 30d
Universe percentile
Price
$0.00005906
$0.00005906
$0.00022129
0.0%
n/a
Market cap
$19.5K
$19.5K
$41.9K
0.0%
P10.5
YearBull Rank
n/a
n/a
#5,814
n/a
n/a
Bull Score
n/a
n/a
30/100
n/a
n/a
Turnover
0.19%
0.19%
0.04%
0.0 pts
P37.3
YB Market Risk
n/a
n/a
Low
n/a
n/a
Cycle
n/a
n/a
Early
n/a
n/a
Median absolute daily movement 0.00%; distance from the highest local daily price -97.8%; circulating supply change +74.2%. These measurements are descriptive and do not predict future direction.
YearBull Rank on this page
YearBull Rank now for powerloom: #80604.
Rank timeline (last 365 days)
Rank change (daily snapshots).
Reading rule: a smaller rank number indicates stronger placement.
7d window: no reference point available.
30d window: no reference point available.
Risk profile: short bursts do not always translate into durable placement. If the last week is quiet, the current rank is usually easier to trust.
Cycle placement: phase changes usually leave a footprint in consistency. If the line breaks range, confirm with more than one week.
Orderflow context: deep markets usually produce smoother rank paths. If the line drifts, liquidity may be gradually shifting.
Exchange footprint: one venue can dominate the profile in short windows. If rank can’t hold gains, it can be concentrated pressure.
YearBull Rank is an internal ordering on YearBull that positions a coin relative to the rest of the tracked universe. A smaller rank number indicates a stronger position at that moment. It is a context signal for relative placement, not an outcome forecast.
Editorial note:
This analysis was prepared by the YearBull research team under the direction of
Alan Zelvin,
Founder and Lead Crypto Researcher.
The assessment follows YearBull’s internal research methodology and editorial standards.
Methodology ·
Editorial Policy
Related Research
Continue with contextually connected profiles and category data:
Stored venue snapshot. Markets last checked: 2026-08-14. Updated on a rolling basis; no fixed refresh date is promised. Venue listings and volumes are stored snapshots, not live quotes.
