Trading activity:
Reported 24-hour volume equals 0.91% of market capitalization. The local markets snapshot lists Raydium (CLMM) and Raydium among venues with observed trading activity.
YearBull indicators:
YearBull Rank #4,118. Bull Score 56/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h -1.20% · 7d -10.75% · 30d -17.36%.
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: 67 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 Yait Siu (YAIT)?
Source description
“Yait Siu is a next-generation AI agent that is multi-modal, multi-platform, and multi-skilled, designed to seamlessly integrate across various environments. Built with a focus on innovation, experimentation, and transparency, Yait Siu represents a groundbreaking step in AI development. By utilizing a universe of modular components, it enables the design and creation of frameworks that allow models to interact independently with the wider world. This approach fosters dynamic and flexible collaboration between AI systems and real-world applications, empowering developers to create solutions that are intelligent, scalable, and adaptive. As a project that builds and experiments in public, Yait Siu is redefining how AI systems are developed, deployed, and integrated across multiple domains, pushing the boundaries of what is possible in the AI landscape.”
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.
Yait Siu (YAIT) FAQ
How does Yait Siu’s modular-component approach support AI experimentation?
The project states that Yait Siu uses a universe of modular components to help design and create frameworks for AI systems. These components are presented as building blocks that can support experimentation, flexibility, and adaptation, although the project does not specify the individual modules, technical standards, or implementation process involved.
What does Yait Siu mean by enabling models to interact with the wider world?
Yait Siu presents its frameworks as allowing AI models to interact independently with external environments and real-world applications. The stated goal is to encourage dynamic collaboration between AI systems and practical applications, but the project does not define the supported environments, interaction methods, safeguards, or specific tasks these models can perform.
Which capabilities does Yait Siu associate with its multi-modal, multi-platform, and multi-skilled design?
The project describes Yait Siu as a next-generation AI agent intended to operate across different modes, platforms, and skill areas. This positioning suggests broad interoperability and varied functionality, but it does not identify the modalities, platforms, supported skills, or performance criteria used to substantiate those capabilities.
How does Yait Siu position public experimentation within its development process?
Yait Siu says it builds and experiments in public, linking this approach with innovation, transparency, and the ongoing development of AI systems. The project does not specify the channels, release practices, review procedures, or governance arrangements through which public participation or visibility is maintained.
What kinds of applications does Yait Siu say developers could create with its frameworks?
The project says its frameworks could help developers create solutions that are intelligent, scalable, and adaptive across multiple domains. It does not name particular industries, applications, integrations, or deployment examples, so the practical scope remains broad rather than tied to a defined product category or use case.
Yait Siu metric comparison
This comparison is a stored snapshot generated 2026-10-23 06:31 UTC from 157 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
$0.00001591
$0.00001512
$0.00023965
+5.2%
n/a
Market cap
$15.9K
$15.1K
$239.7K
+5.2%
P8.7
YearBull Rank
n/a
n/a
#5,985
n/a
n/a
Bull Score
n/a
n/a
55/100
n/a
n/a
Turnover
0.03%
0.24%
0.00%
-0.2 pts
P20.2
YB Market Risk
n/a
n/a
High
n/a
n/a
Cycle
n/a
n/a
Late
n/a
n/a
Median absolute daily movement 1.03%; distance from the highest local daily price -98.2%; circulating supply change 0.0%. These measurements are descriptive and do not predict future direction.
YearBull Rank update
Newest YearBull Rank value for yait-siu: #4118.
Rank timeline (last 365 days)
Rank movement (nearest daily data).
Reading rule: lower is better in this ranking.
7d window (2026-10-20): #2135 → #4118 (down by 1983).
30d window (2026-09-27): #2251 → #4118 (down by 1867).
YearBull Rank is a relative placement score used on YearBull to compare a coin against peers within the same dataset. Smaller numbers mean the coin sits higher in the YearBull list. Use it as positioning context over time, not as a promise.
Liquidity context: a quiet tape can still re-rank the pack.
Venue context: a tightened venue set can reduce variance or increase it.
Stability posture: consistency often matters more than speed.
Cycle read: a single week rarely defines a phase on its own.
Practical note: rank is best used for relative context, not certainty.
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: 2026-07-27. Updated on a rolling basis; no fixed refresh date is promised. Venue listings and volumes are stored snapshots, not live quotes.
