ChainOpera AI (COAI) market snapshot:
Price $0.292460, market capitalization $54.98M,
and reported 24-hour volume $2.46M.
Trading activity:
Reported 24-hour volume equals 4.47% of market capitalization. The local markets snapshot lists PancakeSwap V3 (BSC), LBank and Gate among venues with observed trading activity.
YearBull indicators:
YearBull Rank #1,595. Bull Score 50/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h -1.57% · 7d -9.35% · 30d -3.52%.
Values are descriptive and should be read together rather than as a price forecast.
Read the YearBull methodology.
Snapshot date: 2026-09-29.Data history: 90 days 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 ChainOpera AI (COAI)?
YearBull Project Summary: ChainOpera AI (COAI) is tracked under chainopera-ai. The local profile associates it with Artificial Intelligence (AI), BNB Chain Ecosystem, AI Applications, Binance Alpha Spotlight. The source profile maps it to binance-smart-chain.
Source description
“ChainOpera AI empowers collaborative intelligence through a network of AI agents co-created and co-operated by the community. It is built on a Super AI app and a full-stack AI infrastructure that supports a creator economy for designing, distributing, and using AI agents; agent-centric model training and inference on distributed GPUs; and an AI-native blockchain for verifiable ownership, attribution, and transparent participation. ChainOpera transforms how intelligence is created and shared by aligning users, developers, and infrastructure providers through shared participation mechanisms, enabling a new era of open and collaborative AI.”
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.
ChainOpera AI (COAI) FAQ
How does ChainOpera AI involve the community in creating and operating AI agents?
ChainOpera AI presents a model in which community members co-create and co-operate AI agents. Its stated participation structure brings users, developers, and infrastructure providers into the same ecosystem, with shared mechanisms intended to align their contributions. The project frames this approach as a way to make intelligence creation and use more collaborative rather than controlled solely by a central operator.
What role does the Super AI app play within ChainOpera AI?
The project positions its Super AI app as a central part of its broader platform. It is described alongside full-stack infrastructure that supports the design, distribution, and use of AI agents. This combination is intended to connect agent creators with people who use those agents, while also supporting a creator economy around AI applications.
How does ChainOpera AI support agent-centric model training and inference?
ChainOpera AI states that its infrastructure supports agent-centric model training and inference across distributed GPUs. In practical terms, this places AI-agent workloads at the center of the computing framework and uses geographically distributed graphics processing resources. The project presents this architecture as a foundation for expanding access to the computing needed to develop and operate AI agents.
What is the purpose of ChainOpera AI’s AI-native blockchain?
The project describes its AI-native blockchain as a layer for verifiable ownership, attribution, and transparent participation. These functions are intended to help establish who owns or contributes to an AI agent and to make participation more visible within the ecosystem. ChainOpera AI links this blockchain layer to its broader goal of coordinating users, developers, and infrastructure providers.
How does ChainOpera AI describe its creator economy for AI agents?
ChainOpera AI presents a creator economy centered on designing, distributing, and using AI agents. The model is intended to give creators a framework for bringing agents to users, while connecting those activities with the underlying infrastructure for training and inference. The project says shared participation mechanisms can align the interests of contributors across this ecosystem.
ChainOpera AI metric comparison
This comparison is a stored snapshot generated 2026-09-27 06:30 UTC from 267 daily observations available from 2025-12-30 through 2026-09-27. 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
$0.3120
$0.2971
$0.2729
+5.0%
n/a
Market cap
$58.65M
$55.86M
$51.18M
+5.0%
P94.8
YearBull Rank
#1,290
#3,008
#722
Improved 1,718
P85.7
Bull Score
58/100
27/100
73/100
+31.0 pts
P71.5
Turnover
2.40%
3.24%
7.95%
-0.8 pts
P68.3
YB Market Risk
Low
Low
Low
Unchanged
n/a
Cycle
Early
Early
Early
Unchanged
n/a
Median absolute daily movement 2.64%; distance from the highest local daily price -32.8%; circulating supply change -4.3%. These measurements are descriptive and do not predict future direction.
Editorial research. Identity, project facts, sources, and risks below belong to the dated editorial review. The live analytical snapshot above may be newer and is generated separately from stored market data.
ChainOpera AI (COAI) is tracked under chainopera-ai. The local profile associates it with Artificial Intelligence (AI), BNB Chain Ecosystem, AI Applications, Binance Alpha Spotlight. The source profile maps it to binance-smart-chain.
Asset Role and Supply
Its role should be evaluated through network or product use, supply design, governance, liquidity, and trading-venue quality. The reviewed record shows circulating supply about 188.00 million COAI, total supply about 1.00 billion COAI, maximum supply about 1.00 billion COAI. It classifies supply as capped. Supply fields may change through issuance, burns, migrations, or source revisions and should be checked against project records.
Market Structure
At the 2026-09-12 review, the local snapshot placed ChainOpera AI at market-cap rank #418, with market capitalization about $56.12 million and reported 24-hour volume of $1.84 million. These values describe observed scale and turnover, not fair value or guaranteed executable liquidity.
YearBull Perspective
The dated snapshot recorded YearBull Rank #2,666, Bull Score 30/100, Risk Low, and Cycle Early. Rank, Bull, Risk, and Cycle answer different questions and should be read together.
Key Risks
Material risks include market volatility, liquidity deterioration, protocol or governance failure, concentration, and regulatory change. Historical prices, rankings, and classifications do not predict future performance. Verify contract addresses, network support, custody, and venue availability before acting.
Latest available YearBull Rank for chainopera-ai: #1595.
Rank timeline (last 365 days)
Rank movement (nearest daily data).
Reading rule: smaller rank numbers are better.
7d window (2026-09-22): #664 → #1595 (down by 931).
30d window (2026-08-30): #1808 → #1595 (up by 213).
Cycle view: If the line is range-bound, treat changes as relative, not absolute.
Risk placement: If the last month is chaotic, widen the lookback before concluding.
Market access: If rank holds gains, the footprint is likely supporting the move.
Liquidity framing: If the curve jumps, check whether the cohort moved too (relative effects).
Practical note: a single point is weaker than the curve shape.
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. Treat it as a directional context tool rather than a standalone verdict.
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: 2026-09-12. Next refresh window: around 2026-10-12. Venue listings and volumes are stored snapshots, not live quotes.
