Trading activity:
Reported 24-hour volume equals 1.16% of market capitalization. The local markets snapshot lists KuCoin, Gate and Uniswap V2 (Ethereum) among venues with observed trading activity.
YearBull indicators:
YearBull Rank #5,797. Bull Score 42/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h 3.94% · 7d -20.00% · 30d -27.50%.
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: 89 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 Humans.ai (HEART)?
Source description
“Humans.ai is a next generation blockchain platform that brings together an ecosystem of stakeholders around the use of AI to create at scale. It combines a library of AI tools into a creative studio suite where users will be able to pick and choose as they bring their ideas to life. Individuals are empowered to create and own their digital likenesses, which may be used by themselves and others in the creation of any number of digital assets. The synthetic media, AI apps, and other digital assets utilize blockchain technology to generate Non-Fungible Tokens (NFTs) as a way of creating transparency, provenance, accountability, and long-term governance.”
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.
Humans.ai (HEART) FAQ
How does Humans.ai’s creative studio approach work?
The project presents a creative studio suite that brings together a library of artificial-intelligence tools. Users are described as being able to select tools while developing their ideas, with the platform positioned as an environment for producing synthetic media, applications, and other digital assets. The project frames this approach as a way to support creation at scale within a broader stakeholder ecosystem.
What role do digital likenesses play in the Humans.ai ecosystem?
Humans.ai states that individuals can create and own digital likenesses. These likenesses may then be used by their owners or by other participants when producing different digital assets. The project links this model to personal control over representations and to the wider creation of synthetic media and applications, although it does not specify the precise ownership terms or permissions framework.
Why does Humans.ai use NFTs for synthetic media and other digital assets?
The project says blockchain technology is used to turn synthetic media, artificial-intelligence applications, and other digital assets into non-fungible tokens. It associates this tokenization with transparency, provenance, accountability, and long-term governance. These are stated platform goals; the project does not specify how each objective is implemented or which governance procedures apply to individual assets.
How does Humans.ai position different stakeholders within its platform?
Humans.ai positions itself as a blockchain ecosystem that brings together multiple stakeholders around the use of artificial intelligence for large-scale creation. The stated model connects tool selection, digital likenesses, asset production, and tokenization in one environment. However, the project does not define the stakeholder categories, their individual responsibilities, or how decisions are allocated among them.
Which blockchain ecosystems are associated with HEART, and why does that matter here?
HEART is associated with Ethereum and Osmosis, while the project describes blockchain as the foundation for tokenizing digital assets and supporting provenance, accountability, transparency, and governance. The project does not explain how responsibilities are divided between these networks, whether every feature operates on both, or how users move assets across the two ecosystems.
Humans.ai metric comparison
This comparison is a stored snapshot generated 2026-10-22 06:31 UTC from 291 daily observations available from 2025-12-30 through 2026-10-22. 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
$0.00033611
$0.00038908
$0.00027789
-13.6%
n/a
Market cap
$2.62M
$3.03M
$2.17M
-13.6%
P74.7
YearBull Rank
#3,617
#385
#5,258
Lower by 3,232
P57.6
Bull Score
51/100
90/100
17/100
-39.0 pts
P52.1
Turnover
1.29%
1.33%
3.68%
0.0 pts
P59.9
YB Market Risk
Low
Medium
Low
Medium → Low
n/a
Cycle
Early
Early
Early
Unchanged
n/a
Median absolute daily movement 2.90%; distance from the highest local daily price -82.1%; circulating supply change 0.0%. These measurements are descriptive and do not predict future direction.
YearBull Rank update
Most recent YearBull Rank reading for humans-ai is #5797.
Rank timeline (last 365 days)
Rank change (daily snapshots).
Reading rule: rank #120 sits higher than rank #200.
7d window (2026-10-20): #2835 → #5797 (down by 2962).
30d window (2026-09-27): #523 → #5797 (down by 5274).
YearBull Rank is a comparative index on YearBull that helps contextualize a coin’s position versus others over time. Lower rank numbers indicate stronger placement in the current snapshot. It is best read as relative context across time windows, not as a guarantee.
Risk framing: short bursts do not always translate into durable placement. If it moves only on certain days, it can be update cadence.
Liquidity read: deep markets usually produce smoother rank paths. If the curve improves but won’t hold, treat it as flow-driven.
Cycle framing: phase changes usually leave a footprint in consistency. If the line breaks range, confirm with more than one week.
Exchange footprint: one venue can dominate the profile in short windows. If the line range widens, access or routing may be changing.
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: 2026-10-15. Next refresh window: around 2027-01-13. Venue listings and volumes are stored snapshots, not live quotes.
