Press Release
UniArt’s impossible art formula gallery bring bottom-up NFT appreciation with vote mining on 30th Sep
Preamble
Recently, “Loot” has been spreading virally throughout the crypto community. Industry key opinion leaders (KOLs), founders of quality projects, and investment institutions all pay close attention to the emerging “bottom-up” concept, and more community members are excited about it.
Despite the term bottom-up only recently coming into the limelight, in essence, the philosophy may be at the root of the entire crypto economy. Bitcoin, for example, breaks the rules of centralized government-issued fiat currency by enabling anyone that follows its PoW consensus algorithm to produce a new currency. On the other hand, Ether allows developers to build arbitrary dApps on top of it without permission, and its prosperity hinges on the frequency of this.
These two patriarchs of the crypto economy have opened up a bottom-up path outside the centralized internet. The bottom here can be anyone. The top is no longer governments or corporations but now code, algorithms, data, and consensus mechanisms. Loot is the first bottom-up non-fungible token (NFT), possessing similar intrinsic characteristics at the root of its explosion.
The most widespread application of NFT is currently in the art sector. Crypto community practitioners are working to bring NFT into the traditional art marketplace. To accomplish this, NFT must have general acceptance and market consensus, not just within a niche group of artists and appreciators. Take the most common financial application of collateralized lending, for example; a starving artist, globally unknown pledges his minted NFT to you, the potential lender. They claim it is worth US$10,000 and want to borrow against this collateralized value. Naturally, you are hesitant, unsure of its market value, and even if a current buyer is willing to purchase it at that price, you are still uncertain about its future value. In short, there is not enough market consensus for that NFT. However, let’s use CryptoPunk or BAYC as collateral in this example. Results would be the opposite because each of these digital assets already has widespread market consensus, having been classified as antiques in the NFT community. Therefore, the fair market valuation of NFT is critical to achieving market consensus in the financial sector. Exploring a suitable value solution for NFT is beneficial in a financial application, which opens up various other possibilities for NFT, leading to the further development of the whole crypto community.
UniArts aims to uncover NFT fair market valuation through its customized bottom-up Nominated Proof-of-Stake (NPoS) economic model, aspiring decentralized incubation of creators and their works. In this paper, the core concept of UniArts will be comprehensively explained using this bottom-up concept as the source idea.
Bottom-up NFT Fair Market Valuation
The term bottom-up can be understood differently in different contexts; building on top of a foundation is not a required characteristic. In the context of UniArts, bottom (in a non-pejorative sense) can be understood as what people define together and top as the fair value of NFT. This bottom-up approach is contrasted with more traditional top-down valuation, which was determined mainly by centralized auction houses or prominent collectors. Less renowned artists rarely gained any attention, and in the rare chance they did, their work would often be considered nearly worthless. Such an approach does nothing to showcase potentially exceptional pieces for the mere reason they are unknown, and they remain misunderstood by the public.
In the UniArts network, $UART holders are deemed “nominators,” pledging their tokens as “votes” for an NFT they admire. The more votes an NFT receives, the more people approve of it, and the higher the consensus level. When people are required to invest in their decisions, they become much more selective. Since there is value in $UART, the votes that an NFT receives indicate its fair market value. In the early stages of UniArts’ development, the small user base may not be sufficient to tie the word fair to an NFTs value, but as the network expands, it will become more and more convincing. This process can be referred to as the “flywheel effect.”
Appreciate to Earn
“Appreciate To Earn” is a new concept and a subset of “Play To Earn,” in that merely appreciating an NFT is akin to the process of playing. Axie Infinity, a chain game that has been popular in the crypto community for a while now, relied on this “Play To Earn” concept as the fuel to expand its user base. From this vetted example, we know that it is a viable business model.
UniArt’s Nominators pledge $UART and select an NFT they appreciate to earn more $UART, including a base pledge bonus and a block bonus for top-ranked NFTs. In this process, the word appreciate corresponds to the nominator, and the word earn corresponds to the earned $UART. In Axie Infinity, players buy a pet “Axie” as an entry ticket to the game and earn revenue in-game from this Axie. In UniArts, $UART is the entry ticket into the network.
Play to Earn can be viewed as a modern concept to attract new users. Traditional game companies pay third-party advertising companies to attract new users, but these users do not receive any income. Blockchain games use tokens to incentivize new users, which is a disguised way of attracting traffic; an alternative form of advertising, where the fees paid to advertising companies are instead attributed to the user. If this alternative form of advertising is integrated into a chain game’s economic model, one can only expect explosive organic user growth. Similarly, the Appreciate to Earn concept will cause natural growth of UniArt’s user base, eventually to the point where fair valuation is achieved.
Multi-Chain NFT Gallery “Impossible Art Formula”
UniArts is native to Polkadot, and one of its strategic plans is to spread the NFT gallery to more popular blockchains, the first stop being Polygon. Mechanically, the gallery will be similar to the NPoS economic model but not identical.
- Six NFTs will be presented in each issuance, and users can pledge $UART or $WETH to vote on their favorite NFT.
- There are a total of 3 revenue pools, including a casting pool, a general pool, and a bonus pool. The bonus pool added to the gallery is unique in comparison to the NPoS model mentioned above. The casting pool is a pool in which $UART is minted into an NFT based on the percentage of votes received by the NFT. The general pool allocates rewards based on the proportion of user votes to the total number of votes in the corresponding NFT.
- At the end of each voting period, NFT owners have the option to participate in the next three-day auction. The bonus pool is allocated to the corresponding NFT according to the ratio of the price sold in the auction to the sum of all prices traded in the auction for that period. This pool is then allocated to users that voted in the general pool, as mentioned in (2).
- Specific details can be found in the following chart:

UARTs tokens are capped at 200 million, with 10% held by the team and released after 3 years, 12% by early stage investors, 10% by the treasury, and the rest by NFT vote mining, “Appreciate To Earn”.
“Impossible Art Formula” demonstrates the lack of a perfect solution in art valuation as everyone has their unique preferences. Let’s solve this by using $UART to appoint the “Hamlet” we fancy.
Concluding Remarks
UniArts has customized the NPoS economic model for NFT with an Appreciate To Earn mechanism based on the bottom-up source concept, which helps NFT discover its fair value. This value discovery fills an essential gap in applying NFT to traditional art and financial systems, paving a new path in crypto circles.
The impossible art formula is accessible now and will be online on 30th Sep.
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Affordable SEO Expert Anatoly Zadorozhnyy Announces Launch of SEO Consulting Website
Anatoly Zadorozhnyy has launched Affordable SEO Expert, a dedicated website that allows businesses to work directly with him for SEO services without going through a traditional agency structure. The website outlines his offerings, including technical SEO audits, on-page optimization, and link building, while also providing insight into his experience and SEO methodology.
Los Angeles, CA, United States, 26th May 2026 – Affordable SEO Expert, a newly launched website operated by SEO professional and founder of Marketing 1on1, Anatoly Zadorozhnyy, is now online. The platform was created to provide information on search engine optimization services, SEO methodologies, and digital marketing practices for website visibility and organic search performance.
The website covers several areas of SEO, including technical SEO audits, on-page optimization, content structure analysis, link-building practices, and website performance considerations. The platform also outlines general information regarding SEO processes commonly used to support website indexing, search accessibility, and content relevance across search engines.
The launch of the website reflects ongoing activity in the SEO industry, as independent consultants and specialized platforms expand their online presence to provide educational resources, service information, and search optimization support for businesses across a wide range of industries.
The website also contains information on SEO practices, including both on-site and off-site strategies. Topics referenced throughout the platform include metadata optimization, website structure evaluation, keyword targeting considerations, internal linking practices, technical site analysis, and backlink-related SEO factors commonly associated with organic search visibility.
In addition to service-related information, the website includes background details on industry experience and professional focus areas related to search engine optimization and digital marketing. The platform references work associated with websites operating in local, regional, and broader online markets where search visibility and website accessibility remain important aspects of digital presence management.
Website Features
The Affordable SEO Expert website includes several informational sections, including:
- Information about available SEO-related services
- Background and professional experience details
- Technical SEO and on-page optimization information
- General information related to link-building practices
- Contact and inquiry submission functionality
- Website optimization and search visibility resources
The website launch represents an additional entry into the growing number of specialized online platforms focused on SEO consulting, digital marketing information, and website optimization services. As search engine algorithms and digital marketing standards continue to evolve, platforms dedicated to SEO education and optimization resources remain an active segment of the broader online marketing industry.
About Anatoly Zadorozhnyy
Anatoly Zadorozhnyy is an independent SEO consultant. His work spans technical optimization, content strategy, and search visibility improvements for businesses operating in competitive online markets. The launch of affordableseoexpert.com formalizes the direct consulting model he has operated under. It serves as the primary channel through which new and existing clients can engage his services.
Website: https://www.affordableseoexpert.com/
Facebook: https://www.facebook.com/affordableseoexpertservices/
Media Contact
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City: Los Angeles
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The post Affordable SEO Expert Anatoly Zadorozhnyy Announces Launch of SEO Consulting Website appeared first on King Newswire. This content is provided by a third-party source.. King Newswire makes no warranties or representations in connection with it. King Newswire is a press release distribution agency and does not endorse or verify the claims made in this release. If you have any complaints or copyright concerns related to this article, please contact the company listed in the ‘Media Contact’ section
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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Giggso Introduces Raven, Andie, and AIRTaaS to Help Enterprises Bring Discipline, Reasoning, and Security to AI Adoption
TROY, Mich., May 26th, 2026, ZEX PR WIRE — Enterprises are moving faster with AI than ever before. But many are also quietly losing comprehension of the systems they are building.
Engineering teams now generate code, workflows, automations, and AI-driven decisions at unprecedented speed using tools like Claude, Codex, Cursor, and enterprise copilots. While productivity has increased, organizations are also experiencing a new operational challenge: more meetings, fragmented workflows, inconsistent outputs, security concerns, architecture drift, and growing difficulty understanding how systems actually work together.
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Giggso calls this problem “comprehension debt” — the growing gap between AI-generated velocity and organizational understanding.
Today, Giggso announced Raven, Andie, and AIRTaaS, three offerings designed to help enterprises reduce comprehension debt and bring discipline, reasoning, and continuous security testing into AI adoption at scale.
Together, the offerings form the front door into GSD (Giggso Security Domain), Giggso’s broader architecture for governing, securing, and operationalizing enterprise AI systems.
“At a small scale, AI feels magical,” said Ravi Venugopal, Founder and CEO of Giggso. “At enterprise scale, it can quickly become operational chaos. Teams move faster, but understanding drops. Meetings increase. Ownership blurs. AI starts producing more than organizations can realistically comprehend or govern. That is the problem we are solving.”
At the center of the announcement is Raven, Giggso’s discipline layer for AI-assisted software development.
Raven is designed to help organizations enforce engineering discipline inside AI-driven development workflows before problems reach production. Rather than acting as a traditional code scanner after development is complete, Raven introduces governance, architecture awareness, policy enforcement, and review controls directly into AI-assisted coding environments.
The platform helps organizations identify risks such as:
- architecture drift
- unapproved libraries
- exposed secrets
- policy violations
- insecure dependencies
- undocumented AI-generated logic
- uncontrolled AI usage patterns
The goal is not to slow development, but to preserve organizational understanding as teams move at AI speed.
“AI can now generate code faster than teams can comprehend it,” Ravi said. “Without discipline, enterprises accumulate technical debt, security exposure, and operational confusion at machine speed. Raven helps organizations preserve engineering quality and architectural understanding while still moving fast.”
Giggso also introduced Andie, a structured reasoning engine designed to help enterprises improve contextual thinking and operational decision-making across teams.
Unlike traditional chatbot-style AI interfaces that generate isolated answers, Andie is designed to help organizations reason through problems with context, constraints, and multiple perspectives in mind. The platform is intended to support operational workflows across delivery, strategy, planning, support, and execution environments.
Giggso believes one of the biggest failures in enterprise AI adoption is not a lack of intelligence, but a loss of shared understanding.
“Most organizations do not need another chatbot,” Ravi said. “They need systems that help teams think more clearly together. AI should reduce confusion, not multiply it. Andie is designed to strengthen organizational reasoning, preserve context, and reduce the fragmentation that happens when every team operates with disconnected AI outputs.”
To address the growing security risks around enterprise AI adoption, Giggso is also expanding AIRTaaS, its AI Red Teaming as a Service platform.
As enterprises deploy AI agents, copilots, retrieval systems, and autonomous workflows into production, traditional security testing approaches are increasingly insufficient. AI systems can fail through prompt injection, hallucinations, role-boundary violations, tool misuse, unsafe autonomy, data leakage, and adversarial manipulation.
AIRTaaS continuously stress-tests AI systems against these real-world failure scenarios before they become operational incidents.
The platform combines:
- AI red teaming
- observability
- governance workflows
- incident tracking
- remediation guidance
- human-led adversarial testing
To strengthen its execution capabilities, Giggso has partnered with Seiance India, a woman-owned AI security startup based in Chennai, India, whose product, Trinity, is an AI security and observability platform.
“AIRTaaS turns AI security into an operational discipline instead of a compliance checkbox,” said Abhinaya, CEO of Seiance India P Ltd.
“Enterprises need continuous stress testing because AI systems are constantly evolving. Our focus is helping organizations identify weaknesses early, validate resilience continuously, and improve trust in production AI systems.”
Giggso also announced that portions of AIRTaaS and related tooling will be free for Individual Developers, while core Enterprise developer-focused red teaming capabilities will be low-cost and easy to certify for teams.
The company said the decision reflects a growing concern about “AI washing” — where organizations overstate AI capabilities without sufficient operational rigor — and the rise of “AI slop,” low-quality AI-generated outputs that appear acceptable on the surface but fail under real operational conditions.
“We believe AI adoption needs more honesty, more discipline, and far more operational accountability,” Ravi said. “The future belongs to organizations that can scale AI without losing security, comprehension, governance, and trust in the process.”
Raven, Andie, and AIRTaaS are part of GSD (Giggso Security Domain), Giggso’s enterprise architecture for governing AI systems, coding workflows, observability, orchestration, reasoning, and AI operational security across the enterprise.
More information is available at Giggso
About Author
Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
Press Release
Caladan Launches API Liquidity: Institutional Access to Aggregated Digital Asset Liquidity Across 100+ Tokens
Singapore, May 26th, 2026, ZEX PR WIRE — Institutional counterparties can now access executable streaming prices and RFQ liquidity for spot and perpetuals on 100+ digital assets through the Caladan API, launched today by Caladan, the largest Asia-headquartered market maker for digital assets.
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Built on nearly a decade of active trading, Caladan continuously aggregates pricing and depth from 20+ on-chain protocols, 47+ centralised exchange integrations, and bilateral relationships. The result is a single pricing feed that delivers tighter spreads, higher fill rates, and full depth on long-tail tokens.
“Fragmentation is the defining liquidity challenge in digital assets today. A single exchange, a single counterparty, or a single OTC desk will always have an incomplete view of price and depth. We have spent nine years building the infrastructure to see the whole market simultaneously, and API Liquidity makes that infrastructure available to institutional participants through a single API connection.” – John Gu, CEO, Caladan
Why aggregation produces better pricing
Digital asset liquidity is highly fragmented across centralised exchanges, decentralised protocols, regional venues, bilateral broker-dealers, and OTC desks. Caladan’s sourcing model is the commercial differentiator. The firm facilitates over $170 billion in annual trading volume across more than 100 assets, which means its pricing engine is continuously calibrated against a wider range of market signals. The more heterogeneous the sourcing — on-chain, off-chain, bilateral, and platform-routed simultaneously — the tighter the spread and the deeper the available size at any given price point.
The broadest token coverage of any market maker
API Liquidity provides access to the top 100 tokens — the widest token coverage available from any market maker globally. Coverage spans spot and perpetuals.
For institutional participants managing diversified digital asset portfolios or building crypto-embedded products, this breadth eliminates the need to maintain multiple liquidity provider relationships to cover the full token universe.
Flexible connectivity and settlement
API Liquidity is designed for immediate integration with minimal development overhead. Counterparties can connect through the channel that fits their existing workflow:
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Direct API: Native FIX connectivity (4.2, 4.4, 5.0) for firms that prefer a direct bilateral connection
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Platform partners: Desks already connected to Talos, Finery Markets, or CrossX can access Caladan liquidity with no additional integration work
Settlement is handled through institutional partners, with options for fiat and stablecoins:
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Hidden Road and BitGo Go Network for custodial settlement
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Customers Bank CUBIX for fiat settlement in USD
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USDT and USDC settlement available directly
Competitive credit and margin terms are available for qualifying counterparties. Fiat currency pairs including EUR and JPY are in development, with additional currencies in the pipeline.
About Caladan
Caladan is Asia’s largest digital asset market maker, headquartered in Singapore with teams across seven global offices. Since 2017, Caladan has facilitated over $170 billion in annual trading volume, operating across 65+ exchanges worldwide. The firm provides market-making, OTC trading, DeFi expertise, and investments to institutional participants globally.
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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.
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