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Platon Aims To Become The Public Infrastructute Of Privacy Computing To Open Up Business Prospects For The Crypto Space

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5 years ago

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In the Information Age, Data Becomes a New Factor of Productivity

In economics, factors of production, also known as production inputs, are essential resources for the production of goods and services. In his epochal work “Principles of Economics”, famous British economist Marshall put forward the theory of four factors of production — land, labor, capital and entrepreneurial talent. National income (NI) is the reward of four factors, and that is, national income (NI) = labor wage (w) + land rent (r) + capital interest (i) + operating profit (π). This “four-in-one formula” sums up the core of western economic production theory and distribution theory, which has been widely accepted for more than a century.

However, factors of production are a historical category that evolves with the development of economy and society. The birth and development of the Internet has changed the mode of production, life and consumption, and it promoted many important and profound changes, and played an increasingly important role in economic development, social life and national governance. The full exploitation and effective utilization of all kinds of data has raised production efficiency to an unprecedented level. Data has become an indispensable factor in economic activities and a new generation of production factors after land, energy, population and food.

Table – Production Factors at Different Stages

Privacy Brings Data Dilemma and MPC Realizes Data Collaborative Computing

Nowadays, people have already extended their social activities to the network space. Every day, people contribute data continuously to the network space. A large amount of data is collected, calculated, analyzed, excavated and this goes beyond the original data level of information value.

However, because of the plain text nature of the data, the owner loses ownership of the data once the data is granted to others for use. Therefore, to ensure the privacy protection of data, a huge amount of data managed by enterprises cannot be exchanged and co-calculated with the data held by other enterprises, which is why a large number of data cannot generate value.

The emergence of privacy computing ends this dilemma. Yao Qizhi, a member of the Chinese National Academy of Sciences, proposed secure multi-party computing (MPC) in 1982. In a nutshell, participants have to enter information to calculate an agreed function. In addition to the accuracy of the calculations, they must also protect the privacy of each participant’s input data. Specifically, there are now n participants, each of whom, xi, is aware of the xi they entered, who together calculate a pre-agreed function f (x1 ,…, xn) = y. In this way, all participants will get the final y value, but they will not be able to know the specific data entered by the other participants. Thus, with local data not aggregated and privacy not divulged, each party can still achieve a common desired result by performing the operations of the given logic.

Privacy computing opens up huge business prospects for the digital world (Crypto Space)

Bitcoin’s pioneering combination of virtual currencies and peer-to-peer payment systems open the door to decentralization. With the introduction of intelligent contract function, Ethernet has greatly improved the scalability of blockchain, and all kinds of applications can be deployed on blockchain. Because of these characteristics, early public blockchain networks such as Bitcoin and Ethernet have been developed, attracting a large number of blockchain and encryption enthusiasts in the world, and many traditional institutions have been entering the area of blockchain, exploring various possibilities of decentralization.

The combination of privacy computing and blockchain is expected to put data ownership back in the hands of data producers, meaning that vast amounts of data can be counted without affecting privacy and ownership, so that the owners can profit and data can burst out with greater value. Therefore, the blockchain project based on privacy calculation is naturally suitable for the commercial practice in the fields of financial, medical, scientific research, government affairs, and logistics and so on.

“Operator” PlatON network for blockchain data

PlatON, the representative project of the combination of privacy computing and blockchain currently, is based on the basic attribute of blockchain and is supported by privacy computing network, and provides the next generation Internet infrastructure protocol with the core characteristics of “computing interoperation”. PlatON’s vision is to become the public infrastructure for privacy computing of the next generation, publishing privacy computing algorithms through contracts, and implementing MPC protocols with data providers and computing nodes for privacy protection requirements, so as to realize cooperative computing of data. PlatON, designed to price data flows, is all about computing and data, which is the most fundamental part of future human production. PlatON can achieve large-scale application landing and commercial scenario implementation:

For example:

I. Build a wider credit collection network. The public chain that provides private computing can provide user with customizable computing logic template and multi-party access mode, and in the case that the access party’s data does not need to be collected and shared, only the credit inquiry results are output to the demander, and the original data can be encrypted and stored in the blockchain system to meet all kinds of audit needs.

II. Supply chain financial infrastructure. The public chain of private computing is based on blockchain technology and cryptography algorithm, which can provide a platform solution for supply chain finance to digitally identify, process and transfer assets. Construct a new financial financing model of supply chain in which the information of the upstream and downstream enterprises can be shared symmetrically, the credit value of the core enterprises can be transmitted, the business tickets can be split and the risk can be controlled, and provide convenient data traceability for the supervision and enhance the service efficiency of the industry as a whole.

To build the public infrastructure for the digital age, PlatON continuously optimizes technology, iterates the underlying infrastructure, and breaks through the “impossible triangle” in terms of performance. “Impossible triangle” means that it is difficult to achieve both a good “decentralization” and a good “security” of the system in a blockchain and a high “transaction processing performance” at the same time. The most well-known blockchain projects in the industry are Bitcoin, Ethernet, and EOS. At present, using native Token transfer performance test method and EOS under the same testing conditions, PlatON has achieved a comprehensive performance leader in the quasi-real environment, and will continue to focus on the data field and accelerate the construction of data market.

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Alex Jacob

Alex Jacob is a literature author. He was born in Chicago. Alex passion is writing news articles. He writes number of articles and published it.

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Press Release

Giggso Introduces Raven, Andie, and AIRTaaS to Help Enterprises Bring Discipline, Reasoning, and Security to AI Adoption

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5 hours ago

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May 26, 2026

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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.

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

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Cloud PR Wire

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Press Release

Caladan Launches API Liquidity: Institutional Access to Aggregated Digital Asset Liquidity Across 100+ Tokens

Published

7 hours ago

on

May 26, 2026

By

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.

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:

  • Direct API: Native FIX connectivity (4.2, 4.4, 5.0) for firms that prefer a direct bilateral connection

  • 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:

  • Hidden Road and BitGo Go Network for custodial settlement

  • Customers Bank CUBIX for fiat settlement in USD

  • 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.

About Author

Cloud PR Wire

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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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Press Release

Caladan Launches API Liquidity: Institutional Access to Aggregated Digital Asset Liquidity Across 100+ Tokens

Published

7 hours ago

on

May 26, 2026

By

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.

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:

  • Direct API: Native FIX connectivity (4.2, 4.4, 5.0) for firms that prefer a direct bilateral connection

  • 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:

  • Hidden Road and BitGo Go Network for custodial settlement

  • Customers Bank CUBIX for fiat settlement in USD

  • 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.

About Author

Cloud PR Wire

See author's posts

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.

Continue Reading

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