Ready

Can decentralized finance (DeFi) on Bitcoin finally deliver the automation that investors have been waiting for? Bitflow, a decentralized Bitcoin exchange, seems to think so. Today, the company announced the launch of Automated Dollar-Cost Averaging (DCA) for Bitcoin and Runes tokens on Stacks, marking a significant step toward AI-powered DeFi infrastructure. The introduction of Automated DCA allows users to accumulate Bitcoin (BTC) and popular Runes tokens without relinquishing custody of their assets. By leveraging Bitflow Keepers, the platform’s smart automation engine, this new feature brings recurring, trustless investment strategies directly onto the Stacks ecosystem. The development could signal a turning point for Bitcoin DeFi, long overshadowed by Ethereum’s more robust ecosystem. Unlocking Automation for Bitcoin DeFi Automated DCA isn’t just about convenience—it addresses a fundamental challenge in crypto investing: timing the market. With this feature, users can automate purchases of BTC, stablecoins, STX, sBTC, SIP-10 tokens, and top Runes assets like $DOG (DOG•GO•TO•THE•MOON), Stacks’ leading memecoin. The goal? To simplify long-term crypto accumulation and reduce reliance on manual trading. "Bitcoin DeFi is finally unlocking real automation with Automated DCA. Utilizing Bitflow Keepers, this powerful new feature enables users to program their BTC investments in a fully decentralized and trustless manner," said Dylan Floyd, Bitflow Co-Founder and Lead Developer. For the first time on Stacks, DeFi users can execute systematic investment strategies while retaining full control over their assets. All transactions occur on-chain, fully non-custodial, eliminating reliance on third-party intermediaries—a key principle in the decentralized finance ethos. The Broader Implications for Bitcoin’s Role in DeFi This move could redefine how Bitcoin functions within the DeFi landscape. Traditionally seen as a static store of value, Bitcoin’s role is evolving into that of a productive asset. Bitflow’s automation framework enhances this utility by allowing users to implement profit-taking strategies and recurring purchases based on predefined conditions—without needing to time the market manually. Moreover, the support for Runes and SIP-10 tokens broadens the utility of the Stacks Layer 2 (L2) network, positioning it as a key player in Bitcoin-native finance. The introduction of AI-driven automation could attract users looking for sophisticated tools typically associated with Ethereum’s DeFi offerings. Looking Ahead: AI and Cross-Layer Integration Bitflow’s roadmap for DeFi automation doesn’t end here. The company plans to introduce automated yield strategies that will optimize BTC-based yield farming without manual intervention. These strategies aim to unlock new avenues for generating returns on Bitcoin holdings, advancing the asset’s role beyond passive investment. Additionally, upcoming features like market-triggered swaps will enable users to execute trades automatically based on price trends and volatility indicators. Perhaps most significantly, Bitflow is working on facilitating cross-layer asset flows between Bitcoin’s Layer 1 and Stacks Layer 2. Such integration would improve liquidity efficiency and enable seamless movement of BTC-based assets across layers, enhancing the scalability and accessibility of Bitcoin DeFi. Final Thoughts: Is Bitcoin DeFi Finally Catching Up? The launch of Bitflow’s Automated DCA feature could represent a critical inflection point for Bitcoin-native finance. By bringing AI-powered, non-custodial automation tools to the Stacks ecosystem, Bitflow is challenging the perception that Bitcoin’s utility is limited to being a store of value. While Ethereum continues to dominate the DeFi conversation, Bitflow’s efforts may help Bitcoin close the gap by introducing more accessible, automated financial strategies. As Bitcoin continues to establish itself as a yield-generating asset, innovations like Automated DCA might pave the way for a more active, productive role in the decentralized economy. The question now is whether users and developers will embrace this shift. If they do, Bitcoin could finally become more than digital gold—it could become the foundation for a truly decentralized, automated financial future. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Can decentralized finance (DeFi) on Bitcoin finally deliver the automation that investors have been waiting for? Bitflow , a decentralized Bitcoin exchange, seems to think so. Today, the company announced the launch of Automated Dollar-Cost Averaging (DCA) for Bitcoin and Runes tokens on Stacks, marking a significant step toward AI-powered DeFi infrastructure. Bitflow The introduction of Automated DCA allows users to accumulate Bitcoin (BTC) and popular Runes tokens without relinquishing custody of their assets. By leveraging Bitflow Keepers, the platform’s smart automation engine, this new feature brings recurring, trustless investment strategies directly onto the Stacks ecosystem. The development could signal a turning point for Bitcoin DeFi, long overshadowed by Ethereum’s more robust ecosystem. Unlocking Automation for Bitcoin DeFi Unlocking Automation for Bitcoin DeFi Automated DCA isn’t just about convenience—it addresses a fundamental challenge in crypto investing: timing the market. With this feature, users can automate purchases of BTC, stablecoins, STX, sBTC, SIP-10 tokens, and top Runes assets like $DOG (DOG•GO•TO•THE•MOON), Stacks’ leading memecoin. The goal? To simplify long-term crypto accumulation and reduce reliance on manual trading. "Bitcoin DeFi is finally unlocking real automation with Automated DCA. Utilizing Bitflow Keepers, this powerful new feature enables users to program their BTC investments in a fully decentralized and trustless manner," said Dylan Floyd, Bitflow Co-Founder and Lead Developer. For the first time on Stacks, DeFi users can execute systematic investment strategies while retaining full control over their assets. All transactions occur on-chain, fully non-custodial, eliminating reliance on third-party intermediaries—a key principle in the decentralized finance ethos. The Broader Implications for Bitcoin’s Role in DeFi The Broader Implications for Bitcoin’s Role in DeFi This move could redefine how Bitcoin functions within the DeFi landscape. Traditionally seen as a static store of value, Bitcoin’s role is evolving into that of a productive asset. Bitflow’s automation framework enhances this utility by allowing users to implement profit-taking strategies and recurring purchases based on predefined conditions—without needing to time the market manually. Moreover, the support for Runes and SIP-10 tokens broadens the utility of the Stacks Layer 2 (L2) network, positioning it as a key player in Bitcoin-native finance. The introduction of AI-driven automation could attract users looking for sophisticated tools typically associated with Ethereum’s DeFi offerings. Looking Ahead: AI and Cross-Layer Integration Looking Ahead: AI and Cross-Layer Integration Bitflow’s roadmap for DeFi automation doesn’t end here. The company plans to introduce automated yield strategies that will optimize BTC-based yield farming without manual intervention. These strategies aim to unlock new avenues for generating returns on Bitcoin holdings, advancing the asset’s role beyond passive investment. Additionally, upcoming features like market-triggered swaps will enable users to execute trades automatically based on price trends and volatility indicators. Perhaps most significantly, Bitflow is working on facilitating cross-layer asset flows between Bitcoin’s Layer 1 and Stacks Layer 2. Such integration would improve liquidity efficiency and enable seamless movement of BTC-based assets across layers, enhancing the scalability and accessibility of Bitcoin DeFi. Final Thoughts: Is Bitcoin DeFi Finally Catching Up? Final Thoughts: Is Bitcoin DeFi Finally Catching Up? The launch of Bitflow’s Automated DCA feature could represent a critical inflection point for Bitcoin-native finance. By bringing AI-powered, non-custodial automation tools to the Stacks ecosystem, Bitflow is challenging the perception that Bitcoin’s utility is limited to being a store of value. While Ethereum continues to dominate the DeFi conversation, Bitflow’s efforts may help Bitcoin close the gap by introducing more accessible, automated financial strategies. As Bitcoin continues to establish itself as a yield-generating asset, innovations like Automated DCA might pave the way for a more active, productive role in the decentralized economy. The question now is whether users and developers will embrace this shift. If they do, Bitcoin could finally become more than digital gold—it could become the foundation for a truly decentralized, automated financial future. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

Is Bitcoin DeFi Ready for Full Automation? Bitflow’s New Automated DCA Feature Suggests It Might Be

هل Bitcoin DeFi جاهز للأتمتة الكاملة؟ تشير ميزة DCA الآلية الجديدة في Bitflow إلى أنه قد يكون كذلك

¿Está Bitcoin DeFi lista para una automatización total? La nueva función DCA automatizada de Bitflow sugiere que podría serlo

האם Bitcoin DeFi מוכן לאוטומציה מלאה? תכונת ה-DCA האוטומטית החדשה של Bitflow מציעה שזה יכול להיות

Bitcoin DeFi è pronto per l'automazione completa? La nuova funzionalità DCA automatizzata di Bitflow suggerisce che potrebbe esserlo

ビットコインDeFiは完全自動化の準備ができているか？Bitflowの新しい自動DCA機能はそれが可能であることを示唆している

Bitcoin DeFi მზად არის სრული ავტომატიზაციისთვის? Bitflow-ის ახალი ავტომატური DCA ფუნქცია ვარაუდობს, რომ ეს შეიძლება იყოს

Adakah Bitcoin DeFi Bersedia untuk Automasi Penuh? Ciri DCA Automatik Baharu Bitflow Mencadangkan Ia Mungkin

Este Bitcoin DeFi gata pentru automatizare completă? Noua funcție automată DCA a Bitflow sugerează că ar putea fi

Да ли је Битцоин ДеФи спреман за потпуну аутоматизацију? Нова аутоматизована функција ДЦА Битфлов-а сугерише да би то могло бити

Handa na ba ang Bitcoin DeFi para sa Buong Automation? Ang Bagong Awtomatikong DCA na Feature ng Bitflow ay Iminumungkahi na Maaaring Ito

Ngaba i-Bitcoin DeFi ilungele ukuZitshintsha ngokupheleleyo? Inqaku elitsha le-Bitflow elizenzekelayo le-DCA licebisa ukuba inokuba

比特币 DeFi 是否已准备好实现完全自动化？Bitflow 的新自动化 DCA 功能表明情况可能如此

When people think of generative AI, many envision it working as part of a “system of engagement” — a customer service agent, a supply chain management tool, or a way to intelligently interact with and search an organization’s PDFs and other proprietary data. That’s an accurate view – for the next year or two, applications that intelligently create content by leveraging large language models (LLMs) will remain a primary AI focus for enterprises. But consider this: Most of the code written at enterprises sits within business processes — systems like inventory planning, which sit between the engagement layer and the more rigid systems of record (an organization’s data, etc.) How will GenAI benefit that layer? How can an organization improve its business processes with this pervasive technology? Agentic AI is the answer. While AI agents are built to do specific tasks or automate specific, often repetitive tasks (like updating your calendar), they generally require human input. Agentic AI is all about autonomy (think self-driving cars), employing a system of agents to constantly adapt to dynamic environments and independently create, execute, and optimize results. When agentic AI is applied to business process workflows, it can replace fragile, static business processes with dynamic, context-aware automation systems. Let’s take a look at why integrating AI agents into enterprise architectures marks a transformative leap in the way organizations approach automation and business processes, and what kind of platform is required to support these systems of automation. What Agents Are Doing Now When you provide an agent with context, the agent then feeds that context to an LLM and asks it to complete and respond to it. AI agents can also use capabilities to complete tasks on behalf of users. These AI agents can perform several key functions guided by instructions and information derived from context: Tool use — The agent uses external functions, APIs, or tools to extend its capabilities and perform specific tasks. This can include calling predefined functions or interfacing with external services (like making web requests using cURL or accessing RESTful APIs) to obtain context or execute actions beyond its inherent functionalities. Decision-making — The agent evaluates available information and selects the most appropriate action to achieve its goals. This involves analyzing context, weighing possible outcomes, and choosing a course of action that aligns with the desired objectives. Planning — The agent formulates a sequence of actions or strategies to achieve a specific goal. Reasoning — The agent analyzes the available context, draws conclusions, predicts outcomes of actions, and makes informed decisions about the optimal steps to take to reach the desired outcome. These latter kinds of functions – decision-making, planning, and reasoning – often involve multiple agents working together toward a goal. The agents could seek to refine generated code for correctness, debate whether an agentic decision is biased, or plan the use of other agentic capabilities to complete a task. Orchestrating an Agentic Network Models that power networks of agents are essentially stateless functions that take context as an input and output a response, so some kind of framework is necessary to orchestrate them. Part of that orchestration could be simple refinements (the model requests more information). This might sound analogous to retrieval-augmented generation (RAG) – and it should, because RAG is essentially a simplified form of agent architecture: It provides the model with a single tool that gets it additional information, often from a vector database. But multiagentic model frameworks take this further; they broker requests for additional information or provide a response that’s designed to be fed to another agent for refinements. One agent could, say, write some Python, while another then reviews it. Or an agent could express a goal or idea, and then a second agent’s job could be to break that up into a set of tasks or review the idea to find problems that the first agent can review, and then refine the idea. Your results start to get better and better. OK, but How Do I Build Agentic AI? In the near future, a lot of software engineers will become agentic process authors. They’ll build these processes by mixing and matching components: models, user input, goals – and critical business services. An example of one of these components is the stock in an inventory management system. What if you connected that system to an agent that could help optimize inventory levels during the holiday season? With the help of another agent who has done some historical inventory level analysis, you could ensure that there is just enough inventory to meet seasonal demand yet leave little inventory after the holiday rush. This might disappoint fervent after-Christmas sale shoppers, but it would also help prevent retailers from selling their wares at a loss. But how will developers build these systems? Agentic processes can, of course, be expressed with code, but it also helps to visualize them as “agentic flows” – one agent’s output becomes the input of another agent, and so on. Tools available now are already providing a lot of value in this effort to simplify building agentic systems. One such solution is Langflow, a visual, low-code builder for creating agentic AI applications and complex AI workflows by dragging and dropping different components, without the need for much coding. Langflow enables developers to define anything as a tool, including components like a prompt, data source, model, APIs, tools, or any other agents. We’ve recently seen significant demand for building “flows” with agents, as developers are creating a lot of applications that include several multiagent capabilities: Agents are the most popular type of component that developers are inserting into flows with Langflow. Wrapping up: From copilot to Pilot Agentic workflows bring together enterprise data, AI, and APIs, forming systems of automation that empower domain experts to scale their abilities and make enterprises work better through AI. Integrating AI agents into enterprise architectures marks a big leap in how organizations approach automation and business processes. These agents, empowered by LLMs and agentic frameworks, transcend traditional boundaries by seamlessly operating across processes, workflows, and code. Adopting agentic workflows promises to enhance efficiency, scalability, and responsiveness across business operations. They’ll manage entire workflows, handle complex tasks with greater adaptability, and improve customer experiences by providing more personalized and timely interactions. As automation becomes embedded in enterprise systems, AI copilots will graduate to pilots, and organizations that employ agentic AI will be better positioned to innovate, compete, and deliver value. For more details on agentic AI, read the free whitepaper, “Systems of Automation: The Future of Enterprise Architecture Is Agentic.” And check out this page to learn more about Langflow. Written by Ed Anuff, chief product officer, DataStax When people think of generative AI, many envision it working as part of a “system of engagement” — a customer service agent, a supply chain management tool, or a way to intelligently interact with and search an organization’s PDFs and other proprietary data. That’s an accurate view – for the next year or two, applications that intelligently create content by leveraging large language models (LLMs) will remain a primary AI focus for enterprises. leveraging large language models (LLMs) leveraging large language models (LLMs) But consider this: Most of the code written at enterprises sits within business processes — systems like inventory planning, which sit between the engagement layer and the more rigid systems of record (an organization’s data, etc.) How will GenAI benefit that layer? How can an organization improve its business processes with this pervasive technology? Agentic AI is the answer. While AI agents are built to do specific tasks or automate specific, often repetitive tasks (like updating your calendar), they generally require human input. Agentic AI is all about autonomy (think self-driving cars), employing a system of agents to constantly adapt to dynamic environments and independently create, execute, and optimize results. When agentic AI is applied to business process workflows, it can replace fragile, static business processes with dynamic, context-aware automation systems. Let’s take a look at why integrating AI agents into enterprise architectures marks a transformative leap in the way organizations approach automation and business processes, and what kind of platform is required to support these systems of automation. What Agents Are Doing Now When you provide an agent with context, the agent then feeds that context to an LLM and asks it to complete and respond to it. AI agents can also use capabilities to complete tasks on behalf of users. These AI agents can perform several key functions guided by instructions and information derived from context: Tool use — The agent uses external functions, APIs, or tools to extend its capabilities and perform specific tasks. This can include calling predefined functions or interfacing with external services (like making web requests using cURL or accessing RESTful APIs) to obtain context or execute actions beyond its inherent functionalities. Decision-making — The agent evaluates available information and selects the most appropriate action to achieve its goals. This involves analyzing context, weighing possible outcomes, and choosing a course of action that aligns with the desired objectives. Decision-making — Planning — The agent formulates a sequence of actions or strategies to achieve a specific goal. Planning — Reasoning — The agent analyzes the available context, draws conclusions, predicts outcomes of actions, and makes informed decisions about the optimal steps to take to reach the desired outcome. Reasoning — These latter kinds of functions – decision-making, planning, and reasoning – often involve multiple agents working together toward a goal. The agents could seek to refine generated code for correctness, debate whether an agentic decision is biased, or plan the use of other agentic capabilities to complete a task. Orchestrating an Agentic Network Models that power networks of agents are essentially stateless functions that take context as an input and output a response, so some kind of framework is necessary to orchestrate them. Part of that orchestration could be simple refinements (the model requests more information). This might sound analogous to retrieval-augmented generation (RAG) – and it should, because RAG is essentially a simplified form of agent architecture: It provides the model with a single tool that gets it additional information, often from a vector database. retrieval-augmented generation (RAG) retrieval-augmented generation (RAG) But multiagentic model frameworks take this further; they broker requests for additional information or provide a response that’s designed to be fed to another agent for refinements. One agent could, say, write some Python, while another then reviews it. Or an agent could express a goal or idea, and then a second agent’s job could be to break that up into a set of tasks or review the idea to find problems that the first agent can review, and then refine the idea. Your results start to get better and better. OK, but How Do I Build Agentic AI? In the near future, a lot of software engineers will become agentic process authors. They’ll build these processes by mixing and matching components: models, user input, goals – and critical business services. An example of one of these components is the stock in an inventory management system. What if you connected that system to an agent that could help optimize inventory levels during the holiday season? With the help of another agent who has done some historical inventory level analysis, you could ensure that there is just enough inventory to meet seasonal demand yet leave little inventory after the holiday rush. This might disappoint fervent after-Christmas sale shoppers, but it would also help prevent retailers from selling their wares at a loss. But how will developers build these systems? Agentic processes can, of course, be expressed with code, but it also helps to visualize them as “agentic flows” – one agent’s output becomes the input of another agent, and so on. Tools available now are already providing a lot of value in this effort to simplify building agentic systems. One such solution is Langflow , a visual, low-code builder for creating agentic AI applications and complex AI workflows by dragging and dropping different components, without the need for much coding. Langflow Langflow Langflow enables developers to define anything as a tool, including components like a prompt, data source, model, APIs, tools, or any other agents. We’ve recently seen significant demand for building “flows” with agents, as developers are creating a lot of applications that include several multiagent capabilities: Agents are the most popular type of component that developers are inserting into flows with Langflow. Wrapping up: From copilot to Pilot Agentic workflows bring together enterprise data, AI, and APIs, forming systems of automation that empower domain experts to scale their abilities and make enterprises work better through AI. Integrating AI agents into enterprise architectures marks a big leap in how organizations approach automation and business processes. These agents, empowered by LLMs and agentic frameworks, transcend traditional boundaries by seamlessly operating across processes, workflows, and code. Adopting agentic workflows promises to enhance efficiency, scalability, and responsiveness across business operations. They’ll manage entire workflows, handle complex tasks with greater adaptability, and improve customer experiences by providing more personalized and timely interactions. As automation becomes embedded in enterprise systems, AI copilots will graduate to pilots, and organizations that employ agentic AI will be better positioned to innovate, compete, and deliver value. For more details on agentic AI, read the free whitepaper, “Systems of Automation: The Future of Enterprise Architecture Is Agentic.” And check out this page to learn more about Langflow. For more details on agentic AI, read the free whitepaper, “ Systems of Automation: The Future of Enterprise Architecture Is Agentic. ” And check out this page to learn more about Langflow . Systems of Automation: The Future of Enterprise Architecture Is Agentic. Systems of Automation: The Future of Enterprise Architecture Is Agentic. this page this page to learn more about Langflow Written by Ed Anuff, chief product officer, DataStax Written by Ed Anuff, chief product officer, DataStax

AI Agents: How They're Getting Ready to Blow Up the Business Process Layer

وكلاء الذكاء الاصطناعي: كيف يستعدون لتفجير طبقة العمليات التجارية

Agents d'IA: com s'estan preparant per explotar la capa de processos empresarials

AI-agenter: Sådan bliver de klar til at sprænge forretningsproceslaget

Agentes de IA: cómo se están preparando para hacer estallar la capa de procesos de negocios

Agents IA : comment ils se préparent à faire exploser la couche des processus métier

AI エージェント: ビジネス プロセス層を爆破する準備

AI agentai: kaip jie ruošiasi susprogdinti verslo procesų sluoksnį

Agenci AI: Jak przygotowują się do wysadzenia warstwy procesów biznesowych

Agenti AI: Ako sa pripravujú vyhodiť do vzduchu vrstvu obchodných procesov

AI Agents: ከመይ ጌሮም ነቲ ናይ ቢዝነስ መስርሕ ንጣብ ንምፍንፋሕ ይዳለዉ ኣለዉ።

AI agentlari: ular biznes-jarayon qatlamini portlatish uchun qanday tayyorlanishmoqda

Ama-AI Agents: Balungela Kanjani Ukuqhumisa Isendlalelo Senqubo Yebhizinisi

Navigating Digital Classrooms As Educators—Are We Ready to Adapt?

We now find ourselves fully immersed in the age of Trump 2.0, and it’s fair to say that waters have been choppier than usual. As markets attempt to anticipate the famously unpredictable President’s every move, every statement has become a potential key event on Wall Street. Although Trump’s America First agenda, which appears to be heavily focused on deregulation, the cutting of international aid, and other expenses deemed unnecessary by the returning President, appears to be heavily growth-focused, the widespread uncertainty surrounding his every utterance is leading to widespread volatility. Despite this, the S&P 500 climbed 4.61% between Trump’s resounding election win on November 5, 2024, and his inauguration on January 21, 2025, the recent announcement of 25% tariffs on Canada and Mexico, as well as an additional 10% on Chinese imports has seen Wall Street struggle for momentum in the early days of the President’s second term. Unpicking The Fallout from Trump’s Tariffs One notable case of global market volatility came in the form of Trump’s non-announcement and subsequent announcement of trading tariffs in the early days of his White House return. Markets had initially calmed after the President didn’t announce the tariffs promised during his inauguration, only for jitters to resume when he suggested that they would be introduced on February 1, 2025. Even in the hours leading up to the imposition of the tariffs, a false report that a delay until March 1, 2025, caused more market confusion before being quickly denied by Trump’s press secretary. The uncertainty until the end as to whether Trump would follow up on his tariff threats saw the S&P 500 dip 1.6% in the early hours of trading following the announcement despite the threat of their imposition being long factored into markets. Tariffs can carry a long-term impact on market volatility due to the additional taxes that are required on imports, the threat of retaliatory tariffs as part of a larger international trade war, and the prospect of companies seeking alternative supply chains to ease the economic impact. Markets can also be confounded by the impact of inflation, which may occur if US importers pass on higher supply chain costs as a result of tariffs on to consumers. This would rapidly increase the cost of living and damage consumer spending power. This, coupled with Trump’s proposed mass deportations, could undermine American industry, shrinking labor pools and pushing more upward pressure on prices. While these events are speculative, they will see more institutions focus their attention on reacting quickly to emerging market data surrounding CPI and US labor insights, which paves the way for more dramatic market responses to confounding datasets. What Will Happen to US Financial Markets? Macro strategy risk taker Russel Matthews has suggested that markets will become more erratic, random, and chaotic in the age of Trump 2.0, and this should be a core factor to keep in mind when it comes to risk management. While this could pave the way for institutions to adopt a more cautious, less greedy approach to profit-taking, we’re set to see more nuanced strategies among investors to overcome the threat of volatility. Likewise, J.P. Morgan’s global investment strategy team has suggested a diversified approach to withstand the uncertainties that could occur during Trump’s second term, prioritizing a resilient portfolio to help achieve long-term financial goals. But is there really a tangible threat to the long-term progress of US financial markets? It’s worth noting that the first Trump administration posted a healthy 83% cumulative return for the S&P 500 between 2017 and 2020, with one drawdown of around 15% in 2018 and the pandemic crash of 35% in early 2020. This serves as a timely reminder that the stock market generally trends upward over time, regardless of who’s in the White House. However, it’s also worth noting that Trump’s control of the House of Representatives, Congress, and the Senate means that the returning President has far more room to enact his most ambitious policies this time with less scrutiny. “Over time - as markets adapt - the effects of Trump's policies may stabilize, depending on the success of their implementation and broader economic conditions,” explains Maxim Manturov, head of investment research at Freedom24. “For example, if tax breaks successfully stimulate growth without causing excessive inflation or trade wars to escalate into protracted conflicts negatively impacting global supply chains - investors may find that relative stability returns after initial spikes in volatility.” “Therefore, while short-term reactions may be dramatic following Trump's statements/actions, understanding how they translate into long-term trends becomes crucial for investors seeking to effectively mitigate risk in the face of continued uncertainty surrounding his presidency.” Opportunities in Deregulation Amid concerns over the impact of tariffs and trade wars, it’s easy to forget that Trump is attempting to instill a pro-growth outlook for US industries. The announcement of the SoftBank, OpenAI, and Oracle joint venture called ‘Stargate’ was unveiled by Trump and is an example of the United States’ bid to use deregulation to boost leadership in key areas like artificial intelligence. With the initial investment totaling $100 billion, with the aim to increase to at least $500 billion over the course of Trump’s term, we can expect the initiative to pave the way for AI stocks to build their global market dominance in a way that can support long-term growth on Wall Street. Trump’s controversial statement in December, promising that any person or company investing at least $1 billion into the US would receive fully expedited approvals and permits, including all environmental approvals, is another example of the President’s focus on market growth in a deregulation environment. Volatility to Remain We can be certain that higher levels of market volatility will remain throughout Trump’s second term, but the President’s growth-focused approach appears likely to uncover fresh investment opportunities for institutional and retail investors alike. Overall, the impact of Trump’s tariffs and subsequent trade wars may play a deciding role in the health of US markets, but Wall Street’s historical long-term growth should offer a sense of comfort to investors who could be caught up in short-term price shifts over the next four years. We now find ourselves fully immersed in the age of Trump 2.0, and it’s fair to say that waters have been choppier than usual. As markets attempt to anticipate the famously unpredictable President’s every move, every statement has become a potential key event on Wall Street. Although Trump’s America First agenda, which appears to be heavily focused on deregulation, the cutting of international aid, and other expenses deemed unnecessary by the returning President, appears to be heavily growth-focused, the widespread uncertainty surrounding his every utterance is leading to widespread volatility. Despite this, the S&P 500 climbed 4.61% between Trump’s resounding election win on November 5, 2024, and his inauguration on January 21, 2025, the recent announcement of 25% tariffs on Canada and Mexico, as well as an additional 10% on Chinese imports has seen Wall Street struggle for momentum in the early days of the President’s second term. Unpicking The Fallout from Trump’s Tariffs One notable case of global market volatility came in the form of Trump’s non-announcement and subsequent announcement of trading tariffs in the early days of his White House return. Markets had initially calmed after the President didn’t announce the tariffs promised during his inauguration, only for jitters to resume when he suggested that they would be introduced on February 1, 2025. Even in the hours leading up to the imposition of the tariffs, a false report that a delay until March 1, 2025, caused more market confusion before being quickly denied by Trump’s press secretary. The uncertainty until the end as to whether Trump would follow up on his tariff threats saw the S&P 500 dip 1.6% in the early hours of trading following the announcement despite the threat of their imposition being long factored into markets. S&P 500 dip 1.6% S&P 500 dip 1.6% Tariffs can carry a long-term impact on market volatility due to the additional taxes that are required on imports, the threat of retaliatory tariffs as part of a larger international trade war, and the prospect of companies seeking alternative supply chains to ease the economic impact. Markets can also be confounded by the impact of inflation, which may occur if US importers pass on higher supply chain costs as a result of tariffs on to consumers. This would rapidly increase the cost of living and damage consumer spending power. This, coupled with Trump’s proposed mass deportations, could undermine American industry, shrinking labor pools and pushing more upward pressure on prices . upward pressure on prices upward pressure on prices While these events are speculative, they will see more institutions focus their attention on reacting quickly to emerging market data surrounding CPI and US labor insights, which paves the way for more dramatic market responses to confounding datasets. What Will Happen to US Financial Markets? Macro strategy risk taker Russel Matthews has suggested that markets will become more erratic, random, and chaotic in the age of Trump 2.0, and this should be a core factor to keep in mind when it comes to risk management. While this could pave the way for institutions to adopt a more cautious, less greedy approach to profit-taking, we’re set to see more nuanced strategies among investors to overcome the threat of volatility. Likewise, J.P. Morgan’s global investment strategy team has suggested a diversified approach to withstand the uncertainties that could occur during Trump’s second term, prioritizing a resilient portfolio to help achieve long-term financial goals. But is there really a tangible threat to the long-term progress of US financial markets? It’s worth noting that the first Trump administration posted a healthy 83% cumulative return for the S&P 500 between 2017 and 2020, with one drawdown of around 15% in 2018 and the pandemic crash of 35% in early 2020. 83% cumulative return 83% cumulative return This serves as a timely reminder that the stock market generally trends upward over time, regardless of who’s in the White House. However, it’s also worth noting that Trump’s control of the House of Representatives, Congress, and the Senate means that the returning President has far more room to enact his most ambitious policies this time with less scrutiny. “Over time - as markets adapt - the effects of Trump's policies may stabilize, depending on the success of their implementation and broader economic conditions,” explains Maxim Manturov, head of investment research at Freedom24. “For example, if tax breaks successfully stimulate growth without causing excessive inflation or trade wars to escalate into protracted conflicts negatively impacting global supply chains - investors may find that relative stability returns after initial spikes in volatility.” “Therefore, while short-term reactions may be dramatic following Trump's statements/actions, understanding how they translate into long-term trends becomes crucial for investors seeking to effectively mitigate risk in the face of continued uncertainty surrounding his presidency.” Opportunities in Deregulation Amid concerns over the impact of tariffs and trade wars, it’s easy to forget that Trump is attempting to instill a pro-growth outlook for US industries. The announcement of the SoftBank, OpenAI, and Oracle joint venture called ‘Stargate’ was unveiled by Trump and is an example of the United States’ bid to use deregulation to boost leadership in key areas like artificial intelligence. With the initial investment totaling $100 billion , with the aim to increase to at least $500 billion over the course of Trump’s term, we can expect the initiative to pave the way for AI stocks to build their global market dominance in a way that can support long-term growth on Wall Street. investment totaling $100 billion investment totaling $100 billion Trump’s controversial statement in December, promising that any person or company investing at least $1 billion into the US would receive fully expedited approvals and permits, including all environmental approvals, is another example of the President’s focus on market growth in a deregulation environment. fully expedited approvals fully expedited approvals Volatility to Remain We can be certain that higher levels of market volatility will remain throughout Trump’s second term, but the President’s growth-focused approach appears likely to uncover fresh investment opportunities for institutional and retail investors alike. Overall, the impact of Trump’s tariffs and subsequent trade wars may play a deciding role in the health of US markets, but Wall Street’s historical long-term growth should offer a sense of comfort to investors who could be caught up in short-term price shifts over the next four years.

The Age of Volatility: Readying for the Unpredictability of Trump 2.0

Ерата на нестабилността: Подготовка за непредсказуемостта на Тръмп 2.0

The Age of Volatility: Připravujeme se na nepředvídatelnost Trumpa 2.0

Das Zeitalter der Volatilität: Vorbereitung auf die Unberechenbarkeit von Trump 2.0

L'era della volatilità: prepararsi all'imprevedibilità di Trump 2.0

Het tijdperk van volatiliteit: voorbereiden op de onvoorspelbaarheid van Trump 2.0

Era zmienności: przygotowanie na nieprzewidywalność Trumpa 2.0

Table of Links Abstract and I. Introduction II. Award Form and Content III. Electronic Signatures, Writing Requirement, and Authentication A. Is it possible for an Arbitrator o Digitally Sign an Arbitral Award
B. How could an Electronic Award be Considered to be "In Writing"
C. Could a Multisig E-Award be Duly Authenticated IV. Can Multisig Arbitration be Seen as an Autonomous Legal Order? V. Conclusion Appendix A: Multisig Transaction on Bitcoin Testnet Example Appendix B: Breakdown of BTC Stored in 2/3 Multisig Accounts V. CONCLUSION Multisig is an exciting technology that could change how merchants resolve cross-border disputes. The multisig protocol functions similar to escrow, but a key difference is that no one party, including the arbitrator, has sole possession of the funds. In a 2/3 multisig account, at least two parties must authorize a transfer by signing data with their respective private keys. This scheme provides a more efficient and trust-less mechanism for trading. However, there is some uncertainty whether or not multisig can be recognized as an arbitral award in some jurisdictions. The New York Convention requires awards to be “duly authenticated.” In civil law systems, the authentication of signatures is traditionally performed by public authorities or notaries. Moreover, the lex arbitri may impose additional form and document legalization requirements. If parties select the law of England as the seat of arbitration, they are free to agree on the form of an award under Section 52(1) of the Arbitration Act 1996. Through the concept of party autonomy, parties can restrict arbitrators from following guidelines on the content of awards and authorize the issuance of an award in electronic form. The parties should explicitly opt-out of a reasoned award as provided for under some arbitration rules. In addition, names and wallet addresses should be associated with parties at the time when the arbitration agreement is made. By doing this, an expert witness is able to certify the identity of parties and authenticate electronic signatures. Under ECA 2000, Section 7(1) (a), electronic signatures are admissible as evidence and under section 7(3), any person can certify the authenticity of such signatures. Multisig ought to be viewed as compatible within the international arbitration legal order, where the process is defined in an arbitration agreement and the raw transaction data is the actual arbitral award in an electronic form. Much in the same way courts have been able to adapt the law regarding paper contracts to the emergence of technologies like telegram, telex, fax, and e-mail, blockchain-based applications will be another method for entering into contractual relations. The technological novelty of multisig does not justify characterizing it as a separate legal order. Although multisig is compatible with the aims of international arbitration, in that it could provide a fast, cost-effective, and final method for resolving disputes privately, it is unlikely it will be widely used at the present. For one, there is a steep learning curve for merchants and their legal representatives to learn how to adequately use the technology. Secondly, arbitration institutions might be reluctant or slow to modernize rules to allow for conducting arbitration by electronic means. And finally, the multisig protocol is not intuitive enough for ordinary commercial use. Author:
(1) A.J. Santos, B.A. (UTSA), J.D. (STCL), Department of Private International Law, Ankara Yıldırım Beyazıt University, Faculty of Law (ajsantos@protonmail.com). This paper is available on arxiv under ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 4.0 INTERNATIONAL license. Table of Links Abstract and I. Introduction Abstract and I. Introduction II. Award Form and Content II. Award Form and Content III. Electronic Signatures, Writing Requirement, and Authentication A. Is it possible for an Arbitrator o Digitally Sign an Arbitral Award B. How could an Electronic Award be Considered to be "In Writing" C. Could a Multisig E-Award be Duly Authenticated A. Is it possible for an Arbitrator o Digitally Sign an Arbitral Award A. Is it possible for an Arbitrator o Digitally Sign an Arbitral Award B. How could an Electronic Award be Considered to be "In Writing" B. How could an Electronic Award be Considered to be "In Writing" C. Could a Multisig E-Award be Duly Authenticated C. Could a Multisig E-Award be Duly Authenticated IV. Can Multisig Arbitration be Seen as an Autonomous Legal Order? IV. Can Multisig Arbitration be Seen as an Autonomous Legal Order? V. Conclusion V. Conclusion Appendix A : Multisig Transaction on Bitcoin Testnet Example Appendix A Appendix A : Multisig Transaction on Bitcoin Testnet Example Appendix B : Breakdown of BTC Stored in 2/3 Multisig Accounts Appendix B Appendix B : Breakdown of BTC Stored in 2/3 Multisig Accounts V. CONCLUSION Multisig is an exciting technology that could change how merchants resolve cross-border disputes. The multisig protocol functions similar to escrow, but a key difference is that no one party, including the arbitrator, has sole possession of the funds. In a 2/3 multisig account, at least two parties must authorize a transfer by signing data with their respective private keys. This scheme provides a more efficient and trust-less mechanism for trading. However, there is some uncertainty whether or not multisig can be recognized as an arbitral award in some jurisdictions. The New York Convention requires awards to be “duly authenticated.” In civil law systems, the authentication of signatures is traditionally performed by public authorities or notaries. Moreover, the lex arbitri may impose additional form and document legalization requirements. If parties select the law of England as the seat of arbitration, they are free to agree on the form of an award under Section 52(1) of the Arbitration Act 1996. Through the concept of party autonomy, parties can restrict arbitrators from following guidelines on the content of awards and authorize the issuance of an award in electronic form. The parties should explicitly opt-out of a reasoned award as provided for under some arbitration rules. In addition, names and wallet addresses should be associated with parties at the time when the arbitration agreement is made. By doing this, an expert witness is able to certify the identity of parties and authenticate electronic signatures. Under ECA 2000, Section 7(1) (a), electronic signatures are admissible as evidence and under section 7(3), any person can certify the authenticity of such signatures. Multisig ought to be viewed as compatible within the international arbitration legal order, where the process is defined in an arbitration agreement and the raw transaction data is the actual arbitral award in an electronic form. Much in the same way courts have been able to adapt the law regarding paper contracts to the emergence of technologies like telegram, telex, fax, and e-mail, blockchain-based applications will be another method for entering into contractual relations. The technological novelty of multisig does not justify characterizing it as a separate legal order. Although multisig is compatible with the aims of international arbitration, in that it could provide a fast, cost-effective, and final method for resolving disputes privately, it is unlikely it will be widely used at the present. For one, there is a steep learning curve for merchants and their legal representatives to learn how to adequately use the technology. Secondly, arbitration institutions might be reluctant or slow to modernize rules to allow for conducting arbitration by electronic means. And finally, the multisig protocol is not intuitive enough for ordinary commercial use. Author: (1) A.J. Santos, B.A. (UTSA), J.D. (STCL), Department of Private International Law, Ankara Yıldırım Beyazıt University, Faculty of Law (ajsantos@protonmail.com). Author: Author: (1) A.J. Santos, B.A. (UTSA), J.D. (STCL), Department of Private International Law, Ankara Yıldırım Beyazıt University, Faculty of Law (ajsantos@protonmail.com). This paper is available on arxiv under ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 4.0 INTERNATIONAL license. This paper is available on arxiv under ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 4.0 INTERNATIONAL license. available on arxiv available on arxiv

Why Multisig Might Not Be Ready for Widespread Arbitration Use

One of the most interesting side effects of the TikTok ban saga was how it prompted everyone to pause and reflect on TikTok’s place in our culture and the profound influence it has had. Love it or hate it, TikTok has reshaped the way we consume content, catapulting creators to fame, defining cultural trends, and building communities around niche interests. Now, with TikTok’s future more stable, we can start to unpack its legacy—and one area stands out: the mainstream acceptance of TikTok Shop in the United States. TikTok turned out to be the platform to bring livestream commerce to an American audience at scale, and it has shown this isn’t just a passing trend or something that, as I wrote in 2023, is for niche audiences like baseball card sellers. For American companies, the message is clear—now is the time to harness this momentum and adapt to the future of connected, real-time shopping experiences. From Content to Commerce: The FOMO Effect in Livestream Shopping Livestream shopping taps into something deeply human: the desire to connect in real-time and the fear of missing out. TikTok’s success with its Shop feature demonstrated how content creators can build buzz, cultivate trust, and spark a buying frenzy within minutes of going live. As marketing executive Andrew Garson shared in a recent conversation, “For followers, livestream shopping is not just shopping—it’s an event, a shared experience that blends entertainment with exclusivity, and it’s another way to build connections online.” At the heart of livestream commerce is a simple yet powerful psychology: viewers tune in not just to buy products but to be part of a moment. When a creator recommends a product during a livestream, it doesn’t feel like a hard sell—it feels like a trusted friend sharing something they love. This kind of engagement transforms shopping from a solitary transaction into a communal experience, leveraging the same dynamics that make social media so engaging. For brands, this shift represents an extraordinary opportunity. By aligning with the right creators and speaking authentically to their audiences, businesses can build not just sales but deep, lasting relationships with their customers. Platforms like Whatnot and Loupe have embraced this approach, focusing on niche markets like collectibles and sports memorabilia, where passion runs high and trust drives every transaction. A Blueprint for Success: Authenticity Over Hard Sales Livestream shopping success isn’t about discounts or flashy promotions—it’s about authenticity. The brands and creators that thrive are those who understand their audience and focus on storytelling. Instead of simply presenting a product, they show how it fits into a customer’s life or solves a real problem. It’s marketing that feels personal, not transactional. It’s this authenticity that has allowed niche platforms like Whatnot to raise hundreds of millions to expand their live shopping capabilities, as they prove that the format works when it aligns with the needs of communities. The Future Is Now: Adapting to a New E-Commerce Era American brands are at a critical juncture as they approach engagement with what may be a new era in e-commerce. “This era of e-commerce will be known as one that prioritizes real-time interaction, community-driven trust, and shared experiences over traditional product displays,” shared marketing executive Andrew Garson, “The companies that succeed will be the ones that focus on building authentic connections and turning shopping into something fun, something that people want to be a part of.” Just where that will take place has become the biggest question as we enter 2025. As it appears increasingly likely the TikTok ban will remain in effect at the end of the month, the question has become which platform - existing or otherwise - will rise to meet the moment. The opportunity is here, waiting for someone to seize it. One of the most interesting side effects of the TikTok ban saga was how it prompted everyone to pause and reflect on TikTok’s place in our culture and the profound influence it has had. Love it or hate it, TikTok has reshaped the way we consume content, catapulting creators to fame, defining cultural trends, and building communities around niche interests. Now, with TikTok’s future more stable, we can start to unpack its legacy—and one area stands out: the mainstream acceptance of TikTok Shop in the United States . TikTok turned out to be the platform to bring livestream commerce to an American audience at scale, and it has shown this isn’t just a passing trend or something that, as I wrote in 2023, is for niche audiences like baseball card sellers . the mainstream acceptance of TikTok Shop in the United States for niche audiences like baseball card sellers For American companies, the message is clear—now is the time to harness this momentum and adapt to the future of connected, real-time shopping experiences. For American companies, the message is clear—now is the time to harness this momentum and adapt to the future of connected, real-time shopping experiences. From Content to Commerce: The FOMO Effect in Livestream Shopping From Content to Commerce: The FOMO Effect in Livestream Shopping Livestream shopping taps into something deeply human: the desire to connect in real-time and the fear of missing out. TikTok’s success with its Shop feature demonstrated how content creators can build buzz, cultivate trust, and spark a buying frenzy within minutes of going live. As marketing executive Andrew Garson shared in a recent conversation, “For followers, livestream shopping is not just shopping—it’s an event, a shared experience that blends entertainment with exclusivity, and it’s another way to build connections online.” marketing executive Andrew Garson marketing executive Andrew Garson At the heart of livestream commerce is a simple yet powerful psychology: viewers tune in not just to buy products but to be part of a moment. When a creator recommends a product during a livestream, it doesn’t feel like a hard sell—it feels like a trusted friend sharing something they love. This kind of engagement transforms shopping from a solitary transaction into a communal experience, leveraging the same dynamics that make social media so engaging. For brands, this shift represents an extraordinary opportunity. By aligning with the right creators and speaking authentically to their audiences, businesses can build not just sales but deep, lasting relationships with their customers. Platforms like Whatnot and Loupe have embraced this approach, focusing on niche markets like collectibles and sports memorabilia, where passion runs high and trust drives every transaction. A Blueprint for Success: Authenticity Over Hard Sales A Blueprint for Success: Authenticity Over Hard Sales Livestream shopping success isn’t about discounts or flashy promotions—it’s about authenticity. The brands and creators that thrive are those who understand their audience and focus on storytelling. Instead of simply presenting a product, they show how it fits into a customer’s life or solves a real problem. It’s marketing that feels personal, not transactional. It’s marketing that feels personal, not transactional. It’s this authenticity that has allowed niche platforms like Whatnot to raise hundreds of millions to expand their live shopping capabilities, as they prove that the format works when it aligns with the needs of communities. The Future Is Now: Adapting to a New E-Commerce Era American brands are at a critical juncture as they approach engagement with what may be a new era in e-commerce. “This era of e-commerce will be known as one that prioritizes real-time interaction, community-driven trust, and shared experiences over traditional product displays,” shared marketing executive Andrew Garson, “The companies that succeed will be the ones that focus on building authentic connections and turning shopping into something fun, something that people want to be a part of.” fun, Just where that will take place has become the biggest question as we enter 2025. As it appears increasingly likely the TikTok ban will remain in effect at the end of the month, the question has become which platform - existing or otherwise - will rise to meet the moment. The opportunity is here, waiting for someone to seize it. someone

Livestream Shopping: Ready to Explode in 2025

**Utrecht, Netherlands, January 9th, 2025/Chainwire/--**Nexera announces the launch of its Layer 1 blockchain purpose-built to meet the demands of institutional on-chain capital markets. By embedding compliance, interoperability, and scalability at its core, Nexera Chain delivers a comprehensive solution for real-world asset tokenization, bridging traditional and decentralized finance. This innovative blockchain integrates advanced AI-driven tools for compliance, enabling automated Know Your Customer (KYC), Know Your Business (KYB), Know Your Transaction (KYT), Anti-Money Laundering (AML), and Travel Rule enforcement. Nexera Chain ensures every participant and transaction adheres to global regulatory standards, providing institutions with the confidence to operate in a rapidly evolving regulatory landscape. Its design aligns with the principles of frameworks such as the EU’s Markets in Crypto-Assets (MiCA), offering a strong foundation for compliance without compromising efficiency or innovation. Nexera Chain stands out by addressing the long-standing challenges of blockchain adoption in institutional markets. Its compliance-first infrastructure eliminates the inefficiencies and security gaps caused by fragmented solutions, ensuring seamless integration of regulatory requirements. The blockchain’s omnichain interoperability enables fluid connections across public and private networks as well as legacy systems. This removes barriers to liquidity and data flow, paving the way for institutions to scale their tokenization efforts while maintaining the highest standards of compliance and security. The platform also simplifies tokenization for developers and enterprises with its developer-friendly APIs, SDKs, and white-label solutions. These tools streamline the process of bringing both tangible and digital assets on-chain, ensuring compliance across the entire asset lifecycle. Central to Nexera Chain is the ERC-7208 standard, a universal framework for managing tokenized assets, data, and identity across multiple networks. By standardizing these components, ERC-7208 supports consistent cross-chain activity and unlocks new opportunities for businesses to innovate within a scalable, interoperable environment. With over $1 billion in aggregate value represented across the Nexera ecosystem, including applications in tokenized real estate, art, carbon credit, GPUs, and more, Nexera Chain demonstrates its ability to deliver measurable value. Its unified infrastructure bridges the gap between traditional financial systems and blockchain technology, creating a compliant, scalable, and efficient platform for institutional adoption. "Over the past six years, we’ve meticulously developed advanced modules for compliance, tokenization, and data. With the launch of Nexera Chain, we’re uniting blockchain technology and modern capital markets in a single robust ecosystem. By integrating low-cost transactions and institutional-grade compliance at the protocol level, Nexera Chain enables secure, efficient on-chain financial operations. Nexera Chain redefines how capital markets embrace digital assets and decentralized finance." said Rachid Ajaja, Founder & CEO of Nexera Nexera Chain’s launch represents an important leap forward for blockchain adoption in institutional markets. By embedding compliance and interoperability into its core, it lays the groundwork for secure, scalable, and compliant participation in global tokenized markets. About Nexera Chain Nexera Chain is the first compliance-ready Layer 1 blockchain purpose-built to meet the demands of institutional on-chain capital markets. By embedding compliance, interoperability, and scalability at its core, Nexera Chain delivers a comprehensive solution for real-world asset tokenization, bridging traditional and decentralized finance. Contact PR Manager Ramsey Shallal Nexera Network ramsey@gelocubed.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here **Utrecht, Netherlands, January 9th, 2025/Chainwire/--**Nexera announces the launch of its Layer 1 blockchain purpose-built to meet the demands of institutional on-chain capital markets. By embedding compliance, interoperability, and scalability at its core, Nexera Chain delivers a comprehensive solution for real-world asset tokenization, bridging traditional and decentralized finance. This innovative blockchain integrates advanced AI-driven tools for compliance, enabling automated Know Your Customer (KYC), Know Your Business (KYB), Know Your Transaction (KYT), Anti-Money Laundering (AML), and Travel Rule enforcement. Nexera Chain ensures every participant and transaction adheres to global regulatory standards, providing institutions with the confidence to operate in a rapidly evolving regulatory landscape. Its design aligns with the principles of frameworks such as the EU’s Markets in Crypto-Assets (MiCA), offering a strong foundation for compliance without compromising efficiency or innovation. Nexera Chain stands out by addressing the long-standing challenges of blockchain adoption in institutional markets. Its compliance-first infrastructure eliminates the inefficiencies and security gaps caused by fragmented solutions, ensuring seamless integration of regulatory requirements. The blockchain’s omnichain interoperability enables fluid connections across public and private networks as well as legacy systems. This removes barriers to liquidity and data flow, paving the way for institutions to scale their tokenization efforts while maintaining the highest standards of compliance and security. The platform also simplifies tokenization for developers and enterprises with its developer-friendly APIs, SDKs, and white-label solutions. These tools streamline the process of bringing both tangible and digital assets on-chain, ensuring compliance across the entire asset lifecycle. Central to Nexera Chain is the ERC-7208 standard , a universal framework for managing tokenized assets, data, and identity across multiple networks. By standardizing these components, ERC-7208 supports consistent cross-chain activity and unlocks new opportunities for businesses to innovate within a scalable, interoperable environment. ERC-7208 standard ERC-7208 standard With over $1 billion in aggregate value represented across the Nexera ecosystem, including applications in tokenized real estate, art, carbon credit, GPUs, and more, Nexera Chain demonstrates its ability to deliver measurable value. Its unified infrastructure bridges the gap between traditional financial systems and blockchain technology, creating a compliant, scalable, and efficient platform for institutional adoption. "Over the past six years, we’ve meticulously developed advanced modules for compliance, tokenization, and data. With the launch of Nexera Chain, we’re uniting blockchain technology and modern capital markets in a single robust ecosystem. By integrating low-cost transactions and institutional-grade compliance at the protocol level, Nexera Chain enables secure, efficient on-chain financial operations. Nexera Chain redefines how capital markets embrace digital assets and decentralized finance." said Rachid Ajaja, Founder & CEO of Nexera "Over the past six years, we’ve meticulously developed advanced modules for compliance, tokenization, and data. With the launch of Nexera Chain, we’re uniting blockchain technology and modern capital markets in a single robust ecosystem. By integrating low-cost transactions and institutional-grade compliance at the protocol level, Nexera Chain enables secure, efficient on-chain financial operations. Nexera Chain redefines how capital markets embrace digital assets and decentralized finance." said Rachid Ajaja , Founder & CEO of Nexera Rachid Ajaja Rachid Ajaja Nexera Chain’s launch represents an important leap forward for blockchain adoption in institutional markets. By embedding compliance and interoperability into its core, it lays the groundwork for secure, scalable, and compliant participation in global tokenized markets. About Nexera Chain Nexera Chain is the first compliance-ready Layer 1 blockchain purpose-built to meet the demands of institutional on-chain capital markets. By embedding compliance, interoperability, and scalability at its core, Nexera Chain delivers a comprehensive solution for real-world asset tokenization, bridging traditional and decentralized finance. Nexera Chain Nexera Chain Contact PR Manager Ramsey Shallal Nexera Network ramsey@gelocubed.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Nexera Announces First Compliance-Ready Layer 1 For Institutional On-Chain Capital Markets

Nexera oznamuje první vrstvu 1 připravenou na dodržování předpisů pro institucionální kapitálové trhy v řetězci

Nexera anuncia la primera capa 1 preparada para el cumplimiento normativo para los mercados de capitales institucionales en cadena

Nexera-k kate instituzionaleko kapital-merkatuetarako betetzeko prest dagoen lehen geruza iragartzen du

Nexera اولین لایه آماده انطباق را برای بازارهای سرمایه در زنجیره سازمانی اعلام کرد

Nexera、機関投資家向けオンチェーン資本市場向けの初のコンプライアンス対応レイヤー1を発表

Nexera ប្រកាសការអនុលោមតាមលំដាប់ថ្នាក់ដំបូង 1 សម្រាប់ទីផ្សារមូលធនតាមខ្សែសង្វាក់របស់ស្ថាប័ន

Nexera ogłasza pierwszą warstwę 1 gotową do zgodności dla instytucjonalnych rynków kapitałowych w łańcuchu

Nexera Itangaza Iyubahirizwa Ryambere-Yiteguye Urwego 1 Kubigo Kumurongo-Urunigi Isoko Rikuru

Nexera Inozivisa Yekutanga Kuteerera-Yakagadzirira Layer 1 YeInstitutional On-Chain Capital Markets

“Nexera” institusional zynjyrly maýa bazarlary üçin ilkinji laýyklyk 1-nji gatlagy yglan edýär

Nexera نے ادارہ جاتی آن چین کیپٹل مارکیٹس کے لیے پہلی تعمیل کے لیے تیار پرت 1 کا اعلان کیا

I-Nexera ibhengeza ukuThotyelwa kokuQala-uLungele uLwaleko loku-1 kwiiMarike zeNkunzi zeZiko

Master Company Name Matching in Minutes with Python's Ready-Made Libraries

READY

ready.net

-- employees

Since n.d.

COMPANY RANKING

READY

EVERGREEN INDEX #9705

Representing this company? Click here to claim and customize this page!

Ready WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

READY

ready.net

-- employees

Since n.d.

COMPANY RANKING

READY

EVERGREEN INDEX #9705

RELATED COMPANIESRANK

STORIES ABOUT READY

Representing this company? Click here to claim and customize this page!

Ready WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!