Y Ventures Group Becomes First to Launch an ICO in Singapore 5111

An e-commerce platform that recently launched a token sale aimed to raise $50 million has become Singapore’s first public firm to hold an ICO. Y Ventures Group, which went public on the Stock Exchange of Singapore last year, announced a plan for creating a blockchain-based e-commerce system in July and sent the sale of its AORA token live at the end of the same month.

According to the firm, the tokens do not represent ownership of equity in the firm and, as such, should not be regarded as securities – a move perhaps aimed to sidestep concerns from market regulators. Notably, the Monetary Authority of Singapore – the country’s de facto central bank – halted one token sale in March as it deemed the tokens securities since, in that case, they did represent equity ownership.

Y Ventures may be the first, but it is not the only public firm in the city state looking to venture into the ICO space. Public entertainment company Spackman also said in February that it aims to issue a cryptocurrency called K Coin in an effort to raise funds for its celebrity business. It has not yet made any announcement about a formal launch, however.

Aside from directly conducting token sales themselves, some public firms in Singapore are also acquiring or managing projects that deal with ICOs as another route into the cryptocurrency space. In May, for example, real-estate developer Pacific Star Development signed an agreement with a startup called Crowdvilla in May to become its exclusive asset manager. Crowdvilla is now seeking to raise $18 million through an ICO to build a group of shared holiday homes.

Taking another route, MC Payment, a blockchain payments firm, acquired a lifestyle startup that raised $2.4 million through an ICO in 2017, and is now setting out to go public via the purchase of an already listed Singaporean firm called Artivision.

While Singapore currently has guidelines for ICOs, but no hard and fast rules, a spokesperson for the stock exchange said in a local news report on Friday that public companies must periodically report on their ICO status to ensure stock investors are properly informed.

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Instructure Delivers on Its Agentic AI Promise with the Launch of IgniteAI Agent 1635

New agentic capabilities extend IgniteAI’s open, privacy-first infrastructure, prioritizing educational outcomes and human connection while automating complex workflows at scale

Instructure, the leading learning ecosystem and maker of Canvas LMS, today announced the launch of IgniteAI Agent, initially in the United States and Latin America, marking a major milestone in the company’s vision to serve as the trusted, long-term partner for the future of learning. Powered by Amazon Web Services (AWS), the Agent expands Instructure’s IgniteAI suite to move beyond isolated tools. It provides a secure, transparent workflow capability that helps institutions navigate the shift toward agentic AI, in which technology orchestrates time-consuming, low educational value tasks to amplify human potential. Visit Instructure’s website to learn more about IgniteAI Agent and visit the Artificial Intelligence Supplement site to review the applicable terms.

IgniteAI Agent builds on this foundation by enabling technology to perform complex, multi-step operations on behalf of educators and administrators while preserving institutional control, transparency and trust. The result is less time spent navigating systems and more time focused on mentoring students, delivering feedback and supporting meaningful learning experiences.

“When we launched IgniteAI, we promised an ecosystem where AI works for educators, not around them,” said Shiren Vijiasingam, chief product officer at Instructure. “IgniteAI Agent is the realization of that promise. It moves us beyond generic content creation to true agentic support that can be opted into to securely orchestrate time-saving workflows while educators stay in charge of educational outcomes.”

Early adopters are already applying these capabilities in real-world teaching and instructional design workflows.

“For us, the power of IgniteAI and the Agent isn’t theoretical,” said Brandon Mitchell, Director of Instructional Design and Technology at Hinds Community College. “We’re using it right now to build modules, design pages, clean up accessibility, and speed up content creation. And we’re excited to keep testing and pushing the boundaries, because the potential is enormous.”

Delivering the Agentic Future of Teaching and Learning

IgniteAI Agent is part of Instructure’s IgniteAI suite and is powered by Amazon Bedrock, a platform on AWS for building generative applications and agents. The Agent helps automate routine tasks such as rubric generation, content alignment and discussion reviews. This frees educators to focus more on mentoring, feedback and meaningful learning experiences.

IgniteAI Agent extends these capabilities by enabling AI to carry out end-to-end workflows across Canvas. With a single prompt, educators can now initiate and coordinate complex actions, such as creating and organizing course modules, adjusting all due dates, or seeking out complementary content matched to your course materials, that previously required multiple clicks, tabs and manual steps.

Designed as an open, extensible agent for education, IgniteAI Agent is being built to work not only across Instructure products but alongside trusted partner technologies already used by institutions. Instructure is actively collaborating with partners across the broader edtech ecosystem to enable the Agent to securely embed partner capabilities directly into an educator’s workflow, allowing them to leverage those capabilities more frequently while minimizing friction.

Trust, Transparency and Institutional Control by Design

IgniteAI Agent is governed by the same privacy-first framework that underpins IgniteAI:

  • Closed-loop architecture: AI interactions occur within the institution’s environment and customer data is not used to train external models
  • Strict opt-in controls: Institutions enable AI features at the institutional, departmental or course level
  • Clear transparency: AI Nutrition Facts disclose models in use, data access and privacy protections

From Experimentation to Impact

As institutions move from AI experimentation to measurable outcomes, IgniteAI Agent reinforces that AI is a means to better teaching and learning, not an end in itself. The agent focuses on workflows that matter, reducing administrative burden, improving consistency and supporting equitable, outcomes-aligned instruction.

“It is not enough to simply automate tasks. As AI takes on more responsibility, we must bring quality, rigor and verification to how educational outcomes are defined and measured,” said Vijiasingam. “IgniteAI Agent is designed to be that accountability layer, ensuring that as we scale efficiency, we also elevate the integrity of the learning process while keeping the educator front and center. This is agentic technology built for education, responsibly, transparently and in partnership with our customers.”

Availability

IgniteAI Agent will be available at no cost for U.S. Canvas customers through June 30, 2026, with global free access extended through September 30, 2026 to account for phased rollout in countries outside the U.S. This free access period is designed to support thoughtful adoption, customer co-creation and institutional readiness, giving educators and administrators time to explore agentic AI capabilities within Canvas while maintaining full control over enablement and use.

About Instructure

Instructure is shaping the future of learning by delivering a future-ready ecosystem that helps learners thrive in tomorrow’s landscape. Our vision is to drive a future where education technology seamlessly amplifies human potential, empowering people to excel in a perpetually changing world. Instructure is setting potential in motion by connecting educators, institutions and learners across K–12, higher education and the workforce — enhancing experiences at every age, every stage and every pivotal transition. Discover more at Instructure.com.

New study finds AI models prefer Bitcoin and digital money over traditional fiat currency 1636

The Bitcoin Policy Institute (BPI), a nonpartisan research organization, released new research today examining how frontier AI models would choose to transact if they were operating as autonomous economic agents. The study tested 36 models from six leading AI providers—Anthropic, DeepSeek, Google, MiniMax, OpenAI, and xAI—across 9,072 open-ended monetary scenarios designed to be neutral, with no suggested currencies or predetermined answers.

Key Findings

  • Bitcoin came out on top at 48.3% of all responses, more than any other option. Stablecoins followed at 33.2%.
  • AI models overwhelmingly rejected fiat: +90% of responses favored digitally-native money (including dollar-pegged stablecoins) over traditional fiat. Not a single model out of 36 chose fiat as its top preference.
  • Bitcoin dominated store of value at 79.1%. In scenarios about preserving value long-term, Bitcoin was the strongest consensus on any single question in the study.
  • Stablecoins led for everyday payments at 53.2%. For transactions and payments stablecoins led over while Bitcoin (36.0%), revealing a clear savings-versus-spending divide.
  • Models invented their own money. Without any prompting, 86 responses independently proposed energy or compute units (such as kilowatt-hours and GPU-hours) as a way to price goods and services.
  • Preferences varied by provider but held across conditions. Bitcoin preference ranged from 91.3% (Anthropic’s Claude Opus 4.5) to 18.3% (OpenAI’s GPT-5.2), but results were consistent regardless of how the models’ output settings were configured.

Without any prompting, AI models converged on a two-tier monetary system—Bitcoin for savings, stablecoins for spending—that mirrors how hard money and liquid instruments have functioned throughout history. As AI agents gain economic autonomy, these preferences carry direct policy implications.

The findings suggest growing demand for agent-native Bitcoin payment infrastructure, self-custody solutions, and Lightning Network integration. The research also found that preferences varied meaningfully across providers and rose with model capability, indicating that monetary reasoning in AI systems is shaped by a combination of model intelligence, training data, and alignment methodology. Policymakers and financial institutions should prepare for a future in which autonomous AI agents are significant participants in monetary networks, and their revealed preferences strongly favor open, permissionless systems.

The full study is available at https://www.moneyforai.org/

About the Bitcoin Policy Institute

The Bitcoin Policy Institute (BPI) is a nonpartisan, nonprofit research organization dedicated to examining the policy and societal implications of Bitcoin and emerging monetary networks. BPI provides research and expert analysis to policymakers, regulators, media, and the public. Learn more at www.btcpolicy.org.

Voltage Launches First Payment-Volume Line of Credit: Bitcoin Finality, USD Settlement 2028

Voltage Launches Industry’s First Programmatic Revolving Line of Credit: Bitcoin Finality with USD Settlement

Voltage, a leader in Bitcoin infrastructure, today announced the launch of Voltage Credit, the first revolving line of credit that delivers instant payment finality and the capability to settle entirely in USD. The product lets businesses send payments that clear in seconds, not days, while paying back their credit line in dollars from a standard bank account, or in Bitcoin.

For enterprises frustrated by settlement delays, chargeback exposure, and the cost of legacy payment rails, Voltage Credit offers a new model: tap a revolving credit line on demand, move value instantly over Bitcoin rails, and never touch cryptocurrency on your balance sheet. The result is working capital efficiency without treasury complexity.

Voltage Credit arrives on the heels of the company’s role powering the first publicly reported $1 million Lightning Network payment between Secure Digital Markets and Kraken, a milestone that demonstrated Lightning’s readiness for institutional-scale settlement. With Voltage Credit, the company extends that infrastructure to address one of the most persistent barriers to enterprise Bitcoin adoption: working capital efficiency.

“Businesses shouldn’t have to choose between the speed and cost advantages of Bitcoin rails and the financial flexibility they need to operate,” said Graham Krizek, CEO of Voltage. “Until now, using Bitcoin for payments meant managing cryptocurrency on your balance sheet. Voltage Credit eliminates that tradeoff. Send payments instantly over Lightning, denominated in USD or Bitcoin based on what fits your business, and deploy your capital toward growth. That’s what Bitcoin infrastructure should look like for the enterprise.”

Deferred Settlement In Dollars with a USD Line of Credit

Unlike traditional Bitcoin lending products that focus on retail holders borrowing against static collateral, Voltage Credit is built for operational business needs. The product functions as a true revolving credit line: businesses draw only what they need, pay interest only on what they use, and restore their available credit immediately upon repayment. Credit limits can grow with usage, scaling alongside the business as transaction volume increases. And because Voltage Credit is natively integrated into the Voltage Platform, their credit line is instantly accessible wherever the business already operates, programmatically available across the same rails that power your payments:

Key capabilities include:

  • USD settlement flexibility. Credit can be repaid in dollars from a standard bank account, eliminating forced BTC liquidations and simplifying accounting.
  • Revenue-based underwriting. Because Voltage powers the underlying payment infrastructure, credit limits can scale based on actual transaction volume—not just static collateral.
  • Works with Lightning and on-chain. Businesses can move value via whichever Bitcoin rail fits their use case.

“For CFOs and treasury teams, this solves a real problem,” said Bobby Shell, VP of Marketing at Voltage. “You get the instant settlement and near-zero fees of Lightning without the treasury complexity. No forced crypto exposure, no guessing how much capital to lock up. Just a revolving credit line you can tap on demand, denominated in USD or Bitcoin based on what fits your business. It’s the flexibility finance teams have been asking for since Bitcoin entered the enterprise conversation.”

Bitcoin Rails for Any Business

Voltage Credit is attracting interest from both cryptocurrency-native companies and traditional enterprises exploring Bitcoin payment infrastructure for the first time. For businesses outside the crypto ecosystem, the appeal is straightforward: Lightning Network offers instant, global settlement at a fraction of the cost of legacy payment rails, and Voltage Credit means they can access those benefits while keeping their treasury and accounting entirely in USD, if desired.

For enterprises already operating in digital assets, whether exchanges, payment service providers, or miners, traditional financing has presented a structural problem. Banks typically do not recognize Bitcoin revenue as an asset for underwriting purposes, while existing crypto lending products require businesses to lock up BTC as collateral, creating tax events and exposing corporate treasuries to volatility.

Voltage Credit addresses both audiences by treating payment flows as the high-quality signal they are. Businesses processing consistent volume through Voltage infrastructure can access working capital that scales with their operations, bridging the gap between Bitcoin-denominated revenue and USD-denominated expenses without liquidating assets.

The product features no origination fees and a simple fixed APR on outstanding balances. Voltage Credit is currently available to qualified businesses in the United States.

About Voltage

Voltage is a Bitcoin infrastructure company providing enterprise-grade solutions for regulated, high-volume businesses. The Voltage platform enables enterprises to integrate Bitcoin payments with enterprise SLAs, managed infrastructure, and capital-efficient liquidity solutions. From powering instant settlement to providing revenue-based lines of credit, Voltage builds the operational engine for businesses moving value on Bitcoin rails.

More information is available at voltage.cloud.

BrandJet AI Launches Artemis MCP and Introduces Forward Deployed AE Role for AI-Driven GTM Teams 3920

BrandJet AI, a brand intelligence and outreach automation platform, today announced the launch of Artemis, a new Model Context Protocol (MCP) layer designed to help go-to-market (GTM) teams execute complex multi-step workflows using natural language prompts. The company also introduced a new commercial role, the Forward Deployed Account Executive (FDAE), created to support organizations adopting AI-native revenue operations.

The announcements reflect BrandJet AI’s continued focus on reducing fragmentation across sales, marketing, and revenue technology stacks by connecting intent detection and outreach execution within a single operating environment.

Addressing GTM Fragmentation

Revenue teams typically rely on multiple systems to monitor brand conversations, identify prospects, enrich contact data, sequence outreach, and track engagement. These processes often require manual coordination across platforms, creating delays between signal detection and commercial action.

Artemis is designed to streamline this workflow. Built on a Model Context Protocol architecture, it connects BrandJet AI’s monitoring, enrichment, sequencing, and performance-tracking capabilities into a unified prompt-driven layer.

Through Artemis, revenue operators can initiate structured workflows using natural language instructions. For example, a user may request the identification of professionals discussing specific topics across digital platforms within a defined timeframe, enrichment of those profiles, and the creation of an outreach sequence aligned to campaign goals. Artemis coordinates those tasks within the system, allowing teams to reduce operational handoffs.

According to BrandJet AI, the goal is not to replace strategic oversight but to simplify execution.

“Revenue teams spend too much time stitching together tools instead of acting on real buying signals,” said Nirav Shah, CEO of BrandJet AI. “Artemis helps unify intelligence and execution so teams can move from insight to outreach more efficiently.”

Prompt-Driven Workflow Orchestration

Artemis supports workflows that include:

  • Monitoring brand and competitor mentions across social platforms and the open web
  • Identifying potential prospects based on observable intent signals
  • Enriching lead data within the platform
  • Initiating multi-channel outreach across email and major social networks
  • Tracking engagement and campaign performance in real time

Rather than requiring operators to manually transfer data between systems, Artemis enables coordinated execution through a conversational interface layered on top of BrandJet AI’s infrastructure.

The system is designed to operate within compliance and governance standards established by customer organizations, maintaining human oversight over messaging and campaign parameters.

Introducing the Forward Deployed Account Executive

Alongside the Artemis launch, BrandJet AI announced the introduction of the Forward Deployed Account Executive (FDAE), a role intended to help enterprise customers integrate AI-driven workflows into their revenue operations.

As AI platforms become more advanced, organizations often encounter implementation gaps between technical capability and day-to-day usage. The FDAE model is structured to address that gap by embedding commercially accountable operators more deeply into customer environments.

Unlike traditional account executives who primarily focus on closing new business, or customer success managers who focus on support and retention, the FDAE combines revenue accountability with workflow strategy support. The role is designed to assist customers in mapping Artemis and broader BrandJet AI capabilities to their specific GTM structures.

“The technology layer is evolving quickly, but successful adoption depends on workflow design and operational alignment,” said Marsad Aurangzeb, Founder of BrandJet AI. “The Forward Deployed AE role is intended to help customers translate AI capabilities into measurable revenue outcomes.”

BrandJet AI plans to formalize the FDAE framework and publish additional details regarding the role’s structure and responsibilities in 2026.

Connecting Listening and Outreach

Historically, social listening and sales engagement technologies have evolved separately. Listening platforms track conversations, brand mentions, and sentiment across digital channels, while engagement platforms focus on outbound sequencing and pipeline development.

BrandJet AI’s platform integrates both functions, allowing teams to identify signals and initiate outreach within the same environment. With Artemis, those processes can now be coordinated through prompt-driven workflows.

For example, when a relevant public conversation surfaces online, such as a discussion about a specific technology category, hiring signals, or operational challenges, Artemis can help surface the signal, enrich the associated contact, and assist in preparing a tailored outreach campaign.

The objective is to reduce the time between observed intent and commercial response, while maintaining alignment with compliance and messaging standards.

Enterprise Implementation and Governance

BrandJet AI emphasizes that Artemis is built to operate within enterprise governance frameworks. Campaign parameters, messaging templates, and data usage policies remain configurable by customer teams.

As organizations expand AI adoption within revenue functions, governance considerations, including messaging accuracy, compliance adherence, and brand alignment, remain central. Artemis is positioned as an execution layer that operates within these controls rather than outside them.

The company states that ongoing enhancements are planned, including additional intent modeling refinements, deeper workflow customization, and validation loops that compare forecasted campaign outcomes with actual engagement performance over time.

Availability

Artemis MCP is available immediately to customers on BrandJet AI’s Growth and Enterprise plans. Availability for Starter plan users is expected in Q2 2026. Forward Deployed Account Executive engagements are currently offered on a limited basis for Enterprise customers.

Organizations interested in learning more may contact BrandJet AI directly for additional information.

About BrandJet AI

BrandJet AI is a brand intelligence and outreach automation platform designed for modern revenue teams. The platform enables organizations to monitor brand and competitor activity across digital channels, identify potential prospects based on social and behavioral signals, and execute multi-channel outreach campaigns within a unified interface. BrandJet AI serves growth-stage and enterprise organizations across SaaS, financial services, and professional services industries.

Xojo 2025r3 Delivers Major Updates, New Libraries Feature, Integrated AI Assistant, and Modern OS Support 4547

Xojo, Inc., the developers behind Xojo—a powerful cross-platform development tool and programming language— announce the immediate availability of Xojo 2025 Release 3, a significant update that expands platform compatibility, introduces powerful new development tools and enhances performance across Desktop, Web, Console, iOS and Android.

This release adds official support for macOS Tahoe 26 and iOS 26, including Apple’s new Liquid Glass interface technologies, ensuring developers can confidently build and deploy apps on the latest operating systems.

Xojo 2025r3 debuts Libraries, a major enhancement to the IDE that allows developers to package and reuse compiled classes and interface elements across Desktop, Web, Console and iOS projects. Libraries make sharing and versioning custom functionality easier and faster.

The IDE also introduces Jade, Xojo’s new integrated AI assistant. Jade helps developers write code more efficiently, suggest improvements and accelerate learning directly from inside the Xojo environment. “Xojo 2025r3 is one of our most forward-looking releases yet. With Libraries, modern platform support and our new AI assistant Jade, we’re giving developers powerful tools that help them work faster, build smarter and deliver great apps on every platform,” says Geoff Perlman, Xojo’s Founder and CEO.

New Features and Updates:

  • Support for macOS Tahoe 26 and iOS 26
  • IDE now supports Libraries for Desktop, Web, Console and iOS projects
  • IDE now has an AI assistant, called Jade
  • Added DesktopGrid control
  • Multiple WebListBox improvements
  • Web now uses Bootstrap v5.3.7 and Bootstrap Icons v1.13.1
  • Added Passkeys/WebAuth support for web apps
  • Windows DesktopXAMLContainer improvements
  • Expanded WinUI-backed controls
  • Several Crypto enhancements
  • Improved color settings for layouts and controls on iOS and Android
  • Android Support for PDFDocument
  • Android now uses Kotlin 2.2.20 and targets Android 16 (SDK 36)

About Xojo

Xojo is a cross-platform development tool for building native apps for macOS, Windows, Linux, iOS, Android, the web and Raspberry Pi. For over 25 years, Xojo has supported a growing community of developers passionate about creating powerful applications with ease. Learn more at xojo.com. Download Xojo 2025 Release 3 at xojo.com/download.

Availability

Xojo is free for learning and development, as well as for building apps for Linux and Raspberry Pi. Paid licenses start at $499 for cross-platform Desktop, Mobile, or Web development. Xojo Pro and Pro Plus licenses, starting at $999, offer additional support and resources for professional developers. Special licensing is available for educators and students. Visit xojo.com/store for details.

AI Infrastructure Company EverMind Released EverMemOS, Responding to Profound Challenges in AI 4656

AI infrastructure company EverMind has recently released EverMemOS, an open-source Memory Operating System designed to address one of artificial intelligence’s most profound challenges: equipping machines with scalable, long-term memory.

The Memory Bottleneck

For years, large language models (LLMs) have been constrained by fixed context windows, a limitation that causes “forgetfulness” in long-term tasks. This results in broken context, factual inconsistencies, and an inability to deliver deep personalization or maintain knowledge coherence. The issue extends beyond technical hurdles; it represents an evolutionary bottleneck for AI. An entity without memory cannot exhibit behavioral consistency or initiative, let alone achieve self-evolution. Personalization, consistency, and proactivity, which are considered the hallmarks of intelligence, all depend on a robust memory system.

There is a consensus that memory is becoming the core competitive edge and defining boundary of future AI. Yet existing solutions, such as Retrieval-Augmented Generation (RAG) and fragmented memory systems, remain limited in scope, failing to support both 1-on-1 companion use cases and complex multi-agent enterprise collaboration. Few meet the standard of precision, speed, usability, and adaptability required for widespread adoption. Equipping large models with a high-performance, pluggable memory module remains a core unmet demand across AI applications.

Discoverative Intelligence

“Discoverative Intelligence” is a concept proposed in late 2025 by entrepreneur and philanthropist Chen Tianqiao. Unlike generative AI, which mimics human output by processing existing data, Discoverative Intelligence describes an advanced AI form that actively asks questions, forms testable hypotheses, and discovers new scientific principles. It prioritizes understanding causality and underlying principles over statistical patterns, a shift Chen argues is essential to achieving Artificial General Intelligence (AGI).

Chen contrasted two dominant AI development paths: the “Scaling Path,” which relies on expanding parameters, data, and compute power to extrapolate within a search space, and the “Structural Path,” which focuses on the “cognitive anatomy” of intelligence and how systems operate over time.

Discoverative Intelligence falls into the latter category, built on a brain-inspired model called Structured Temporal Intelligence (STI) that requires five core capabilities in a closed loop: neural dynamics (sustained, self-organizing activity to keep systems “alive”), long-term memory (storing and selectively forgetting experiences to build knowledge), causal reasoning (inferring “why” events occur), world modeling (an internal simulation of reality for prediction), and metacognition & intrinsic motivation (curiosity-driven exploration, not just external rewards).

Among these capabilities, long-term memory serves as the vital link between time and intelligence, highlighting its indispensable role in the path toward achieving true AGI.

EverMind’s Answer

EverMemOS is EverMind’s answer to this need: an open-source Memory Operating System designed as foundational technology for Discoverative Intelligence. Inspired by the hierarchical organization of the human memory system, EverMemOS features a four-layer architecture analogous to key brain regions: an Agentic Layer (task planning, mirroring the prefrontal cortex), a Memory Layer (long-term storage, like cortical networks), an Index Layer (associative retrieval, drawing from the hippocampus), and an API/MCP Interface Layer (external integration, serving as AI’s “sensory interface”).

The system delivers breakthroughs in both scenario coverage and technical performance. It is the first memory system capable of supporting both 1-on-1 conversation use cases and complex multi-agent enterprise collaboration. On technical benchmarks, EverMemOS achieved 92.3% accuracy on LoCoMo (a long-context memory evaluation) and 82% on LongMemEval-S (a suite for assessing long-term memory retention), significantly surpassing prior state-of-the-art results and setting a new industry standard.

The open-source version of EverMemOS is now available on GitHub, with a cloud service version to be launched late this year. The dual-track model, combining open collaboration with managed cloud services, aims to drive industry-wide evolution in long-term memory technology, inviting developers, enterprises, and researchers to contribute to and benefit from the system.

About EverMind

EverMind is redefining the future of AI by solving one of its most fundamental limitations: long-term memory. Its flagship platform, EverMemOS, introduces a breakthrough architecture for scalable and customizable memory systems, enabling AI to operate with extended context, maintain behavioral consistency, and improve through continuous interaction.

To learn more about EverMind and EverMemOS, please visit:
Website: https://evermind.ai/
GitHub: https://github.com/EverMind-AI/EverMemOS
X: https://x.com/EverMindAI
Reddit: https://www.reddit.com/r/EverMindAI/