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Poke Becomes First AI Agent Approved for Apple’s Messages for Business Platform

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Poke, a startup that simplifies interaction with powerful AI agents to the simplicity of sending a text message, has secured approval to operate on Apple’s Messages for Business platform.

This marks the first time a standalone third-party AI agent has been integrated into the service, previously reserved for businesses such as airlines, retailers, and hotel chains to communicate directly with customers via iMessage.

Launched in March, Poke aims to make advanced AI accessible to everyday users who lack technical expertise or interest in complex interfaces. Through simple text conversations, users can manage daily planning, calendars, health and fitness tracking, smart home controls, and photo editing. To date, the service has relayed more than 100 million messages across SMS, Telegram, WhatsApp (in select markets), and now iMessage.

The integration expands Poke’s reach within Apple’s tightly controlled ecosystem and comes just days before Apple’s Worldwide Developers Conference (WWDC), where the company is expected to unveil an AI-optimized Siri and other developer tools. While rumors suggest Apple may open its App Store to AI agents, Poke’s approval operates through the existing Messages for Business framework, allowing users to interact with the AI directly through iMessage without downloading a separate app.

Marvin von Hagen, co-founder of The Interaction Company (the Palo Alto-based startup behind Poke), highlighted the strategic importance of the move. The company will pay Apple on a per-user basis — a structure von Hagen described as significantly more favorable than recent fee increases imposed by Meta on its WhatsApp platform due to EU regulations.

This revenue-sharing model could represent a meaningful new income stream for Apple while giving AI startups like Poke scalable distribution within one of the world’s most valuable consumer ecosystems.

“I think that Apple is just noticing this is the best way to offer AI, and … actually, good for them, because they charge us. They charge us per user on the platform and actually make money with this, especially if it becomes really big,” von Hagen said.

Approval Process and Trust Factors

Securing Apple’s approval was no small feat. It required Poke to demonstrate robust live human support capabilities as a fallback, clearly identify itself as an AI agent, and adhere to strict design guidelines. This included using Apple-style buttons, interface elements, and link previews instead of inline links.

Von Hagen noted the process took several months and will likely pose a similar barrier for other AI agents seeking entry.

“This took a couple of months to adhere to all of these standards, and it will take anyone else who wants to build on this — it will also take them a couple of months to get through this approval process,” he said.

Trust played a significant role in Poke being first. Von Hagen emphasized that the startup’s focus on quality and long-term brand integrity, rather than aggressive growth tactics, aligned well with Apple’s standards.

Poke is currently rolling out invites to existing users, giving them the option to shift interactions to iMessage. The service will initially remain free for businesses and consumers, with paid tiers expected soon.

This development is significant on multiple levels. For Apple, it represents a pragmatic step toward embracing AI agents without immediately opening the App Store or core iOS systems. By integrating capable third-party agents into Messages for Business, Apple can enhance the utility of its messaging platform while generating new revenue and gathering valuable data on AI usage patterns.

For the broader AI industry, Poke’s approval highlights the growing push toward agentic AI — systems that go beyond answering questions to actively performing tasks. While giants like OpenAI, Anthropic, and Google dominate headlines with frontier models, startups like Poke are focusing on usability and accessibility. Poke is attempting to meet users where they already are, rather than forcing them into new apps or interfaces by operating across SMS, messaging apps, and now iMessage.

With WWDC approaching, Apple is under pressure to demonstrate meaningful AI progress. Allowing Poke onto Messages for Business could serve as an early signal of how Apple envisions third-party AI integration — controlled, secure, and revenue-generating for the company.

Poke, backed by Spark Capital, General Catalyst, and several angels, recently raised an additional $10 million, bringing its total funding to $25 million. The 10-person startup is now valued at $300 million post-money. Its lean structure and focus on practical, text-first interactions differentiate it from more resource-intensive agent platforms.

Von Hagen and his team are betting that simplicity and seamless integration will drive adoption. In a world where many AI tools still feel experimental or overly complex, Poke’s text-message interface lowers the barrier dramatically. Early traction, 100 million messages in just a few months, suggests strong product-market fit among users seeking frictionless AI assistance.

Foxconn and Intel Forge AI Infrastructure Alliance, to Build Next-Gen AI Systems

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Taiwanese manufacturing giant Foxconn is deepening its push into artificial intelligence infrastructure through a new partnership with Intel, a move that highlights how the AI boom is reshaping the competitive landscape of the semiconductor and data center industries.

Foxconn, formally known as Hon Hai Precision Industry, announced Thursday that it will collaborate with Intel to jointly develop and deploy next-generation AI infrastructure and intelligent computing platforms.

The partnership comes as technology companies, cloud providers, and governments worldwide pour unprecedented sums into AI computing capacity. Industry executives estimate that hyperscalers and major cloud providers will spend close to $1 trillion annually on AI infrastructure within the next few years, creating enormous opportunities for chipmakers, server manufacturers, and data center equipment suppliers.

Under the agreement, Intel will contribute its processor and accelerator technologies, while Foxconn will leverage its vast manufacturing footprint and system-integration capabilities. The companies plan to collaborate on AI data center equipment, including server racks powered by Intel’s Xeon processors and AI accelerator chips.

The partnership will also focus on several increasingly important areas of AI infrastructure, including high-speed interconnect technologies, advanced cooling systems, and energy-efficiency solutions.

Those areas have become critical battlegrounds in the AI race. As AI models grow larger and more computationally demanding, the challenge is no longer simply producing faster chips. Companies now must also solve problems involving power consumption, heat dissipation, and data movement between thousands of interconnected processors.

This is where Foxconn sees a major opportunity.

Traditionally known as the world’s largest contract electronics manufacturer and the primary assembler of products for companies such as Apple, Foxconn has been rapidly repositioning itself as a supplier of AI infrastructure. The company is already the largest manufacturer of AI servers for Nvidia and has become one of the biggest beneficiaries of the global AI investment wave.

Chairman and Chief Executive Officer Young Liu recently said that spending by major cloud providers represents one of the strongest growth drivers in the company’s history.

“Our collaboration with Intel will combine the strengths of both companies across computing platforms, system integration, and global supply chain capabilities,” Liu said in a statement.

For Intel, the partnership represents another effort to strengthen its position in the rapidly evolving AI ecosystem. Although Nvidia remains the dominant force in AI accelerators, Intel has been expanding its presence in AI infrastructure through Xeon processors, accelerator technologies, and advanced packaging capabilities. The company has also benefited from a growing shortage of high-performance CPUs, which remain essential for AI workloads alongside graphics processors.

Notably, the partnership extends beyond traditional data centers. Foxconn and Intel said they plan to develop AI systems for factories, smart cities, and robotics applications, reflecting a broader industry shift toward “edge AI,” where intelligence is deployed directly into devices and industrial environments rather than solely through centralized cloud infrastructure.

That opportunity could prove enormous.

As enterprises increasingly adopt autonomous systems, industrial robots, and AI-powered automation, demand is expected to grow for compact computing systems capable of running sophisticated AI models outside conventional server farms.

The companies also disclosed plans to explore custom chip development and broader system integration solutions, suggesting the alliance could eventually move into the rapidly expanding market for bespoke AI semiconductors.

Custom silicon has become one of the hottest segments of the semiconductor industry, with companies such as Alphabet, Amazon, and Microsoft increasingly designing their own processors to optimize performance and reduce costs.

The Foxconn-Intel collaboration arrives as competition intensifies across every layer of the AI infrastructure stack. Companies are racing not only to build more powerful chips but also to secure positions in server manufacturing, networking equipment, cooling technologies, power systems, and AI deployment platforms.

Neither company disclosed the financial value of the agreement, identified customers, or provided a timeline for commercial deployment. Nevertheless, the announcement shows that AI infrastructure is evolving into a massive ecosystem that requires integrating chips, servers, networking, software, and manufacturing expertise.

The deal thus reinforces Foxconn’s transformation from a contract manufacturer into a strategic AI infrastructure player, while it provides another avenue to expand Intel’s footprint in a market being defined by demand for large-scale AI computing systems.

Analysts expect partnerships such as this to become common as companies seek to combine technological expertise with manufacturing scale to capture a share of one of the industry, especially as spending on AI infrastructure accelerates globally.

Meta Launches Business AI Agent with Agentic Capabilities, Signaling Deeper Push into Enterprise Market

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Meta Platforms on Wednesday introduced a new artificial intelligence agent designed to handle day-to-day business operations, marking a significant step in the social media giant’s effort to expand beyond consumer apps into enterprise AI tools.

Unveiled at the company’s WhatsApp-focused Conversations conference in London, the Business Agent adds “agentic” functionality — the ability to autonomously take actions on behalf of businesses, such as booking calendar appointments, qualifying leads, closing sales, and processing payments.

This goes well beyond simple rule-based chatbots by enabling more complex, multi-step workflows.

Naomi Gleit, Meta’s head of product for the initiative, described the launch as a clear enterprise play.

“This is definitely an enterprise play,” he said.

Meta said more than 1 million businesses are already using earlier chatbot versions of such agents on WhatsApp and Messenger. The new version will be rolled out globally to businesses of all sizes and added to Instagram as well. Initially free, paid subscription options are planned for the coming months.

Broader Business Agent Platform and Ecosystem Integration

Alongside the in-app Business Agent, Meta is launching a wider Business Agent Platform that allows companies to build and deploy custom AI agents across their operations. The platform connects to hundreds of non-Meta systems, including Shopify, Zendesk, and Shopee, and offers enterprise-grade controls, guardrails, and performance measurement tools.

This platform approach aims to position Meta as a central orchestrator in the growing agentic AI space, where AI systems can independently manage workflows rather than just respond to queries.

Gleit highlighted the need for a unified experience, saying: “The number one thing I hear, especially from small businesses, is ‘I just want to go to one place that can do all the things.’”

She is leading a new Enterprise Solutions team as part of a recent company-wide restructuring around AI. The team will deploy squads of forward-deployed engineers to work directly with large customers, a model popularized by companies like Anthropic, to navigate internal adoption challenges and customize solutions.

Meta is also working to consolidate its various AI agents, including internal workflow tools, the public Meta AI bot, and a recently launched ads-focused business assistant.

The launch spins off Meta’s ambition to leverage its massive reach across WhatsApp, Messenger, and Instagram, platforms with billions of users, to gain ground in the enterprise AI market against specialists like OpenAI, Anthropic, and Google.

By embedding agentic capabilities directly into the communication tools businesses already use to engage customers, Meta is betting it can become a one-stop platform for both consumer-facing interactions and internal operations. This strategy could help the company diversify revenue beyond advertising while deepening its integration into business workflows.

Gleit emphasized the importance of orchestration and efficiency.

“We actually want to take actions now. We actually want it to be able to complete the payment, to process the booking, to place the order,” she said.

The move comes as competition in agentic AI intensifies. Rivals are rapidly advancing their own autonomous agents, while Microsoft and Apple are enhancing their ecosystems with similar capabilities.

However, Gleit acknowledged the risks of permitting AI agents to act on behalf of businesses, particularly around security and reliability. Meta recently faced an embarrassing incident in which hackers tricked its AI support chatbot into granting access to high-profile Instagram accounts.

She noted the issue stemmed from a flawed technical check rather than the agent itself.

“It wasn’t the agent. The agent actually exposed a technical check that wasn’t working. There was sort of a separate system and technical check that had a bug, and because people were using the agent, they discovered it,” she said.

Shares of Meta rose more than 3% in morning trading, suggesting investors view the announcement positively as a step toward new revenue streams and deeper platform stickiness.

The Business Agent and Platform represent Meta’s latest attempt to monetize its vast messaging ecosystem while positioning itself in the high-growth enterprise AI sector.

As AI agents move from experimental tools to core business infrastructure, Meta’s entry adds significant competition and choice for companies looking to automate operations. But the move represents more than just a product launch for Meta — it is seen as part of a broader strategic shift to build durable, high-margin AI businesses that complement its advertising empire and reduce reliance on any single revenue source.

Sunshine Silver Raises $270 Million in IPO as Mining Firms Join 2026 Listing Boom

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The resurgence of the U.S. initial public offering market is spreading well beyond artificial intelligence and technology, drawing mining companies back to public markets as investors hunt for exposure to commodities tied to industrial demand, energy security, and precious metals.

Sunshine Silver Mining & Refining Company priced its long-awaited U.S. IPO on Wednesday, raising $270 million and becoming the latest beneficiary of one of the strongest listing environments seen in years.

The Kellogg, Idaho-based company sold 20 million shares at $13.50 each, generating proceeds of approximately $270 million. The offering was priced at the lower end of its marketed range, a sign that while investor appetite remains robust, buyers are becoming more selective as a growing pipeline of new issuances competes for capital.

The listing arrives amid a dramatic revival in U.S. equity capital markets. After several years marked by high interest rates, geopolitical uncertainty, and weak investor sentiment, 2026 has evolved into a record year for new stock offerings.

Much of the attention has focused on blockbuster technology listings, with companies such as SpaceX and Anthropic preparing highly anticipated public debuts. However, Sunshine Silver’s successful offering highlights how enthusiasm is now extending into sectors traditionally overlooked during technology-led market rallies.

The renewed interest in mining companies comes along with several powerful trends reshaping global commodity markets. Governments across North America and Europe are seeking to strengthen domestic supply chains for critical minerals and metals, while investors are increasingly looking for exposure to hard assets amid concerns over inflation, geopolitical tensions, and supply disruptions.

Industry data show that at least 18 companies, primarily from Canada and Australia, alongside a smaller group of U.S.-based firms, have either completed or pursued dual U.S. listings this year. That compares with only three similar transactions during 2025, underscoring the rapid acceleration in mining-sector capital raising.

The momentum continued this week when copper-focused developer CopperTech Metals filed for a New York listing, joining a growing queue of resource companies seeking access to deeper pools of U.S. capital.

Founded in 2010, Sunshine Silver specializes in acquiring, redeveloping, and operating precious-metals assets across North America. Its flagship project centers on restarting and expanding a previously shuttered mining operation in Idaho’s Silver Valley, a region with a long history of silver production and one of the most significant mining districts in the United States.

Across the mining industry, companies are revitalizing existing assets rather than developing entirely new mines. Such projects often benefit from established infrastructure, historical geological data, and shorter development timelines, potentially reducing both costs and execution risks.

Sunshine Silver’s investment story is also closely tied to the outlook for silver itself. Traditionally viewed as a precious metal alongside gold, silver has increasingly become an industrial commodity because of its critical role in solar panels, electronics, electric vehicles, data centers, and advanced manufacturing.

Growing electricity demand from artificial intelligence infrastructure and renewable-energy deployment has strengthened long-term forecasts for silver consumption, prompting renewed investor interest in producers and developers.

The company enters public markets with backing from some of the mining sector’s most prominent investors. According to regulatory filings, investment firm The Electrum Group is expected to retain more than 50% of Sunshine Silver’s outstanding shares following the offering. The company is also backed by Ospraie Management, a well-known natural-resources-focused investment manager.

The continued presence of major shareholders after the IPO may provide investors with confidence regarding long-term strategic support, while also signaling that existing backers believe substantial value remains to be unlocked as projects advance.

Sunshine Silver is scheduled to begin trading on the New York Stock Exchange under the ticker symbol SSMR. Its debut comes alongside a wave of notable listings, including quantum-computing company Quantinuum and industrial-engine manufacturer Innio.

The transaction was led by major investment banks Morgan Stanley, Scotiabank, and BMO Capital Markets.

Beyond Sunshine Silver itself, the offering serves as another indication that investors are increasingly willing to fund companies tied to real assets and long-term infrastructure themes, not just artificial intelligence and software.

As record-breaking capital continues flowing into technology, energy, and industrial projects, mining firms appear poised to benefit from a market environment that is rewarding companies linked to the physical foundations of the global economy. If commodity prices remain supportive and investor demand for new issues stays strong, Sunshine Silver’s IPO may be remembered not simply as a standalone transaction but as part of a broader revival in mining-sector financing across North American capital markets.

How to Vet an Alternative Asset Manager in 2026

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Alternative assets represent an $18 trillion global market, and vetting an alternative asset manager to take care of your stake in it requires looking beyond basic historical performance. In a volatile macro environment, institutional allocators and family offices face a landscape where traditional strategy boundaries are blurring and operational risks are compounding. True due diligence means digging into the structural, technical, and operational machinery that drives sustainable returns.

The baseline for any serious evaluation starts with absolute clarity of strategy and rigorous institutional controls. Investors must look for managers who can clearly articulate their edge, back it up with fully audited track records, and demonstrate robust risk mitigation protocols.

Image Source: Google Gemini

The Core Pillars of Modern Operational Due Diligence

A comprehensive institutional framework separates top-tier managers from the rest of the field. Evaluation must focus heavily on infrastructure, alignment of interests, and structural transparency.

Evaluating the technical foundation requires examining how a firm manages data and executes strategy across different functions. The industry is moving rapidly toward unified operating environments.

A premier example of this evolution is a multi-division platform that seamlessly integrates alternative assets, wealth advisory, and data-driven intelligence, such as the operational model deployed by the Abacus Global Management firm for its many clients. When evaluating an organization, look closely at how information flows between its portfolio management systems and risk controls.

A manager’s operational framework must withstand deep operational inspection before any capital is committed. Sophisticated allocators use a specific checklist during this phase of the review:

  • A technology stack that utilizes advanced data governance to prevent operational leakage
  • A clear fee design with clawback provisions that protect the limited partners
  • A transparent reporting cadence that provides granular portfolio visibility

Liquidity terms must align precisely with the underlying asset class. Mismatches between fund redemption terms and the actual time required to liquidate assets are a frequent driver of fund distress during market corrections.

Navigating Emerging Markets and Founder-Led Frameworks

Deploying capital into emerging markets introduces distinct layers of complexity. Standard regulatory frameworks often look different across jurisdictions, making localized knowledge and specialized compliance infrastructure non-negotiable.

Managers operating in these regions require heightened scrutiny regarding local political risk, currency hedging mechanisms, and legal protections for foreign investors. For founder-operator limited partners, evaluating a manager also involves assessing key-person risk and succession planning. A brilliant investment strategy means very little if the firm’s entire institutional knowledge rests in the head of a single individual without a clear corporate governance structure.

Regulatory bodies have tightened oversight on valuation policies, meaning that third-party valuation verification is no longer optional for illiquid alternatives. Managers must show a repeatable, documented process for marking assets to market, especially when dealing with complex or distressed credit instruments.

Designing the Ultimate Allocator Framework

Securing capital preservation requires an ongoing commitment to monitoring. Due diligence is not a one-time gatekeeping exercise; it is a continuous process of verification throughout the investment lifecycle.

The most successful limited partners establish an active monitoring system that tracks style drift, team turnover, and operational compliance on a quarterly basis. Reviewing current industry Whitepapers and operational case studies on private market governance can provide allocators with deeper insights into updating their internal evaluation protocols. Reading more posts on our site is a great way to expand your understanding of the top-level topics discussed above.