Vennre, a wealth creation platform enabling HENRYs (High Earners, Not Rich Yet) to access private market opportunities, today announced the successful close of its Pre-Series A funding round, raising USD 9.6 million through a hybrid equity and debt structure.

The round was co-led by Vision Ventures and anb seed Fund, with participation from Sanabil 500, Ace & Co, Plus VC, and strategic individual investors from the private banking, technology and entrepreneurship ecosystems.

This investment reflects growing confidence from leading regional VCs and strategic backers in Vennre’s mission to democratize access to curated private investments for high income retail investors. By bypassing traditional gatekeepers, Vennre offers a transparent, Shariah-compliant solution previously available only to institutions and ultra-wealthy participants.

Founded by Ziad Mabsout, Anas Halabi and Abdulrahman AlMalik, Vennre has also reached two operational milestones: the appointment of Dr. Ibrahim AlMojel as Chairman of its Saudi board and surpassing USD 40 million in transaction value across its platform – clear evidence of growing market traction and investor trust.

Ziad Mabsout, CEO and Co-Founder of Vennre, said:

“A generation of ambitious professionals across the region has earned success but has not been given the tools required to compound it. This funding is not just another round — it is a clear endorsement from leading institutions that a large, long-underserved HENRY segment is ready for a better wealth-building experience. We are building for long-term wealth creation, not one-off transactions — starting with curated and vetted private investment opportunities and expanding into a full wealth journey built on discipline, trust, and alignment. This round allows us to raise the bar for what private wealth platforms in the region should deliver.”

Khalid S. Alghamdi, CEO of anb capital, added:

“We are pleased to co-lead Vennre’s Pre-Series A through the anb seed Fund. Private markets globally already manage more than USD 14 trillion in assets, yet individual investors account for less than 5% of that exposure. Vennre directly addresses this imbalance by offering Shariah-compliant access to a segment long excluded from these opportunities. Having already facilitated over USD 40 million in transactions, Vennre is proving that high-income Saudis are ready to engage with private markets at scale — fully aligned with Vision 2030’s mandate to broaden capital markets participation.”

Kais Al-Essa, Founding Partner and CEO of Vision Ventures, said:

“We are glad to co-lead Vennre’s Pre-Series A and excited to support such an amazing founding team. We’re always ready to back founders who use technology to make people’s lives easier and give them access to opportunities that were not available to them before. Vennre enables access to high quality investment opportunities in real estate, private equity, venture capital and private credit. These four asset classes were previously available to a select few. Democratizing such access is one of our investment goals at Vision Ventures as it enables generational wealth creation and empowers everyone to access vetted income generating and high return investments, in line with Saudi Arabia’s financial sector development plan and fintech momentum.”

Looking ahead, Vennre plans to deploy this capital to grow its client network, launch new platform features, and deepen its Saudi presence in line with ongoing financial sector liberalization and fintech momentum. More here https://www.vennre.com/

Microsoft Corp. has begun deploying its second-generation artificial intelligence chip, Maia 200, marking a major step in the company’s long-term effort to build its own AI hardware, rein in soaring computing costs, and reduce dependence on Nvidia’s dominant processors.

The Maia 200 chip, produced by Taiwan Semiconductor Manufacturing Co., is now being deployed in Microsoft data centers in Iowa, with further rollouts planned for the Phoenix area. Microsoft has invited developers to begin using the chip’s control software, though it has not said when Azure cloud customers will be able to directly access Maia-powered servers.

Some of the earliest Maia 200 units will be allocated to Microsoft’s superintelligence team, where they will generate data to help improve the next generation of AI models, according to cloud and AI chief Scott Guthrie. The chips will also power Microsoft’s Copilot assistant for businesses and support AI models, including OpenAI’s latest systems, that the company offers to enterprise customers through Azure.

At one level, Maia 200 is about performance and efficiency. Microsoft says the chip outperforms comparable offerings from Google and Amazon Web Services on certain AI tasks, particularly inference, the process of running trained models to generate answers. Guthrie described Maia 200 as “the most efficient inference system Microsoft has ever deployed,” a pointed claim at a time when power consumption has become one of the biggest constraints on AI expansion.

But at a strategic level, Maia 200 reflects a much broader shift across Big Tech. As AI workloads explode, the cost of buying and running Nvidia’s industry-leading GPUs has become a central concern. Demand continues to outstrip supply, prices remain high, and access to the most advanced chips has become a competitive differentiator. Designing custom chips gives hyperscalers more control over costs, performance, and supply chains, while allowing tighter integration with their own software and data center architectures.

Microsoft is not the only Big Tech company toeing this path. Amazon has spent years developing its own processors, including Trainium chips for AI training and Inferentia chips for inference, which it markets as lower-cost alternatives to Nvidia hardware for certain workloads on AWS. Google has long relied on its Tensor Processing Units, or TPUs, which are deeply embedded in its data centers and underpin many of its AI services, including search and generative models.

Meta Platforms has also joined the push, developing its own in-house AI accelerator, known as MTIA, to support recommendation systems and generative AI workloads across Facebook, Instagram, and other services. Apple, while focused more on on-device intelligence than data centers, has built its Neural Engine into iPhones, iPads, and Macs, giving it tight control over how AI features run on its hardware.

Together, these efforts point to a clear trend: AI has become too central, too expensive, and too power-hungry for the largest technology firms to outsource entirely to third-party chipmakers.

Microsoft’s late start in custom silicon compared with Amazon and Google has not diminished its ambitions. The company says it is already designing Maia 300, the next generation of its AI chip, indicating a long-term roadmap rather than a one-off experiment. It also has a fallback option through its close partnership with OpenAI, which is exploring its own chip designs, potentially giving Microsoft access to alternative architectures if needed.

Analysts say energy efficiency is now as important as raw computing power. AI data centers consume vast amounts of electricity, and in many regions, new power generation and grid capacity are not keeping pace. Gartner analyst Chirag Dekate said projects like Maia are becoming essential as power constraints tighten.

“You don’t engage in this sort of investment if you’re just doing one or two stunt activities,” he said. “This is a multigeneration, strategic investment.”

For Microsoft, the implications extend beyond cost savings. Custom chips strengthen its negotiating position with suppliers, reduce exposure to supply shortages, and allow it to tailor hardware more precisely to workloads such as Copilot, Azure AI services, and OpenAI models. Over time, that could translate into more predictable pricing and performance for enterprise customers, a key advantage as businesses scale AI across operations.

Maia 200 does not mean Microsoft is abandoning Nvidia. GPUs will remain critical, especially for the most demanding training tasks. Instead, the chip represents a hedge and a pressure valve, part of a diversified hardware strategy designed to keep AI growth economically viable.

The deployment of Maia 200 reinforces a clear message: Microsoft is no longer content to be just a buyer of AI hardware. It wants to shape the economics of AI computing itself, even as competition intensifies and the cost of staying at the cutting edge continues to rise.