NEW YORK, April 29, 2026 /PRNewswire/ — Squads today announced an $18 million strategic round led by Solana Ventures, with participation from Coinbase Ventures, Haun Ventures, L1D, Collab+Currency, Electric Capital, Placeholder, Jump Crypto, and Robot Ventures, bringing total funding to $42.9M. This raise accelerates Altitude, a financial operating system built on stablecoin infrastructure.

Stablecoins are changing the infrastructure of business finance. For the last decade, building financial products for businesses meant building on top of banks – bank partnerships were required to hold customer funds and access payment rails. Every new market meant a new bank and a new compliance cycle. Blockchains changed the underlying infrastructure. Stablecoins turned money into software, allowing treasury and payments to be separated from the fractional reserve system for the first time.

This separation has produced a new category of licensed Payment Service Providers (PSPs) that move money across both stablecoin and traditional banking rails. The market has moved quickly: Stripe acquired Bridge for $1.1 billion, Mastercard acquired BVNK for $1.8 billion. These PSPs were the missing piece to build a full-stack financial operations platform on stablecoin rails.

Altitude is built on this shift. It does not hold customer funds. Treasury is held in stablecoins. When funds need to move, they settle on stablecoin rails instantly, 24/7, at low cost. When they need to reach traditional banking rails, they do so through a network of licensed stablecoin PSPs.

Since publicly launching in December 2025, Altitude has processed over $200 million in payments for exporters, global agencies, crypto-native companies, and cross-border remote teams. Customers choose Altitude for what stablecoin infrastructure unlocks: global-by-default coverage, multi-currency support, instant settlement, and programmable controls. With $18M in new funding, Altitude is growing its team, expanding its payment network, and accelerating product development.

“This raise backs a simple idea: businesses are better off running on stablecoins than on legacy banking infrastructure. Solana is now mature enough to carry global business finance, regulators have built the frameworks to support it, and for the first time you can build a full financial platform on a genuinely new system,” said Stepan Simkin, CEO of Squads.

“The Squads team spent the last four years building the security infrastructure that most of the Solana ecosystem runs on. Stablecoins and programmable blockchains are changing how global finance works. This is the team with the technical depth and the vision to build the financial platform that sits on top of that shift. We believe Altitude will be how the next generation of global businesses runs their financial operations,” said Matthew Beck, Head of Solana Ventures.

Two criticisms have historically limited stablecoin adoption in mainstream business finance: compliance gaps and security concerns. Altitude addresses both directly.

On compliance, Altitude has built a proprietary engine that imposes the same checks expected from any regulated fintech: continuous sanctions screening, AML checks, transaction monitoring, and KYB verification. This engine enables every Altitude account to plug into licensed PSPs including Bridge, MoonPay, Infinite, Due, and others for global coverage.

On security, Altitude enforces controls at each layer of the stack. At the product layer, every business account comes with programmable controls, granular permissions, and configurable multifactor authentication. At the infrastructure layer, Squads Protocol handles asset custody and money movement, securing over $10 billion in value. At the settlement layer, every transaction is recorded and settled on Solana.

“As we scaled, treasury and payments turned into an operational headache. Complexity and fees kept compounding. Altitude removed both,” said Kash Dhanda, COO, Jupiter.

About Squads

Squads is a financial infrastructure company building on Solana. The company operates two products: Squads Multisig, the smart account standard securing over $10 billion in assets across the Solana ecosystem, and Altitude, a financial operating system that gives businesses multi-currency accounts, corporate cards, global payments, APY on balances, and a CFO stack to run it all. Learn more at altitude.xyz or squads.xyz.

View original content:https://www.prnewswire.co.uk/news-releases/squads-raises-18m-to-build-business-finance-on-stablecoin-infrastructure-302757566.html

NEW YORK, April 29, 2026 /PRNewswire/ — Squads today announced an $18 million strategic round led by Solana Ventures, with participation from Coinbase Ventures, Haun Ventures, L1D, Collab+Currency, Electric Capital, Placeholder, Jump Crypto, and Robot Ventures, bringing total funding to $42.9M. This raise accelerates Altitude, a financial operating system built on stablecoin infrastructure.

Stablecoins are changing the infrastructure of business finance. For the last decade, building financial products for businesses meant building on top of banks – bank partnerships were required to hold customer funds and access payment rails. Every new market meant a new bank and a new compliance cycle. Blockchains changed the underlying infrastructure. Stablecoins turned money into software, allowing treasury and payments to be separated from the fractional reserve system for the first time.

This separation has produced a new category of licensed Payment Service Providers (PSPs) that move money across both stablecoin and traditional banking rails. The market has moved quickly: Stripe acquired Bridge for $1.1 billion, Mastercard acquired BVNK for $1.8 billion. These PSPs were the missing piece to build a full-stack financial operations platform on stablecoin rails.

Altitude is built on this shift. It does not hold customer funds. Treasury is held in stablecoins. When funds need to move, they settle on stablecoin rails instantly, 24/7, at low cost. When they need to reach traditional banking rails, they do so through a network of licensed stablecoin PSPs.

Since publicly launching in December 2025, Altitude has processed over $200 million in payments for exporters, global agencies, crypto-native companies, and cross-border remote teams. Customers choose Altitude for what stablecoin infrastructure unlocks: global-by-default coverage, multi-currency support, instant settlement, and programmable controls. With $18M in new funding, Altitude is growing its team, expanding its payment network, and accelerating product development.

“This raise backs a simple idea: businesses are better off running on stablecoins than on legacy banking infrastructure. Solana is now mature enough to carry global business finance, regulators have built the frameworks to support it, and for the first time you can build a full financial platform on a genuinely new system,” said Stepan Simkin, CEO of Squads.

“The Squads team spent the last four years building the security infrastructure that most of the Solana ecosystem runs on. Stablecoins and programmable blockchains are changing how global finance works. This is the team with the technical depth and the vision to build the financial platform that sits on top of that shift. We believe Altitude will be how the next generation of global businesses runs their financial operations,” said Matthew Beck, Head of Solana Ventures.

Two criticisms have historically limited stablecoin adoption in mainstream business finance: compliance gaps and security concerns. Altitude addresses both directly.

On compliance, Altitude has built a proprietary engine that imposes the same checks expected from any regulated fintech: continuous sanctions screening, AML checks, transaction monitoring, and KYB verification. This engine enables every Altitude account to plug into licensed PSPs including Bridge, MoonPay, Infinite, Due, and others for global coverage.

On security, Altitude enforces controls at each layer of the stack. At the product layer, every business account comes with programmable controls, granular permissions, and configurable multifactor authentication. At the infrastructure layer, Squads Protocol handles asset custody and money movement, securing over $10 billion in value. At the settlement layer, every transaction is recorded and settled on Solana.

“As we scaled, treasury and payments turned into an operational headache. Complexity and fees kept compounding. Altitude removed both,” said Kash Dhanda, COO, Jupiter.

About Squads

Squads is a financial infrastructure company building on Solana. The company operates two products: Squads Multisig, the smart account standard securing over $10 billion in assets across the Solana ecosystem, and Altitude, a financial operating system that gives businesses multi-currency accounts, corporate cards, global payments, APY on balances, and a CFO stack to run it all. Learn more at altitude.xyz or squads.xyz.

View original content:https://www.prnewswire.co.uk/news-releases/squads-raises-18m-to-build-business-finance-on-stablecoin-infrastructure-302757566.html

What is the Market Size of Processing in-Memory AI Chips?

BANGALORE, India, April 29, 2026 /PRNewswire/ — The global Processing in-memory AI Chips market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.

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What are the key factors driving the growth of the Processing in-Memory AI Chips Market?

The processing in-memory AI chips market is expanding due to growing pressures on compute architectures from data movement inefficiency, latency constraints, rising power sensitivity, and deployment cost control across AI workloads.Demand is shifting toward chip designs that minimize the distance between memory and computation, enabling faster inference execution and better throughput under constrained thermal and energy conditions.This trend is especially relevant for workloads where bandwidth pressure, response time, and local processing efficiency directly determine system value.The market benefits from broader interest in architectures supporting both edge and data center AI tasks, without full reliance on conventional processor-memory separation.These factors create a strong commercial foundation for processing in-memory adoption.

Source from Valuates Reports: https://reports.valuates.com/market-reports/QYRE-Auto-15O17238/global-processing-in-memory-ai-chips

TRENDS INFLUENCING THE GROWTH OF THE PROCESSING IN-MEMORY AI CHIPS MARKET:

DRAM-PIM is driving growth in the processing in-memory AI chips market by addressing one of the most persistent bottlenecks in AI computing, which is the heavy cost of transferring data between memory and logic. By embedding compute capability closer to high-capacity memory structures, DRAM-PIM improves efficiency in bandwidth-intensive inference and parallel data handling environments. This makes it highly relevant for larger models and workloads that require sustained access to large datasets with lower latency overhead. Its role in improving throughput while reducing external data shuttling is strengthening its position in advanced AI infrastructure, particularly where performance scaling must happen without proportionate increases in power draw or board-level complexity.

SRAM-PIM is supporting market growth by serving AI use cases that prioritize low latency, fast local access, and power-efficient computation in compact environments. Its architectural suitability for tightly coupled memory and processing enables faster execution of inference tasks where response speed is critical and repeated memory access patterns are concentrated. This makes SRAM-PIM especially attractive in edge AI systems, embedded intelligence platforms, and applications where energy budgets and footprint limitations are decisive purchase factors. As device-side intelligence becomes more valuable across industrial, consumer, and autonomous systems, SRAM-PIM is gaining traction as a practical route to delivering on-chip efficiency without the penalties associated with conventional memory-transfer-heavy architectures.

In-memory processing chips are driving the growth of the processing in-memory AI chips market by creating a more application-aligned hardware approach for modern AI inference. Their appeal lies in improving usable performance per watt, reducing system bottlenecks, and enabling more scalable deployment economics across both small and large computing power environments. These chips are increasingly viewed as a structural response to the limitations of traditional architectures in handling AI workloads efficiently. As buyers seek solutions that can balance throughput, heat, latency, and integration flexibility, in-memory processing chips are moving from niche experimentation toward broader commercial adoption, supporting a market that is increasingly defined by workload efficiency rather than raw compute expansion alone.

A major factor supporting the market is the growing need to reduce the cost of data movement inside AI systems. In conventional architectures, moving data back and forth between memory and processors consumes time, power, and system resources. Processing in-memory chips directly address this problem by bringing computation closer to stored data. This improves execution efficiency and makes the architecture attractive for inference-heavy environments where repetitive data access creates performance drag. As buyers increasingly evaluate compute systems based on usable efficiency rather than nominal processing strength, demand for architectures that minimize data transport overhead continues to strengthen the market.

Power efficiency is emerging as a decisive growth factor for the processing in-memory AI chips market. AI deployment is no longer limited to environments where power availability is secondary. Enterprises, edge operators, and embedded system developers now require hardware that can support meaningful intelligence under tight energy and thermal budgets. Processing in-memory designs improve energy utilization by reducing unnecessary memory access traffic and enabling more efficient task execution. This gives them strong relevance in a market where lower operating cost, thermal manageability, and sustained performance matter as much as raw computational output, especially across continuously running inference systems and distributed AI infrastructure.

The expansion of edge AI is supporting market growth by increasing demand for chips that can perform inference closer to the source of data. Edge systems need fast decision-making, low energy consumption, and compact integration, all of which align well with processing in-memory designs. As intelligence moves into cameras, sensors, industrial devices, and smart endpoints, conventional architectures often face efficiency tradeoffs that reduce suitability in such environments. Processing in-memory chips help overcome these limitations by supporting local computation with lower latency and reduced data transfer dependency. This makes the technology increasingly relevant as edge intelligence shifts from optional capability to essential product differentiation.

The growing complexity of AI inference workloads is creating favorable conditions for processing in-memory adoption. As models become more memory-intensive and inference demand spreads across commercial applications, the limitations of traditional compute-memory separation become harder to ignore. Buyers are looking for architectures that can handle repeated memory access more efficiently and sustain performance under real deployment conditions. Processing in-memory chips respond to this need by improving memory interaction efficiency, which is particularly valuable in workloads where bandwidth and latency determine real-world usefulness. This shift is helping the market as hardware decisions become increasingly shaped by inference practicality rather than theoretical compute scale.

The market is also benefiting from a growing emphasis on cost-per-inference rather than simple peak performance comparisons. Buyers increasingly want AI hardware that can deliver consistent workload execution with better efficiency, lower supporting infrastructure requirements, and more practical deployment economics. Processing in-memory chips are well positioned in this context because they help reduce some of the overhead traditionally associated with memory bottlenecks, energy consumption, and system complexity. Their value proposition becomes stronger when purchasing decisions are based on long-term operating efficiency and scalable deployment. This cost discipline is pushing interest toward architectures that offer more balanced performance across real commercial use cases.

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What are the major product types in the Processing in-memory AI Chips Market?

DRAM-PIMSRAM-PIM

What are the main applications of the Processing in-memory AI Chips Market?

Near-Memory Computing (PNM) ChipIn-Memory Processing (PIM) ChipIn-Memory Computing (CIM) Chip

Key Players in the Processing in-memory AI Chips Market:

MyhticSyntiantD-MatrixHangzhou Zhicun (Witmem) TechnologyBeijing Pingxin TechnologyAistarTekSAMSUNGSK HynixShenzhen Reexen TechnologyGraphcoreAxelera AISuzhou Yizhu Intelligent TechnologyBeijing Houmo TechnologyEnCharge AI

Which region dominates the Processing in-memory AI chips market?

Asia-Pacific remains the most dynamic region due to its deep semiconductor ecosystem, expanding edge device manufacturing base, strong memory technology orientation, and increasing integration of AI into consumer and industrial electronics. China is supporting market formation through locally aligned compute architecture development, while South Korea, Japan, and Taiwan provide supply-side depth through memory and advanced chip ecosystem capabilities. Other regions are adopting more gradually, mainly through selective edge AI and infrastructure modernization use cases.

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What are some related markets to the Processing in-memory ai chips market?

Computing in Memory Technology Market was valued at USD 268 Million in the year 2024 and is projected to reach a revised size of USD 175260 Million by 2031, growing at a CAGR of 154.7% during the forecast period.In-memory Computing Chips for AI market was valued at USD 231 Million in 2025 and is anticipated to reach USD 44335 Million by 2032, at a CAGR of 112.4% from 2026 to 2032.HTAP-Enabling In-Memory Computing Technologies MarketIMDG (In-Memory Data Grid) Software Market Research ReportEmbedded Ai Chips Market Research ReportUltra-low Power AI Chips Market Research ReportHigh-Bandwidth Memory Chips Market was valued at USD 3816 Million in the year 2024 and is projected to reach a revised size of USD 139450 Million by 2031, growing at a CAGR of 68.2% during the forecast period.LPDDR Chips Market was valued at USD 6891 Million in the year 2024 and is projected to reach a revised size of USD 10870 Million by 2031, growing at a CAGR of 6.8% during the forecast period.Semiconductor Memory Market was valued at USD 125890 Million in the year 2024 and is projected to reach a revised size of USD 232900 Million by 2031, growing at a CAGR of 9.3% during the forecast period.AI Calculus Chips Market was valued at USD 46520 Million in the year 2024 and is projected to reach a revised size of USD 269300 Million by 2031, growing at a CAGR of 25.1% during the forecast period.Military Chips Market was valued at USD 1168 Million in the year 2024 and is projected to reach a revised size of USD 1583 Million by 2031, growing at a CAGR of 4.5% during the forecast period.

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