The Missing Layer of AI

The Missing Layer of AI

The Missing Layer of AI

Specialty AI Memory placed at proximity to AI accelerators. Ultra-Fast. Dirt Cheap. Cooler

Specialty AI Memory placed at proximity to AI accelerators. Ultra-Fast. Dirt Cheap. Cooler

Specialty AI Memory placed at proximity to AI accelerators. Ultra-Fast. Dirt Cheap. Cooler

The product

System-specific, co-designed AI memory, placed at proximity to AI accelerators

System-specific, co-designed AI memory, placed at proximity to AI accelerators

System-specific, co-designed AI memory, placed at proximity to AI accelerators

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0x

0x

0x

0x

0x

Faster access

Faster access

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0%

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Cost reduction

Cost reduction

Minor Heat

Minor Heat

Minor Heat

vs HBM

vs HBM

The $700B problem

Why settle for the memory bottleneck?


The most powerful AI processors spend the majority of their time doing nothing.
They are waiting for data from memory that cannot keep up.
HBM was supposed to fix this, but demand now outpaces supply, costs have exploded, and three manufacturers control the market


The most powerful AI processors spend the majority of their time doing nothing.
They are waiting for data from memory that cannot keep up.
HBM was supposed to fix this, but demand now outpaces supply, costs have exploded, and three manufacturers control the market


The most powerful AI processors spend the majority of their time doing nothing.
They are waiting for data from memory that cannot keep up.
HBM was supposed to fix this, but demand now outpaces supply, costs have exploded, and three manufacturers control the market

HBM demand will continue to grow

HBM demand will continue to grow

130%+ YoY Growth, with 70%+ growth continuing into 2026.

Capacity is limited

Capacity is limited

Sold Out Through 2026. All three major manufacturers fully allocated.

Sold Out Through 2026. All three major manufacturers fully allocated.

Costs keep climbing

Costs keep climbing

60 to 80% of GPU BOM consumed by HBM and CoWoS packaging alone.

60 to 80% of GPU BOM consumed by HBM and CoWoS packaging alone.

Investments continue to rise

Investments continue to rise

$700B+ projected AI infrastructure spend by Amazon ~$200B,
Google ~$180B,
Meta ~$125B,
Microsoft ~$145B

$700B+ projected AI infrastructure spend by Amazon ~$200B,
Google ~$180B,
Meta ~$125B,
Microsoft ~$145B

How to use Memstak Specialty Memory

Two Paths Forward
Different integration paths give you flexibility based on your roadmap

Path 1: Alongside HBM

Keep your current HBM investment while expanding capacity and speed.

  • High bandwidth,
  • 100GB+ capacity,
  • Ultra fast access,
  • At a cost that undercuts HBM by an order of magnitude.

Supercharge your existing setup without touching what already works.

Path 2: Replace HBM

Path 2: Replace HBM

For next generation designs where cost and power efficiency are paramount.

  • Enhanced bandwidth,
  • 200GB+ added capacity,
  • Ultra fast access,
  • Dramatically lower cost per gigabyte.
  • Enhanced bandwidth,
  • 200GB+ added capacity,
  • Ultra fast access,
  • Dramatically lower cost per gigabyte.

The path for organizations that want to leap ahead rather than iterate.

Whether you augment or replace, the result is the same:
a faster, cheaper, cooler AI system that does not depend on constrained HBM supply chains.

Whether you augment or replace, the result is the same:
a faster, cheaper, cooler AI system that does not depend on constrained HBM supply chains.
Bridging the Performance Gap

Optimized for the Most Demanding AI Workloads

5-5x

5-5x

5-5x

5-5x

5-5x

5-5x

Faster token generation for LLM inference

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0x+

Speedup for Massive Context Windows

1.5-2x

1.5-2x

1.5-2x

1.5-2x

1.5-2x

1.5-2x

Faster AI training via higher GPU utilization

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Projected gains when entire model fits in Memstak memory.
Detailed benchmarks and methodology may be provided during further in-depth conversations
Maximum efficiency, minimum footprint

Thermal & Power Efficiency

Current state

Heat Is Throttling Your Performance

HBM's thermal overhead creates a cascade of hidden costs that never appear on the chip spec sheet.

Cooling infrastructure often rivals the cost of the accelerators themselves

Rising temperatures force GPUs to throttle, capping sustained throughput

Memory reliability degrades as system heat increases

With Memstak

Less Energy Per Access

At data center scale, that difference compounds into measurably lower power bills and denser GPU configurations.

Power draw per memory operation drops by 10x

Reduced cooling demand across the entire facility

Run denser configurations without hitting thermal limits

Enhance your thermals

Architectural Agility

Current state

Upgrades Locked to the Next Chip Cycle

Improving memory performance today means waiting years and rebuilding from the silicon up.

New HBM generation requires interposer redesign

Full package re-qualification adds months to timeline

Performance gains are locked behind the next product cycle

With Memstak

Current Generation Upgrades

Memstak integrates at the package level on your existing timeline and architecture.

No new interposer required

No full package re-qualification cycle

What would be a next-gen improvement becomes a current gen upgrade

Integrate with your schedule

A different level of knowledge

Built on 25+ Years of Stacked Memory Expertise
Engineered to define AI's next era.

An emerging memory vendor bypassing major memory companies with

System-Specific, Co-Designed AI Memory products for AI accelerators

25+
25+
25+

years of accumulated experience in stacked specialty memory

A product company, not providing IP licensing

Headquartered in Hillsboro, Oregon, in the heart of Silicon Forest.

Discover Your Next Gen Performance Multiplier

Explore how our proprietary specialty memory can improve your throughput at a lower cost.

Whether you are evaluating memory alternatives for a next generation accelerator or optimizing an existing deployment, our engineering team is available for technical discussions and detailed performance projections tailored to your workload.

Contact us

Advancing the architecture of AI
©2026 Memstak Inc. All rights reserved.
Advancing the architecture of AI
©2026 Memstak Inc. All rights reserved.