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ElastixAI Enables
The Agent Economy

Instead of forcing developers to conform models to their hardware, ElastixAI delivers 10X+ more tokens / dollar by making hardware to conform to models.

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INFERENCE WITHOUT LIMITS

About Us

ElastixAI co-designs reconfigurable hardware, system software, and model-level optimization as a unified stack. Matching compute to inference demand at every layer, we deliver 10x+ more tokens per dollar with up to 80% lower power consumption.

CURRENT BARRIERS

Three Structural Barriers Limiting AI Inference

GPU architectures were built for training. Deploying them for inference introduces three barriers that no amount of software optimization can fully overcome.

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Solution

No Trade-Off Between Cost, Performance, and Flexibility

When developers design the ML model, system software, and hardware together from the start, they can optimize each layer for the others. The result is lower TCO per token, more tokens per energy, and hardware that stays current as model architectures evolve.

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Cost Efficiency

GPU deployments provision for peak training, but are left running at low utilization during inference.

Using FPGAs, ElastixAI’s solution allocates resources precisely to the arithmetic intensity profile of each model layer, eliminating underutilized capacity and reducing per-token cost by 10x+ compared to equivalent GPU deployments.

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Energy Efficiency

Conventional inference hardware keeps tensor cores and memory subsystems fully powered regardless of demand, burning watts proportional to provisioned capacity rather than actual workload. Because ElastixAI configures substrates to match each inference workload at the hardware level, power draw tracks actual compute demand. The result is up to 80% lower energy consumption per token at production scale.

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Elasticity

Custom silicon takes years and millions of dollars to reach tapeout, and by the time it does, the industry has already passed it by.

FPGAs let developers reconfigure their existing hardware to support new model architectures and optimizations for instant performance and efficiency gains. Deployments stay current, and integration requires only a drop-in PyTorch replacement.

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Run Your Workload. See the Numbers.

Run Your Workload. See the Numbers.

Get hands-on with our automated full-stack hardware co-design and see the difference for yourself.

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Get hands-on with our automated full-stack hardware co-design and see the difference for yourself.

Join waitlist

ElastixAI Articles

Blog
The AI Data Center Economy Runs on Tokens per Second per Watt
The AI Data Center Economy Runs on Tokens per Second per Watt

In early 2026, Microsoft disclosed an $80 billion unfulfilled Azure order backlog due to insufficient electricity to power the deployments. CEO Satya Nadella confirmed on the record that their GPUs are sitting idle in inventory, waiting for installations that can’t proceed until the grid can deliver the load.

Read more →
What Becomes Possible With 100x More Tokens?
What Becomes Possible With 100x More Tokens?

What if we could generate 100x more tokens for the same budget? What new possibilities and world-changing applications would open up if the cost of AI stopped being the deciding factor?

Read more →
Why AI Inference Could Be the Next Global Energy Crisis
Why AI Inference Could Be the Next Global Energy Crisis

The AI revolution has officially entered the stage of massive-scale deployment. But as organizations scale AI-powered applications to serve billions of daily queries, they are quickly finding that energy consumption is threatening their efforts.

Read more →
The Inference Economy: LLM Inference Is Everywhere, Not Just in Your Chatbot
The Inference Economy: LLM Inference Is Everywhere, Not Just in Your Chatbot

When most people think of Large Language Models (LLMs), they think of chatbots. However, this perspective drastically understates the true scope and technical necessity of the inference market. Inference is much more than typing a prompt and receiving a response. In reality, it’s become a basic compute primitive that powers the entire AI lifecycle.

Read more →
Blog
The AI Data Center Economy Runs on Tokens per Second per Watt
The AI Data Center Economy Runs on Tokens per Second per Watt

In early 2026, Microsoft disclosed an $80 billion unfulfilled Azure order backlog due to insufficient electricity to power the deployments. CEO Satya Nadella confirmed on the record that their GPUs are sitting idle in inventory, waiting for installations that can’t proceed until the grid can deliver the load.

Read more →
What Becomes Possible With 100x More Tokens?
What Becomes Possible With 100x More Tokens?

What if we could generate 100x more tokens for the same budget? What new possibilities and world-changing applications would open up if the cost of AI stopped being the deciding factor?

Read more →
Why AI Inference Could Be the Next Global Energy Crisis
Why AI Inference Could Be the Next Global Energy Crisis

The AI revolution has officially entered the stage of massive-scale deployment. But as organizations scale AI-powered applications to serve billions of daily queries, they are quickly finding that energy consumption is threatening their efforts.

Read more →
The Inference Economy: LLM Inference Is Everywhere, Not Just in Your Chatbot
The Inference Economy: LLM Inference Is Everywhere, Not Just in Your Chatbot

When most people think of Large Language Models (LLMs), they think of chatbots. However, this perspective drastically understates the true scope and technical necessity of the inference market. Inference is much more than typing a prompt and receiving a response. In reality, it’s become a basic compute primitive that powers the entire AI lifecycle.

Read more →

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