Ambiq Micro, Inc. (“Ambiq^®“), a technology leader in ultra-low power semiconductor solutions for edge AI, today announced compressionKIT™, a next-generation AI-based codec in beta release, proven to substantially reduce the power and memory costs of handling continuous sensor data in wearable and edge devices.

As always-on devices—from medical wearables to smart home and industrial sensors—generate continuous data streams, storing and transmitting that data has become a significant drain on memory, battery life, and system costs. compressionKIT addresses this at the source by compressing data while preserving the key information needed for AI—allowing devices to do more with less.

compressionKIT enhances Ambiq’s edge AI portfolio by solving a key bottleneck: effectively representing sensor data before it is stored, transmitted, or analyzed.

Key Benefits

• Up to 20x data compression¹
  Shrinks continuous sensor streams while retaining the features needed for AI and analytics
• Up to 16x lower on-device memory usage²
  Enables longer data retention and reduces storage requirements
• Reduced transmission power
  Fewer bits sent over the air, which translates to improved battery life
• Multiple inference deployment options
• Supports inference on-device, in the cloud, or across hybrid edge-cloud pipelines using either compressed or reconstructed data
• Configurable compression targets
  Enable developers to optimize trade-offs between data rate, quality, and system constraints

Executive Quote

“For always-on devices, managing sensor data efficiently is just as important as running inference efficiently,” said Dr. Adam Page, Head of AI at Ambiq. “compressionKIT gives developers a practical way to reduce storage and transmission demands while preserving the signal information needed for meaningful AI insights.”

For developers, compressionKIT offers configurable compression targets (2x – 20x) and a visual tuning interface to optimize the balance between data rate and signal quality. The platform supports both hybrid DSP + ML approaches for efficient deployment and AI-first neural compression for maximum data reduction.

compressionKIT is currently in beta testing, with rolling improvements to be released in the coming quarters.

Learn more about compressionKIT here.

About Ambiq

Headquartered in Austin, Texas, Ambiq’s mission is to enable intelligence (artificial intelligence (AI) and beyond) everywhere by delivering the lowest power semiconductor solutions. Ambiq enables its customers to deliver AI compute at the edge where power consumption challenges are the most severe. Ambiq’s technology innovations, built on the patented and proprietary subthreshold power optimized technology (SPOT®), fundamentally deliver a multi-fold improvement in power consumption over traditional semiconductor designs. Ambiq has powered over 290 million devices to date. For more information, visit www.ambiq.com.

Ambiq Micro and the Ambiq logo are registered trademarks of Ambiq Micro, Inc. All other company or product names noted herein may be trademarks of their respective holders.

¹ Baseline assumes uncompressed transmission of raw data. Results were measured on the Apollo510 using two-channel PPG sampled at 64 Hz in 4-second windows. Reported compression combines a fixed 16× reduction from the compressionKIT model with a dynamic entropy encoder, achieving average compression ratios of up to 20× over one minute of data. The data compression ratio at 20x is not deterministic.
² Memory usage reduction is based on internal benchmarking on the Apollo510 of compressed versus uncompressed data storage under the same operating conditions. Actual savings may vary depending on signal characteristics, sampling rates, and application requirements.

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