Ambiq Micro, Inc. (“Ambiq®“), a technology leader in ultra-low power semiconductor solutions for edge AI, 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
“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.
Ambiq Micro, Inc. | ambiq.com
Sponsor this Article
Kirsten Campbell is a Marketing Tornado and junk robot of information. Analytical and creative, she has been in marketing and communications since 2008 and worked with everyone from small businesses to your favorite household names.
Ask her about the time she made a numismatics blog interesting (yes, really) or wrote an obit for a family she never met.
An ardent admirer of corporate snark played out online, Kirsten loves Reese’s peanut butter cups and still isn't over the Mars Rover.
