Modular. Small. AI Everywhere

Based on more than 20 years of research, our technology is unprecendented
Stream Analyze specialize in software for scalable real-time analyses of data in motion.

Using a modular approach, our technology allows for us to deploy a very small footprint on to virutally any hardware device available.

The small footprint of our software makes it possible to run it directly on devices and microcontrollers having sufficient memory. There are several options:

  • If there is 7 MB or more available, the entire sa.engine can be run on the device.
  • If there is 1 MB, the core of the engine (sa.core) can run analytics autonomously on the chip, but if certain sa.engine functionality is to be used, such as ad-hoc query processing the full system has to run on a more powerful computer accessing the microcontroller.
  • There is also a very small microinterpreter (sa.microcore) that runs directly on the microcontroller, allowing full functionality when accessing the microcontroller remotely from an sa.engine running on a regular computer. The footprint of this version of our software only requires 101 kB of memory on the chip.

Thus, we can provide analysis truly on the edge, where many other systems only can provide fog computing.

Plug-ins

Our software engine can be extended to include additional functionality where needed. We already provide a magnitude of plug-ins for analysts providing modules for pre- and post processing and data stream models.

Other plug-ins are JVM modules for audio and imaging as well as security, allowing you to use your incumbent security protocols.

Should you alreay have analytical modules that you want to reuse, these can easily be integrated with sa.eninge as a plug-in.

Embeddings

Analysts, Web Designers and Data Scientists can easily extend their current work with our software as it is built for being embedded into bespoke platforms such as Android SDK, Kafka, Azure Hub, Tesorflow and 800xA to name a few. This makes our software independent on other software and operating systems and allowing you to easily deploy and embed into your current software environment.

Superior Performance

sa.engine can be configured for paralellization, which when measured has priovided uncontested measurements using the Linear Road benchmark: www.cs.brandeis.edu/~linearroad.

The Linear Road Benchmark makes it possible to compare performance characteristics of Stream Data Management Systems relative to each other and relative to alternate systems such as relational databases. Stream Data Management Systems process streaming data by executing continuous historical queries while producing query results in real time.