Embedded AI Coder is a code generator tool that effortlessly converts trained neural networks into optimized C-code for a variety of microcontrollers and microprocessors. Our tool ensures exceptional speed and efficient memory usage, empowering developers to seamlessly integrate AI capabilities into their products.
Your benefits
Any hardware, any tool chain
No need for special libraries and hardware accelerators, Embedded AI Coder generated code can be deployed to any device.
Resource-efficient and cost effective
Minimizing resource consumption on highly constrained embedded systems.
Compliant with relevant safety requirements
Compliant with automotive and functional safety requirements such as ISO26262 and MISRA.
Ease of Use
- Software-as-a-service solution for fast onboarding
- Web UI to upload model, change code generation settings and generated code
- Rest API to call it from your CI/CD toolchain
Broad neural network and hardware support
- The coder works for various target hardware and is compatible with commonly used layers of neural networks: Batchnorm, Convolutions, Depthwise Convolutions, LSTM, Fully Connected, Elementwise Add, Sub, Mul, Softmax, Relu, Leaky Relu, Logistic, Padding, StridedSlice, Tanh, MaxPooling, AveragePooling and TransposeConv. It supports the data types int8 and float32.
- Hardware targets range from tiny microcontrollers to powerful microprocessors with various architectures (ARM Cortex-M, ARM Cortex-A, vendor-specific architectures).
High performance and resource efficiency
- Bosch submitted results at the MLPerf™ Inference Tiny benchmark
- Among state-of-the-art results in all categories
- Best-in-class memory efficiency
See Benchmark portal with comparable tools and background information for comparison.
Safety compliance
- The Embedded AI Coder complies with all automotive and functional safety requirements, such as ISO26262 and MISRA.
- It generates secure, numerically correct code free of runtime errors.
Easy development of embedded C-code
Our Embedded AI Coder builds a bridge between the AI and hardware world, making it possible to generate embedded C-code without the help of embedded software experts. In contrast to handwritten code, it saves companies high development costs and resources. This is particularly advantageous in view of today's typical rapid development cycles and frequently changing code requirements.
Client use cases with our Embedded AI coder
In the automotive industry:
- Cost savings through virtual sensors (i.e., AI algorithms that replace physical sensors) in braking systems, steering systems, engine management, etc.
- Tire pressure monitoring
- Early damage detection
- Driving assistance systems, for example ultrasonic parking sensors
- Driver monitoring systems (mandatory by law from July 2024)
Outside the automotive industry:
- In wearables, for example to monitor vital signs
- In medical devices for health monitoring
Get further information