Custom AI Solutions

The timeline varies based on the complexity and scope of the project. It typically involves several stages, including data collection, data cleaning, model development, testing, and deployment. For simpler projects, this process may take 8-12 weeks. However, more complex projects, such as those involving large datasets, multi-layered models, or edge device optimization, can take several months. The exact duration depends on factors like data quality, the need for model refinement, and system integration requirements.

For a more accurate estimate, request a free consultation to discuss your specific needs.

Custom AI solutions require high-quality data relevant to the problem you’re solving. This can include structured data (databases, spreadsheets) ideal for tasks like classification or predictive modeling and unstructured data (images, audio, video) used for tasks like image recognition, NLP, or audio classification.

We will help you analyze the data you have available and assess its suitability. If the data is insufficient, we can assist with data collection strategies.

Data doesn’t need to be pre-cleaned—our team handles data cleaning and preparation, ensuring it’s properly formatted and ready for model training.

Additionally, for Edge AI, data may need to be optimized for real-time, low-power environments, which we will manage as part of the process

Our AI Solution service provides end-to-end support across the entire AI lifecycle, including:

• Data collection and analysis: We assist in gathering and assessing the quality and relevance of the data required for your AI solution.
• Data cleaning and preparation: We take care of all data preprocessing tasks, ensuring the data is properly formatted and ready for model training.
• Custom AI model development: We design AI models tailored to your specific needs, ensuring they are optimized for your use case.
• Model validation and testing: We rigorously test the model for accuracy, performance, and reliability before deployment.
• Model deployment: We integrate the AI model into your existing systems or deploy it to edge devices seamlessly.
• Optimization for edge devices: We fine-tune the AI model to ensure it runs efficiently within the power, memory, and processing constraints of edge devices.
• Ongoing monitoring and refinement: After deployment, we continuously monitor the model’s performance and provide updates or optimizations as needed.
• Support, training, and documentation: We offer comprehensive support, training for your team, and detailed documentation to ensure you can manage and maintain the AI solution effectively.

Our AI solutions are compatible with a wide range of hardware and platforms, ensuring flexibility and seamless integration. We support:

• Edge devices: Including , smartphones, cameras, IoT devices, industrial sensors, web browsers via web assembly.
• Hardware platforms: Such as Raspberry Pi 4/5, Nvidia Jetson, NXP iMX8, Synaptics Astra Machina and similar embedded systems.
• Operating systems: macOS, iOS, Android, Linux (Ubuntu x86, x86/CUDA), and Windows.
• Cloud platforms: Integration with leading cloud services like AWS, Google Cloud, and Microsoft Azure for hybrid AI solutions.

If your hardware or platform isn’t listed, feel free to contact us for a custom solution tailored to your specific setup.