Why Brain Builder for AITRIOS is a Game-Changer for AI Development Workflows

Building an AI model from scratch is no small task. If you're an AI expert, you already know how complex and time-consuming the process can be—especially when it comes to classification, object detection, and anomaly detection. For those new to AI, the learning curve is even steeper.

Brain Builder for AITRIOS transforms the traditionally complex and resource-intensive development process into something accessible to everyone.

Independent developers, small engineering teams, and small to medium businesses can now build, test, and ship AI vision projects quickly and easily, and without thechallenges and headaches of the traditional approach. Gone are the days of collecting massive datasets, and then going through endless cycles of training, adjustment, and testing. Brain Builder handles these technical challenges automatically. Brain Builder has a clean, logical, and intuitive user interface. The dashboard has a user-friendly design that feels as simple as a photo management app.

When traditional AI workflows often ask for extensive dataset creation, specialized knowledge, and a vast amount of time spent on customization, Brain Builder for AITRIOS helps overcome these challenges and makes it possible for effective models to be trained with as few as 50 images, even for a more complex model for anomaly recognition.

Based on our field experience, Brain Builder for AITRIOS gives substantial time savings in building an AI model. Traditional AI development typically requires a full week for seasoned experts and up to a month for newcomers. Brain Builder dramatically accelerates this timeline. Experienced users can complete projects in just hours, and even first-time users can go from concept to deployed model within a single day.

Let ’s examine both approaches. By comparing the traditional AI workflow to the Brain Builder workflow, you can see exactly how much time and specialized knowledge you can save.

Traditional AI Workflow: What It Takes to Build a Model From Scratch

If you're building an AI model manually, here’s what you need to do:

1. Define Task (Classification, Object Detection, or Anomaly Detection)
   Before you even start, you have to decide what type of AI model you need:
   ・Classification – Categorizing images into predefined labels.
   ・Object Detection – Identifying and localizing objects within an image.
   ・Anomaly Detection – Finding irregularities in images, often for quality control.
   
   
2. Prepare Dataset
   ・You need to source thousands of images from datasets or collect them yourself.
   ・Once collected, you must annotate each image – a process that can take days or weeks depending on the dataset size.
   ・Annotation tools can be expensive and require expertise in labeling data correctly.
   
   
3. Configure AI Model
   ・You must pick the right model version based on accuracy, speed, and size trade-offs
   ・You’ll also need to select a compatible label format for your dataset, as different tools use different formats.
   
   
4. Train AI Model
   ・Training requires high-performance computing power—either a powerful GPU workstation or cloud servers.
   ・You need to configure training parameters, such as:
   　　・Learning rate
   　　・Batch size
   　　・Epochs
   　　・Augmentation settings
   ・You will run multiple training cycles to optimize performance.
   ・Throughout training, you must monitor loss curves to avoid overfitting or underfitting the model.
   
   
5. Convert and Optimize
   ・Once training is complete, you get a floating-point model, which is often too large for edge devices like the IMX500.
   ・You must manually convert the model to a compatible format while balancing file size and accuracy.
   ・If your model isn't optimized for IMX500 from the start, you might have to start over, leading to major delays.
   
   
6. Deploy and Test
   ・Finally, you deploy the model to your hardware (like a Raspberry Pi AI Camera or an embedded system).
   ・If the performance is not satisfactory, you must fine-tune the model, which means going back to Step 3 and repeating the process.

How Long Does This Take?
・An AI expert could do all of this in about a week.
・A beginner with medium AI experience could possibly get a just working model in 3–4 weeks.

Brain Builder Workflow: AI Without the Hassle

Now, let’s see how Brain Builder for AITRIOS simplifies this entire process:

1. DefineTask
   ・Simply choose your task (classification, object detection, or anomaly detection).
   ・Brain Builder uses a pre-configured model tailored to your selected task, ensuring optimal performance without the need for manual selection.
   
   
2. Prepare Dataset
   a) Upload Your Data
   You can train working models with as few as 50-100 images. This opens up possibilities for use cases that would otherwise be too expensive or time-consuming to attempt. It also means that you can quickly validate a concept and then scale up as needed.
   ・Upload your images directly to Brain Builder.
   ・The platform automatically handles dataset splitting (training, testing, and validation).
   ・No need to upload data to the cloud – everything is processed locally on your computer.
   ・You get an evaluation score for your dataset, and information on how to improve it for best training results.
   
   b) Annotate Your Data (If needed)
   The annotation process is designed to be as efficient as possible, turning raw data into practical training sets with minimal efforts.
   ・Use Brain Builder’s built-in annotation tools – no need to rely on third-partytools.
   ・Quickly label images using bounding boxes and classification tags.
   ・For anomaly detection, upload images of “normal” parts and a few images of anomalies to help the model learn effectively.
   
   
3. Train AI Model (Automatically)
   Once you have your labeled images, you select a preset and sit back and let Brain Builder do the heavy lifting. Then you can check the indicators on model accuracy and confidence levels and make decisions about fine-tuning.
   ・No need to manually configure learning rates, batch sizes, or epochs—Brain Builder optimizes these for you.
   ・No worries about overfitting or underfitting—Brain Builder automatically evaluates model performance and suggests improvements.
   ・You control the processing time duration by being able to choose between Quick, Balanced, or Thorough. The longer the processing time, the more optimized for your datasets your AI model is going to be.
   
   
4. Deploy and Test (to IMX500 or Raspberry Pi AI Camera)
   Deployment is as seamless as training. When your model is ready, you hit “Export” and Brain Builder packages it in an archive optimized for the IMX500 intelligent vision sensor from Sony, without needing to write additional code or make complex configurations:
   ・Once training is complete, Brain Builder gives you a ready-to-use model optimized for deployment.
   ・Simply download and push it to your Raspberry Pi AI Camera or IMX500—no complex conversions required.
   

How Long Does This Take?
・Even a beginner can complete the process in 1 day.
・An experienced AI engineer* can finish in a few hours.

*Approximate estimate; varies case by case

Why Choose Brain Builder?

Final Thoughts

Brain Builder for AITRIOS simplifies AI for everyone. For experts, Brain Builder eliminates time-consuming manual tasks that slow down your workflow. For beginners, it removes the steep learning curve typically associated with AI development. Instead of spending weeks on dataset preparation, model architecture decisions, and training parameter optimization, you can focus on what matters: solving real problems with AI.

The Brain Builder process is simple: upload images, apply labels, select your training depth, and deploy. No coding required. No complex configuration necessary.

The latest release of Brain Builder for AITRIOS v25.02 brings many asked-for improvements, making the overall user experience more stable and smoother, and providing a faster and better performance. Two important highlights are that evaluation results can now be exported as a CSV file from the Evaluation panel, and datasets can be exported as training and validation splits, both for dynamic and static uploads, ensuring clear tracking and reproducibility of data used in training.

Another notable feature of the v25.02 release is the extended trial license. You can now try the sophisticated Anomaly Hi-Fi model alongside the previously available Classifier and Detector. The trial period has been extended from 10 to 30 days, so that you will have plenty of time to experiment, fine-tune your models, and test them in real use cases, before committing to a license.

To offer our customers more flexibility, the v25.02 introduces new tiered licensing options as well – Basic, Standard, and Pro plans – to accommodate different project needs and budgets.

AITRIOS combines edge devices equipped with intelligent vision sensors with AI development tools in an integrated platform, empowering teams of all skill levels to build, deploy, and manage vision AI applications at the edge.

Learn more about AI tools and services on AITRIOS