How organizations use customized AI to protect data and increase efficiency

In the current AI era, we see an increasing need for specialized AI solutions for businesses. While large language models like ChatGPT and Gemini have made impressive progress, they often lack the specific knowledge that companies require. Moreover, concerns about data privacy and security are rising. How can organizations optimally utilize AI without exposing sensitive information? The answer lies in customized AI models.

The power of your own data

Companies are increasingly developing smaller, customized AI models that utilize their own unique datasets. A promising technique in this regard is Retrieval-Augmented Generation (RAG). This method links general AI models to company-specific knowledge sources, such as product data and customer service protocols. This allows organizations to create AI applications that precisely align with their needs, without sharing sensitive information with external parties.

Synthetic Data as a Solution

One of the biggest challenges in developing custom AI is collecting and preparing the right training data. This process can be time-consuming and costly, especially in highly regulated industries. Synthetic data offers a solution here.

By using AI techniques to generate realistic but artificial datasets, companies can quickly obtain the necessary training data. Delta Electronics, a leader in power management, has successfully applied this approach. They reduced their process for generating training data from days to just 10 minutes.

The Future of Business AI

Smaller, customized AI models offer a balanced solution to the privacy issue in AI. They can access local data, run on internal infrastructure, and thus reduce dependence on external servers. This not only enhances security but also leads to cost savings.

To lower the threshold for developing custom AI, companies can form partnerships for access to base models, AI workflows, and synthetic data generation tools. By customizing their own models, organizations benefit from faster AI implementation and improved data security, while still leveraging the full power of AI.

The future of business AI lies in customization. By intelligently utilizing proprietary data and innovative techniques such as RAG and synthetic data, companies can create AI solutions that perfectly align with their unique needs while simultaneously protecting their valuable trade secrets.