A Private LLM enforces your organization’s privacy and compliance end-to-end while being customized to your workflows and optimized for quality, latency, and cost—with clear auditability and vendor-independent control.

Explore the various ways your company's data can be exposed through the use of LLMs and, more importantly, what you can do to protect it.

A recent court order now requires OpenAI to retain and segregate most ChatGPT user conversations, raising fresh concerns about data privacy and security. As regulations around LLMs continue to evolve, many organizations are exploring private LLM solutions to gain greater control and ownership over their data.

Organizations worldwide are increasingly leveraging powerful open-weights AI models, such as Alibaba’s Qwen and DeepSeek’s R-series, to drive innovation. Yet despite their potential, security practitioners often raise concerns around models originating from China, citing perceived technical security risks linked to national origin. In this article, we'll unpack these security myths, clarify the real risks, and discuss practical approaches your team can use to confidently evaluate and deploy open-weights models: regardless of country origin.

The use of of LLMs is exploding. Many enterprise companies have hesitated to adopt the technology due to security and privacy reasons. Datasaur resolves these concerns in multiple ways. Companies do not have to choose between innovation and security: you can achieve both.

Datasaur empowers AI Agent development with tools for model evaluation, data labeling, and secure deployment, ensuring optimized performance and continuous improvement. It helps businesses build efficient, reliable, and intelligent AI systems.