Artificial Intelligence as a Service (AIaaS) is revolutionising the business world, enabling access to powerful AI tools without the need for in-house development. However, data security and privacy remain a key challenge, especially for companies handling sensitive information.
How to ensure that corporate data does not end up in the public domain when using open solutions such as ChatGPT or Gemini?
Privacy and security: a priority
Enterprise solutions such as Azure Cognitive Services have marked a turning point by offering closed environments where information is kept within the customer’s tenant. At Esferize we already take advantage of this technology to develop customised solutions that guarantee maximum security.
The rise of Open Source LLMs
In recent weeks, open source language models have taken a step forward. Until now, options such as Meta Llama allowed execution in private environments, but new players such as DeepSeek and Qwen are changing the game. Their hardware efficiency and customisability make them very attractive alternatives for the corporate world.
Does this make current models obsolete? Not necessarily.
The evolution of LLMs is likely to follow parallel paths, where the choice between one solution or the other will depend more on commercial than technical factors.
What does this mean for business?
A unique opportunity opens up: install, train and host private AI models to improve operational efficiency. Imagine a system that:
- Be trained with your customer database and commercial catalogue.
- Generate automatic responses in chatbots or voice assistants.
- Create personalised budgets and schedule meetings in any language.
- Automate incident management and even execute corrective actions without human intervention.
