Artificial intelligence (AI) and chatbots are revolutionising the way companies and public institutions communicate with their customers and citizens. In this article, we compare the EGOCMS chatbot based on lalamo.cloud technology with the AI chatbot of the Federal Ministry of Research.
AI chatbot of the Ministry of Research
The Federal Ministry of Education and Research's AI chatbot was developed to support project funding and facilitate legally binding decisions. This chatbot uses Retrieval Augmented Generation (RAG) technology to provide reliable information from secure data sources and minimise hallucinations. It was developed in collaboration with open-source companies such as Deepset and is an example of how to reduce bureaucracy and speed up decision-making processes in the public sector. The chatbot relies on open source technologies and uses OpenAI models hosted on AWS and Azure instances. While this enables answers to be provided quickly and efficiently, it raises questions regarding data protection and digital sovereignty, as the data is processed outside of European data protection borders.
EGOCMS chatbot / lalamo.cloud
In contrast, the lalamo.cloud approach of the EGOCMS Chatbot is 100% focussed on data protection and sustainability. Hosting in Germany and the use of open source alternatives such as Llama, Gemma and Mistral ensure a high standard of data protection and minimise resource consumption. Lalamo.cloud relies on local LLMs that are operated on regional infrastructure to reduce dependence on large cloud providers and ensure compliance with European data protection standards.
Advantages of the lalamo.cloud approach
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Local data processing: All data is processed and stored within Germany, which guarantees compliance with strict European data protection regulations (GDPR). This provides companies and users with the assurance that their data will not be transferred to countries outside the EU, where different data protection laws may apply.
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Reduced dependence on cloud providers: The use of local servers and open source models reduces dependence on large cloud providers such as AWS or Azure. This strengthens digital sovereignty and minimises the risk of data breaches and external access to sensitive data.
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Sustainability and resource efficiency: Lalamo.cloud relies on smaller, optimised LLMs that require less computing power and therefore reduce energy consumption and CO₂ emissions. This contributes to a more environmentally friendly IT infrastructure and helps companies to achieve their climate targets. The use of efficient models also enables smaller companies to deploy powerful AI solutions without the need for high operating costs or extensive computing resources.
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Fine-tuning and customisability: The local models can be adapted to the specific requirements and workflows of a company through fine-tuning. This enables efficient and resource-saving use of AI technology that is precisely tailored to the company's needs. Companies can therefore develop customised solutions that optimally support their specific business processes.
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Security and control: By self-hosting the models, companies retain full control over their data and can ensure that all security and compliance requirements are met. This is particularly important for companies that work with sensitive data or have to fulfil strict regulatory requirements.
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Scalability and flexibility: The lalamo.cloud solution offers a flexible and scalable infrastructure that can be adapted to a company's growing needs. Companies can gradually expand and adapt their AI solutions without having to rely on the limitations of cloud providers.
With these advantages, the EGOCMS chatbot based on lalamo.cloud technology offers a powerful, secure and sustainable solution for companies and public organisations that want to automate their communication processes and make them more efficient.