Fine-tuning
What is fine-tuning?
Fine-tuning optimizes a pre-trained language model (LLM) for specific industry or task requirements by retraining it with a targeted selection of data. This specific adjustment significantly increases the model's accuracy and efficiency when dealing with industry- or task-specific inquiries.
Benefits for your SME
By fine-tuning your language model, you can fully exploit the capabilities of artificial intelligence, thereby significantly improving productivity, efficiency, and accuracy in your SME. Here are the three main benefits that fine-tuning brings to your business:
Control
Fine-tuning gives you more control over how your AI works and what it achieves.
Individualization
Adapt your AI model optimally to the business processes of your SME.
Competitive advantage
By leveraging AI technologies tailored to the needs of both your SMB and your customers, you can differentiate yourself from the competition.
Solution
Customization through Fine-Tuning: Your AI, Your Advantage
Stand out from the crowd with AI solutions that are as unique as your business. Evoya AI's fine-tuning service gives you the opportunity to personalize your AI.
For SMEs, this specifically means that their AI solutions can be tailored not just to their own individual needs but also to those of their customers, leading to improved performance, more effective automation, and increased customer satisfaction.
Step 1
Identifying Needs and Crafting Strategies
The first step involves a detailed needs analysis to understand your business processes and objectives. In this context, we evaluate both the potential uses of the language model in your company as well as the possibilities and limitations of fine-tuning.
Based on this information, we develop an appropriate implementation strategy. In doing so, we define, based on your requirements such as data protection and compliance, whether and how the language model – if not already determined – will be integrated into your existing systems (on-premise) or implemented in the cloud, depending on the need, within or outside Switzerland.
Step 2
Data Preparation and Model Training
In the second step, we focus on selecting and preparing the data needed for training your language model. This includes collecting and analyzing data that reflects your industry specifics and automation requirements. Subsequently, the actual fine-tuning of the model is carried out with this data.
Step 3
Deployment and Continuous Optimization
After the fine-tuning, the language model is integrated into your systems, either on-premise or in the cloud – within or outside Switzerland, based on the strategy defined in step 1.
Furthermore, we offer continuous support and optimization to further improve the model's performance over time and adapt to changing business requirements.
