
Custom generative AI model fine-tuning
We fine-tuned advanced models such as Llama 3 and Mistral using the client’s own data. This made the models highly accurate and personalized, while continuous learning improved their performance over time.

Models fine-tuned
Llama 3 & MistralProprietary data integrated
12M+ user interactionsEngagement impact
+35% retentionDynamiq, a European generative AI platform, scaled rapidly as users demanded sharper personalization and higher performance. Competitors shipped generic models, but those models missed context and failed to meet the accuracy and relevance Dynamiq required.
To maintain their competitive edge, Dynamiq needed a strategy that protected both revenue and agility. This required building fine-tuned models on proprietary data (such as Llama 3 and Mistral), integrating them smoothly into the main product, ensuring reliable scalability with clear SLAs, and upholding strict GDPR and partner data compliance.
Relevant Software designed and executed that strategy. We conducted focused discovery and data audits, defined the model roadmap, and built a secure cloud infrastructure with strong privacy safeguards. Success was measured against key business KPIs like retention, ARPU, and support ticket volume. The outcome improved personalization, ensured ongoing regulatory compliance, and enabled seamless scaling without service interruptions.
Vitalii DukFounder & CEO, DynamiqTheir commitment to transparency and client involvement ensured that we were always on the same page.

We fine-tuned advanced models such as Llama 3 and Mistral using the client’s own data. This made the models highly accurate and personalized, while continuous learning improved their performance over time.

Our engineers developed automated pipelines that collect, clean, and structure millions of records daily. This ensured models were trained on high-quality, relevant data, reinforcing the client’s data-driven advantage.

We integrated the AI models seamlessly into the client’s existing platform without disruption. Secure APIs made deployment and scaling easy while maintaining stable operations.

The system was designed to grow with user demand and to easily adopt new AI technologies in the future. This keeps the platform flexible and cost-efficient.

We automated data retrieval and content generation. As a result, teams spent less time on manual work and delivered insights faster, boosting overall productivity.

60% boost in personalization accuracy
60% boost in personalization accuracyA/B testing showed that fine-tuned Llama 3 and Mistral models improved recommendation accuracy by 60%, increasing the relevance of content and user satisfaction.
3× growth in active user engagement
Six months after launch, the number of daily active users interacting with AI-powered features tripled, driven by faster response times and enhanced output quality.
25% savings in infrastructure costs
Migrating model training and inference to a scalable AWS cloud cut operating costs by 25% while keeping performance strong as the system grew.
✓ Fine-tuned Llama 3 and Mistral on proprietary datasets for superior accuracy and personalization
✓Delivered training pipelines, scalable cloud deployment, and a continuous improvement framework
✓Built APIs for smooth deployment and compatibility with the current infrastructure
✓Applied encryption, audit logs, and secure storage to meet regulatory standards
✓Boosted engagement, streamlined operations, and reinforced Dynamiq’s competitive advantage
Vitalii DukFounder & CEO, Dynamiq“Partnering with Relevant Software has been a game-changer for us. The team’s strategic insight, technical prowess, and support have been instrumental in the success of our initiatives.”
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