Your path from LLM evaluation to AI acceleration

Without comprehensive evaluation frameworks, organizations purchasing or building LLMs struggle to align their models with specific use cases, address critical performance gaps, and adapt to evolving industry needs while ensuring scalability and reliability.

Evaluation insights deliver a tailored roadmap to fine-tune an LLM you’re using or optimize an LLM you’re building.

At Turing, we leverage our expertise in LLM evaluation, fine-tuning, and RLHF, combined with scalable training teams, to help you build robust, reliable models that deliver exceptional performance and ROI.

The process begins with a comprehensive evaluation of the LLM’s performance across diverse tasks and datasets to identify gaps and align the model with specific business goals and use cases.

This is followed by targeted retraining techniques, such as fine-tuning or data augmentation, along with iterative testing and validation to ensure the model meets performance benchmarks and real-world demands.

A well-evaluated and fine-tuned LLM that delivers reliable, efficient, and domain-specific performance, aligned with business objectives and ready to tackle real-world challenges.

• Targeted performance improvements: Through techniques like supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF), companies can identify specific strengths and weaknesses to optimize their LLMs, enabling targeted improvements that enhance accuracy, efficiency, and relevance for specific use cases.
• AI-business alignment: Align model performance with specific company goals or domain requirements by assessing and fine-tuning across diverse metrics, real-world scenarios, and expert human data.
• Competitive advantage: Robust evaluation helps prioritize where to invest in fine-tuning, retraining, or dataset creation, saving time and resources while maximizing the return on AI initiatives.

Unlock faster innovation, greater model precision, and more effective problem-solving power to stay ahead in AI development.