AI Model Training & Fine-Tuning
Taking foundational or raw models and customizing them for specific enterprise tasks.
Reinforcement Learning from Human Feedback (RLHF)
Utilizing human experts to reward and correct model outputs, ensuring safe and aligned AI behavior.
Supervised Fine-Tuning (SFT)
Training models on highly specific, high-quality proprietary datasets to improve performance in niche domains.
Prompt Engineering & Optimization
Designing and refining complex prompt libraries to extract the most accurate, reliable outputs from Large Language Models (LLMs).
Domain Adaptation
Customizing general models (like GPT or open-source equivalents) specifically for industries like legal, medical, or technical customer success.
Human-in-the-Loop (HITL) Training
Continuous model improvement where human operators seamlessly handle edge cases and feed corrected data back into the system.
Express Interest
Discuss your foundational models, proprietary data sets, and deployment goals with an Otuela AI architect.