Full-stack
AI Ops.

Systematic assessment of AI model outputs for quality, safety, and alignment.

Human preference data for reinforcement learning from human feedback.

High-accuracy labeling across image, video, text, and audio.

Adversarial testing to surface failure modes and unsafe outputs.

3-tier QA model with gold sets, IAA tracking, and audit logs.

Taxonomy design, guideline authoring, and annotation workflow architecture.