AI Creative Effectiveness (ACE) uses artificial intelligence to analyze creative performance patterns and provide pre-launch scoring and recommendations. By learning from your past campaigns, ACE extracts brand-specific success drivers and applies them to new assets—checking brand/platform compliance, predicting performance, and suggesting edits before you go live. This pre-optimization approach helps teams prioritize high-potential assets and fix issues early, reducing costly revisions and improving campaign outcomes.

Semantic & Intent Fusion Targeting (SIFT) represents the next generation of contextual advertising. Instead of relying solely on keywords or legacy segments, SIFT uses pre-computed LLM-derived embeddings to understand page content and user intent at programmatic speed. By querying billions of URLs and anonymized behavioral signals through fast vector similarity search, SIFT adds high-propensity semantic signals to standard RTB inputs—without the latency of in-auction LLM inference.

AI Uncovering Responsive Audiences (AURA) is a breakthrough AI-first audience discovery and optimization program. Using advanced pattern recognition across behavioral, demographic, and transactional data, AURA continuously identifies and upweights high-response micro-segments that traditional targeting methods miss. Early pilots demonstrate an average 22% lift with no creative changes and minimal workflow impact—just split your audience lines and let AI optimize weekly.