Others forecast the outcome. We model and influence the behavior that creates it. SignalsScience tells you who will buy, and exactly what to do to make them buy.
Enterprises can record, activate, and generate, but still struggle to predict behavioral response before action. Teams act before they can reliably forecast what the buyer will do.
Signals become useful when they are connected to behavior and decisions. Behavior intelligence models the full communication loop: sender, message, channel, receiver, context, and observed effect.
Explore selected publications across four connected areas of inquiry.
How models represent, learn, and predict human actions and responses.
Proposes a unified architecture that learns from content and behavioral signals together, supporting tasks that connect what people encounter with how they respond.
View paperStudies whether behavioral supervision can improve how vision-language models understand content, using human responses as an additional learning signal.
View paperExplores action-based learning as a way to represent diverse human preferences and align model predictions with pluralistic patterns of behavior.
View paperInvestigates synthesized eye-tracking signals as supervision for natural-language models, connecting patterns of human attention with language understanding.
View paperHow language, visual content, and communication strategies influence attention, interpretation, and choice.
Analyzes the strategies used in advertisements and examines how persuasive appeals can be identified across visual and textual content.
View paperDevelops methods for evaluating persuasive model outputs and studies how generative models can be trained against explicit measures of persuasiveness.
View paperExamines the visual and semantic characteristics associated with long-term advertising recall and explores methods for generating more memorable creative.
View paperHow content and interventions can adapt to different people, contexts, and behavioral patterns.
Introduces a zero-shot method that verbalizes rich video information so language models can reason over content without task-specific video training.
View paperDevelops a framework for measuring engagement with generated images and investigates how human response signals can guide image-generation models.
View paperUses self-play to iteratively compare and refine generated images, creating a learning loop for improving visual content against preference signals.
View paperHow individual and collective responses can be modeled to explore scenarios before real-world deployment.
Studies how groups of language-model agents can pool independent judgments to improve predictions of human decisions.
View paperIntroduces an agentic workflow for generating behavioral hypotheses, designing experiments, and evaluating evidence across repeated research cycles.
View paperAn agent-based model of 100,000 people compared standard and delayed second-dose vaccination strategies, identifying conditions under which delaying a second dose could improve population outcomes.
View paperIntroduces a framework for defining, simulating, and optimizing differentiable agent-based models, including learned parameters, agent actions, and interaction rules.
View paperThe buyer language changes across channels, but the engine and operating loop stay consistent. Predict, explain, and optimize the actions that drive revenue.
Behavioral AI research meets enterprise growth leadership. Deep science to understand behavior, paired with senior operators to turn foresight into enterprise value.
Product vision, behavioral science, and company strategy. Pioneer in behavioral AI with decades of experience turning research into enterprise decision systems. Previously held strategic leadership positions at Adobe.
Enterprise partnerships and go-to-market strategy at global scale. Previously served as Executive Vice President at Omnicom.
Brand strategy and market development. Global marketing leader who previously held Chief Marketing Officer (CMO) and strategic leadership roles at Salesforce, Coca-Cola, and Unilever.
Commercial strategy and governance, ensuring the platform operates with enterprise trust and calibration. Previously served as CEO at Inscape.
Your clients do not need another record of what happened. They need to see the decision while it can still be changed. Predict behavior. Align GTM. Grow revenue.