Trusted insights
We refine AI outputs with targeted human review to produce reliable, high-quality labels.
AI that reads your world. See user emotions, intentions, and preferences in video — 20x faster and for a fraction of the cost.
We help AI understand how people feel and respond by combining multimodal models with targeted human insight.
We refine AI outputs with targeted human review to produce reliable, high-quality labels.
We use large-scale video, audio, and log data to capture how emotional responses vary across real-world situations.
Systems that better match how people perceive and interpret multimodal content.
Today’s AI struggles to understand human emotion, intent, and preferences because it learns mostly from static text. We combine video-based AI with trusted and targeted human feedback to better capture real emotional signals and reduce noise.
We use focused, high-quality human feedback only where it matters most, reducing the need for large-scale labeling. This helps quickly refine vision-language models by improving accuracy with less data and faster iteration.
High-bandwidth human signals captured at the speed of thought, frame by frame.
AI methods paired with deep insights from human psychology to surface what matters.
From games to healthcare, the platform adapts to the signals each field needs.
Few-shot and transfer learning meet video understanding, and proprietary AI-human co-annotation models.
The HF.ai platform is designed for scenarios where understanding humans matters. It captures signals like attention, fatigue, stress, and engagement, and can be applied in driver assistance systems, warehousing, patient care, social media, games user research and beyond
A guided workflow that blends AI speed with human judgment — annotate, refine, and surface the moments that matter, all in one place.
Get quick labels from our video understanding agents
Let AI select sections that require further clarification and send them to human annotators.
Human annotators provide reliable, time-continuous labels on the videos.
Get insights that enable informed decision-making for your next move.
Iterate on your AI models with targeted feedback loops. Retrain on validated labels to boost AI model accuracy
A stack designed to do more with fewer labels — combining few-shot temporal models, annotator evaluation and automated quality control, all rooted in decades of academic research.
Generalize labels from a handful of annotations — taking time-continuous data labeling to the next level.
The breakthrough isn't volume, it's quality. Focus annotation effort exactly where it moves the model.
Automatically detect unreliable annotators early to keep subjective labels grounded in trustworthy truth.
Integrated tools for cleaning, processing and visualizing feedback — built on years of academic research.

Co-founder · AI & Affective Computing
Awarded AI researcher, IEEE Fellow, +20 years of R&D experience in Affective AI.

Senior AI Engineer
PhD & Postdoc, Uni Malta. Inventor of the PAGAN labelling tool.

Senior Engineer
PhD in AI, +10 years of DevOps expertise

CTO
15+ years in the game industry and real-time compute.

AI Engineer
PhD in AI. Awarded affective AI tech in CHI

Sales and Operations
+10 years of experience managing complex international projects

Co-founder · Operations
20+ years scaling teams and ventures, raised over $100m
Everything you need to know about the platform, data and onboarding.
Whether you have a question, feedback, or want to start a project — our team is here to help.
info@humanfeedback.ai