Human-curated cultural recommendations, real consumption signals, and emotional metadata from Brazilian cultural consumption. Built for researchers, AI developers, and experimental recommendation systems.
Request API AccessRecomendeMe provides non-synthetic cultural data suitable for model training, evaluation, benchmarking, and experimental algorithm development.
Access human-curated cultural recommendations with contextual and emotional metadata for training recommendation models, cultural understanding systems, and preference prediction algorithms.
Investigate cultural discovery patterns, algorithmic bias, diversity in recommendation systems, and long-tail content exposure in real-world environments.
Build and validate research-grade recommendation systems using cultural graphs and signal-based ranking. Not positioned as production SaaS, but as infrastructure for experimentation.
RecomendeMe API is currently used by academic institutions for research in recommendation systems, cultural data analysis, and human-computer interaction.
Academic validation: The RecomendeMe API is actively used in university research programs, thesis projects, and applied research on recommendation systems and cultural data.
The RecomendeMe API is not publicly available or self-serve. Access is granted case-by-case based on use case evaluation and research alignment.
Contact our admin team describing your use case, research goals, or product needs. We review applications individually and provide scoped access based on project requirements.
admin@recomendeme.com.brWe welcome academic inquiry and research partnerships. If you're working on thesis research, cultural data analysis, or recommendation systems studies, please describe your research objectives and institutional affiliation.
Explore published research and reports at RecomendeMe Research to understand how the platform supports academic work.
We work with organizations interested in cultural intelligence infrastructure, experimental recommendation systems, and AI training datasets.
Access is custom-scoped based on your needs. We support pilots, research partnerships, and experimental integrations. Contact us with details about your use case and technical requirements.
RecomendeMe is built on principles of responsible data usage, user consent, and ethical AI development. We treat cultural data as signal for research and intelligence, not surveillance.
All data collection follows informed consent principles. Users understand how their cultural consumption contributes to research and platform improvement.
We do not sell raw personal data. API access provides aggregated and anonymized datasets designed for research and development, not individual profiling.
Datasets are processed to protect individual privacy while preserving cultural patterns and signals necessary for research applications.
We align with human-centered AI development principles, emphasizing cultural diversity, long-tail representation, and anti-bias research.
Our approach considers LGPD and GDPR frameworks for responsible data handling, though specific compliance claims require legal counsel.
We maintain open communication with API users about data provenance, limitations, and appropriate use cases for research and development.
Technical documentation, research repositories, and experimental implementations are available to API users and research partners.
Data schemas, integration patterns, and API concepts for authorized users.
Papers, reports, and studies using RecomendeMe data and methodology.
Open-source implementations of algorithms and analysis tools developed with RecomendeMe infrastructure.
Most recommendation datasets are synthetic, platform-specific, or lack the emotional and cultural context necessary for training culturally-aware AI systems. RecomendeMe provides real human curation signals from actual cultural consumption.
Real recommendations from humans sharing cultural content with intent, emotion, and context—not passive consumption logs or synthetic ratings.
Brazilian cultural consumption patterns, including local artists, regional preferences, and underrepresented cultural expressions often missing from global platforms.
Our data includes niche content, emerging artists, and cultural items outside mainstream popularity, enabling research on discovery and diversity.
Ready to explore cultural data infrastructure for your research, AI training, or experimental recommendation system?
Contact Us: admin@recomendeme.com.br