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Use LLMs on enterprise data — safely.

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Discover and trade verified synthetic datasets — all in one marketplace.

Buy, sell, and sponsor synthetic datasets with full transparency and compliance.

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Your AI is only as good as the data it trains on.

DTS solves unusable data — whether it's restricted, imbalanced, or missing coverage your model needs.

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Measure what matters.

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Redefining how organisations trust, protect, and use data.

CUBIG builds AI-driven systems that redefine data security — from generation and transformation to validation and integration.

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Home / Glossary / Reinforcement Learning

What is Reinforcement Learning?

Reinforcement learning refers to a type of machine learning where an agent learns optimal behaviors by interacting with an environment through rewards and penalties. It is widely used in robotics, gaming, finance, and autonomous systems.

Related Glossaries

  • Data Diagnosis (Data Health Check) Data Diagnosis, or Data Health Check, refers to the process of checking data for quality issues, schema errors, missing values, context loss, and unusable formats before AI execution. It is the starting point for determining whether data is truly ready…
  • Sentiment Analysis Sentiment analysis refers to the process of using natural language processing (NLP) to analyze text and determine sentiment polarity, such as positive, negative, or neutral. It is widely used in social media monitoring, customer feedback analysis, and market research.
  • Data platform A data platform is an integrated system that manages, processes, and analyzes structured and unstructured data. It facilitates secure data storage, retrieval, and analytics to support AI, business intelligence, and big data applications.
  • Raw data Raw data refers to unprocessed information collected from various sources, such as sensors, databases, or surveys. It lacks structure and requires cleaning, transformation, and analysis before being used in decision-making, machine learning, or statistical modeling.

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