By creating unique IDs and relating otherwise disparate data, ResolvER can merge records from multiple data sets. Additionally, it allows for the integration of external data with simple yet robust ways of linking records. Master Data Management becomes fast, scalable, and automated, unlocking the ability to append, merge, and enrich data based on generated keys.
ResolvER is cutting-edge data relationship management technology that, using semantic matching, lexical matching, and Natural Language Processing (NLP), finds ways of linking records faster and merging disparate data easier than ever before. Deduplicate and link records to create powerful and robust Master Data Records.
Matching data on one level is useful. Creating ties and structures that describe the relationship between linked data sets opens a world of valuable insights. From simple parent-child relationships to an entire web of various connections forming a virtual knowledge graph of connections, ResolvER manages and reveals the complex relationships between your data.
Data is littered with duplicate information across assets. In order to derive any value from data from a variety of sources, you need a system for Entity Resolution in order to create a single lens view. We use the most advanced Machine Learning and Artificial Intelligence to solve this problem.
ResolvER adapts to your specific needs. Both Machine Learning and rule-based matching are available to meet any project requirements.
No matter the size of the project, get the tools and resources to run it efficiently. As needs grow, ResolvER scales up to deliver consistent performance.
ResolvER offers the most efficient, state-of-the-art indexing query methods, optimized to give you the fastest query time, the fastest build time, and the fastest recall possible.