Making Sense of Large Volumes of Disconnected Data
Solving for complex entity resolution challenges requires human intelligence at scale. Humans understand natural variations in language, variations in imagery, contextual references, and behavioral patterns which are often essential in interpreting data inconsistencies.
But making sense of enormous volumes of disconnected data is not something humans do efficiently or accurately.
Transform your disconnected data into a clean, canonical record of entities, objects, and relationships
Entity Resolution Capabilities
Through a combination of human and machine intelligence, our platform solves the challenges of duplicate records, data inconsistencies, and the lack of a comprehensive view across multiple systems.
Identity Recognition
Our platform helps associate entities from multiple data sources of varying data types to a single real-world reference through pattern comparisons.
Ontology Resolution
Our platform helps to detect and resolve semantic or taxonomy conflicts to align with your ontology.
Record Linkage
By clustering records or occurrences that correspond to the same entity, our platform can propose canonical matches using language understanding to link and deduplicate named entities.
Platform & Tools
The platform is the core of our high-performance data labeling. Annotation tools, workflow configuration, job distribution, worker evaluation, and quality control are all managed within our platform with varying degrees of ML assistance.
Known Workforce
Alegion qualifies and trains a team of human annotators who are identified as a match for your project. Our teams can be NDA-ready, geo-isolated, or selected according to specific compliance requirements. Or, you can bring your own team.
ML Project Expertise
We don’t just onboard you onto our platform and hope for the best. You’ll be assigned an Alegion solutions specialist who understands your problem space and continually iterates on your labeling tasks to deliver on your accuracy requirements.
Data Scientist
We’re swimming in training data and I didn’t have to lift a finger.
Transform your dataset into a clean record
