One API to pick and choose metadata from Gracenote, TiVo, IMDB, Netflix and 50 others

Combine multiple metadata providers together with external data sources and create a unified dataset to ingest into your platform

Ingesting, Matching and Merging metadata from a variety of sources to produce a clean and unified dataset ready for powering next generation Content Discovery experiences.

Content Recommendation Engine for TV and OTT

Clean Metadata, Accurate
& De-duplicated

Achieving a high-quality dataset is never straightforward and can be resource intensive. We have an established ETL to achieve just this. Meaning you can instead invest time and energy into core development of your products and services; rather than worrying about data.

Aggregation Processes

Ingestion
metadata datasource
Import Source Data
Typical data sources: API, S3, Database
Typical formats: JSON, XML, CSV
AI Datamodels
Transform to Data Models
Map the imported data to our internal data models. Resources types: Shows, People, Services, Tags & Locations.
metadata enrichments
Load to Database
Update data to a partition in our PostgreSQL database.
Matching & Merging
matching algorithm
ID Matching
Given a shared namespace between data sources we will group records.
AI matching engine
AI Matching
For each record a vector representation is calculated. These vectors are then used for matching.
deduplication of records
Merge Records
Rule based merging to create the best possible combined record.

Learn how we can help you

Aggregating various feeds & matching with metadata to produce a unified dataset is a significant technical challenge. It is a problem we can solve for you.