Frequently Asked Questions
We do!
Converting between insurance AMS or core policy systems consists of two main steps:
- Mapping payload columns such as premium amounts, counts of drivers, maximum limits etc.
- Mapping referential entities used by the source system to the referential entities in the destination system (source system might have a carrier ‘Philadelphia Ind Ins Co’ with id=234, and the destination system has ‘Philadelphia Indemnity Insurance Company’ with id=38483).
Too often, somebody is stuck manually converting hundreds or thousands of LOB, company, or location names in an Excel file so that the data is clean and ready for the ETL or migration scripts.
RecordLinker simplifies data transformation and helps data teams convert records between systems efficiently. Our ML-powered solution reduces the time wasted on record-by-record manual work.
Thanks to our integrations you are able to import your data with the correct structure for your system.
We’re cloud-only. But don’t worry - we don’t need access to your systems.
Our process is based on you sending us your reference data. Since you choose what to share, there’s no need for a multitude of internal approvals.
We can work with any system you have! As long as you can provide us with the input records you need to normalize (either by uploading an Excel or sending the data via API), that’s all we need.
That’s completely up to you. If you prefer, you can create your canonical record set manually in our system. Alternatively, you can upload the canonical records from your existing system of records, and we’ll use that model and follow its changes.
Sometimes, your data team will prefer a hybrid approach - to import your canonical records into RecordLinker, and later update or even create a new canonical record in RecordLinker - we'll know which ones got changed or manually created, and can provide those back to you via API or Excel download so that you can update your system of records appropriately.
No! We’ve worked with organizations across a number of different industries, and our portfolio is constantly growing. Reach out to us to learn more about how we can solve your data challenges.
Machine learning is an amazing thing, but it’s only ever as effective as the guidance (and the training data that powers it).
We recommend that you provide us with at least 5-10 sample linkages for each of your canonical records. Don’t worry if you don’t have these ready now; you can easily build up your training set via our user interface. It’s very fast and surprisingly fun!
