Blog
Guides, product deep-dives and infrastructure notes from the team building Fiuvi.
Every new data source fragments formats, schemas and freshness a little further. Here is why aggregation, not another one-off integration, is the fix.
Raw data is noisy, inconsistent, and rarely labeled. Here is the pipeline we use to turn it into something a model can actually train on.
Read articleA five-minute walkthrough of activating your API key and pulling enriched data for any source we support.
Read articleResolving a fully enriched record in a single call sounds simple. Under the hood, it means solving sourcing, coverage, and freshness at once.
Read articleA closer look at how Metacore turns organized raw data into datasets that are structured, cataloged, and ready for model training.
Read articleCoverage is the metric that matters most for a data API. Here is how we decide which sources to add next, and how we keep 99% of records resolving.
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