Every Article, as Structured Text

Full body text, with navigation, adverts, related-article rails, and newsletter prompts stripped out. This is the field that separates a news feed you can build on from a list of links, and it is the reason most snippet-based APIs disappoint once someone tries to do entity extraction or classification on them.

We collect what is publicly readable and we do not bypass paywalls or share subscription credentials. For soft paywalls the publicly served portion is collected and the record is explicitly marked as partial rather than presented as a complete article. Where you hold a licence with a publisher, that can be configured into the engagement so the collection reflects the access you legitimately have.

Wire copy reprinted across dozens of outlets is the single biggest source of inflated counts in media monitoring, so reprints are clustered under a shared syndication ID with the earliest known publication marked as the original. You can then count clusters when you want a story count, or individual articles when you want a reach count — both are correct answers to different questions, and collapsing them is what makes most coverage reports wrong.

Both, and most engagements combine them. You supply the publications that matter in your category and the brand, product, executive, and competitor terms to match on, and collection is scoped accordingly. Adding a publication or a term later is a configuration change during the engagement rather than new development.

Historical depth varies by publisher, because some maintain complete public archives and others prune aggressively. We confirm achievable depth per publication during scoping rather than quoting a single number that would be wrong for most of your list, and backfill is quoted separately from ongoing collection.

That depends on the sources, and it is a question we answer specifically rather than generally. News content is copyrighted, publisher terms differ, and permitted use is scoped explicitly in the engagement with provenance recorded per document so you can demonstrate where every record came from. If your intended use is not supportable for a given publisher set, we will tell you before the contract rather than leave you to discover it in diligence.

Into the systems you already run. Records land as JSON, CSV, or Parquet in S3, GCS, or Azure Blob, or straight into Snowflake or BigQuery, on whatever cadence you set. Webhooks push new records to your endpoints as they are detected, which is how most customers wire alerting. A solutions engineer sets the schema, cadence, and destination with you during onboarding rather than handing you a docs page and wishing you luck.

Keeping the collectors working is our responsibility, not yours. Extractors are monitored continuously, and when a site changes we patch upstream while the schema we deliver to you stays fixed — so nothing downstream needs to be touched. If a change causes a genuine coverage gap we tell you which window was affected rather than quietly returning fewer records.

Yes, and we would rather you did. Every engagement starts with a free sample run against your own targets — your competitors, your catalogue, your keywords — and we hand back the actual dataset. Judging real output against your real requirements is the only useful evaluation, and it is a much better use of a first conversation than a slide deck.