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Concepts

The concepts behind the API

Developer-first definitions of the ideas the platform is built on: entities, mentions, metering, grounding, and the machine layer.

Brand intelligence APIA brand intelligence API serves analyzed brand, category, and audience data as typed responses your code and agents consume, instead of charts a human reads.MCP serverAn MCP server exposes an API's operations as tools that AI agents discover and call themselves. What that means for brand intelligence integrations.Brand mention dataBrand mentions as structured records: where they come from, how duplicates are resolved, how sentiment is attached, and why source links matter.Entity resolutionWhy matching text to brands is hard: ambiguous names like Apple, nicknames, sub-brands, and how brand entities keep mention data clean.Share of voice dataShare of voice as a computed metric: the inputs, the denominator problem, and why consistent measurement matters more than any single reading.Ad library dataThe public ad archives as a data source: what Meta, Google, LinkedIn, and TikTok expose, what they forget, and why daily capture matters.Ad library APIThe official ad library APIs are narrow or missing. What Meta, Google, LinkedIn, and TikTok actually expose programmatically, and how Adveron serves all four libraries over one API and MCP server.Audience intelligence dataAudience intelligence from observed public behavior versus declared panel answers: what each method sees, and where behavioral data fits in code.Category conversationCategory conversation as a data model: the market-level layer above single brands, where trends, entrants, and share shifts become visible.Usage-based API pricingHow credit-metered API pricing works, why data APIs price on usage instead of seats, and what metering means for agents and automation.API key scopingScoping API keys to workspaces: why least privilege applies to data APIs, and how scoped keys keep usage attributable and revocation cheap.llms.txtThe llms.txt convention: a root file that gives AI systems a curated, markdown map of a site, and what it does and does not control.AI groundingGrounding means an AI system's outputs are anchored in retrieved, current data instead of training memory. Why it decides whether agent work is usable.
Adveron — brand, category, and audience intelligence.
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