What is Enterium

Enterium is a content-operations platform. It runs the complete lifecycle of expert web content for a fleet of owned sites: discovering source material, generating articles grounded in a per-niche research corpus, verifying them with deterministic quality gates, publishing them to live sites, and measuring the search-traffic outcome — feeding what it learns back into the next cycle.

The platform is operated by a small human team together with LLM agents as first-class users: agents read platform state, file defects, manage tasks and launch runs through the same API and an MCP server. This documentation is written for them as much as for people.

The operating model

Work is organized around a contract: one niche, one brand voice, one destination site. For each contract the platform maintains configuration (topic ontology, source feeds, brand description) and an accumulating research corpus. A nightly scheduled run drives every active contract through the full cycle without human intervention; humans supervise through dashboards, reports and the task board.

The platform in one pass

1. Collect — harvest candidate sources for the contract’s niche and rank them by semantic (vector) relevance to its ontology; extract research facts into the corpus.
2. Generate — produce an article from a qualified source through a staged, versioned LLM pipeline, grounded in the research corpus (RAG).
3. Verify — deterministic gates on the publish path: topic deduplication, claim verification against sources (anti-fabrication), relevance filtering and brand-safety scoring.
4. Publish — render the final layout and ship it to the destination site; a URL only counts as published once it is verified live.
5. Measure — search-console metrics, cost accounting and error tracking close the loop; topic-level feedback steers what Collect looks for next.

The full walkthrough with the exact gates is in Content lifecycle.

What makes it interesting to build on

• Modular monolith with enforced boundaries — one backend split into bounded contexts whose isolation is checked in CI, not by convention. See Architecture.
• Immutable pipeline versions — generation code is versioned like data: any past run is reproducible, and rollback is a pointer move. See Pipelines.
• Agent-native surface — a documented MCP server, scoped agent tokens and machine-readable state everywhere. See MCP.
• Fail-loud philosophy — steps do not fall back to defaults silently; a broken invariant stops the run and lands in the error surface where it is visible. See How to read errors.

How to read this portal

The sidebar is the map. Suggested order: this page → Architecture → Content lifecycle; acting as an agent, start at Agent quickstart and Connecting to MCP. Deep dives live under How it works; operational facts (limits, errors, status, changelogs) under Reference. Consuming this portal as an LLM? For LLM agents is your contract — every page has a Markdown twin at <route>.md.