Data Journalism · Live
The data foundation for journalism.
Source-grounded data for rankings, comparisons, longitudinal pieces, and fact-checked long-form — queryable by name, citable by source. Plug it into your own publishing stack and let editorial focus on the story instead of the spreadsheet.
Why the data is well-shaped for journalism
Most data journalism projects start the same way: a reporter or analyst spends weeks pulling, cleaning, and reconciling sources before any story can be written. The data is usually public, but never usable. By the time the analysis is done, the deadline is shorter than the verification window, and the editor takes the writer's word for it.
The Corthos layer collapses that step. Entities are already resolved. Sources are already cited. Cohorts and rankings are already computed. The question stops being "can we get the numbers?" and starts being "what's the story?" — which is the part editorial actually wants to spend time on.
What's in the layer for editorial
The Corthos data foundation, framed for the byline.
| Capability | What it means |
|---|---|
| Citable on every claim | Every fact carries a source pointer and a definition. When a piece needs to say "according to X," the citation is already attached to the data. |
| Cohort-aware rankings | Rankings need a peer set, not the whole field. Cohort definitions and per-entity scores come with the data so a comparison is honest by construction. |
| Time series for "what changed" | Multi-year history for every entity. The trend, the inflection, and the year-over-year delta are queryable — not something the writer has to assemble from snapshots. |
| Friendly entity model | Writers query by name, not by ID. The institution, employer, or place is a real entity with relationships, not a cell in a spreadsheet. |
| Reproducible analysis | The same query produces the same answer next quarter. The layer doesn't change underneath you, so older pieces stay defendable. |
| Continuous freshness | New releases land in the layer continuously. Your editorial calendar tracks the news cycle, not the data project. |
What this looks like in practice
Rankings
Top-X lists where every position is defendable. The cohort is defined; the metric is defined; the source is attached. No "trust me" in the methodology section.
Comparisons & explainers
Side-by-side pieces that put two or more entities against each other across the right axes — with the underlying data sitting one click away.
Longitudinal & trend pieces
"What changed over the last decade" stories built on real time series, with inflection points and year-over-year deltas already queryable.
Long-form, fact-checked end-to-end
Investigative and explanatory pieces where every claim points back to a specific record. The fact-checker's job becomes hours, not weeks.
Plug it into your own stack.
Most editorial teams already have a publishing stack they like — CMSes, design systems, and data-viz pipelines they've invested in. We don't replace any of it. The data layer is yours to consume via API, Export, or MCP, and the rest of your output stays exactly the way you build it today.
Optional · publishing help
If you also want help with the output.
For teams that want a hand on the publishing side too, we can layer on tools that turn the data layer directly into article drafts, ranking pages, and comparison views — but these are add-ons, not the headline. The data foundation is what's universal.
press.corthography.ai
Source-grounded content drafts generated from the data layer — articles, rankings, and explainers with citations attached.
Corthuxa-driven layouts
Adaptive presentation layers that render entity, ranking, and comparison views directly from the layer — for teams that want a turnkey output surface.
Enterprise Engagement Model
Our proven three-phase approach to enterprise transformation
- 1
Assessment
We evaluate current data assets, flows, and decision points.
- 2
Blueprint
We design your Corthos OS integration map, guarantees, and SLAs.
- 3
Build
We implement, validate, and operationalize the enterprise rollout.
Make the data the easy part of your next story.
Get in touch to discuss how the Corthos domain-intelligence layer fits your data, your domain, and the AI products you're building.