Custom · On request
Your data, on the layer.
Extend the curated foundation with your own proprietary data. We merge your records into the same entity model, serve them back through the same API, Export, and MCP surfaces, and maintain the result alongside the public layer — a private, integrated foundation only your team sees.
Who it's for
Enterprise teams whose AI products and analyses are limited because their proprietary data sits in one warehouse and the broader landscape sits everywhere else. Custom merges the two — your records become first-class citizens in the same entity model, ranked against the same cohorts, exposed through the same surfaces.
If you've ever wished your internal data could be queried with the same friendly schema and lineage as a public reference dataset — and updated alongside it forever — Custom is the engagement that gets you there.
What a Custom engagement looks like
Your data, integrated into the layer.
| Capability | What it means |
|---|---|
| Your data, our model | Your proprietary records get resolved into the same entity model as the curated layer. Internal IDs map to canonical entities; relationships stitch across both datasets cleanly. |
| One foundation, two sources | Public and proprietary facts coexist on the same entity, with provenance attached so you always know which is which. Your AI and analyses get the full picture. |
| Same surfaces, private deployment | Use the API, Export, or MCP exactly as documented — but pointed at a deployment that includes your data. Nothing changes about how your team consumes; everything changes about what they can ask. |
| Cohort and ranking extensions | Define cohorts that span your data and ours. Rank your portfolio, your customers, or your operations against the broader landscape — with the math already built. |
| Access controls and isolation | Your private layer is isolated from other tenants. Role-based access lets you share specific slices internally without exposing the whole foundation. |
| Maintained alongside the public layer | When the curated layer refreshes, your merged data is reconciled. You inherit our continuous-maintenance work without the integration becoming someone's full-time job. |
What you can build on top
Internal AI products with private context
Agents and assistants that reason about your customers, your portfolio, or your operations alongside the broader landscape — with everything traceable.
Benchmarking against the field
Rank your entities against the same cohorts the public layer uses. Know exactly where you stand on every metric the broader market cares about.
Customer-facing data products
Embed comparisons, rankings, and insights that combine your data with the public foundation, in apps your customers see — defendable, citable, current.
Strategy & decision support
Models, dashboards, and explorations that bring your private knowledge and the public landscape into a single, queryable foundation.
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.
Fold your data into the layer.
Get in touch to discuss how the Corthos domain-intelligence layer fits your data, your domain, and the AI products you're building.