Kraph

KNOWLEDGE INFRASTRUCTURE FOR HUMAN AND AI

Connecting knowledge,
creating understanding.

Kraph builds knowledge information services by turning domain knowledge from across the world into high-quality data, metadata, knowledge graphs, and fit-for-purpose structures that people and AI can use together.

Explore our services About Kraph

01 / ABOUT

Information is abundant.
Knowledge we can understand is not.

Documents and data are growing rapidly, yet they remain scattered across sources and formats. Kraph goes beyond collection to structure entities, concepts, relationships, sources, and context together.

02 / WHAT KRAPH DOES

Turning knowledge into structures ready for services.

01

Structured knowledge

We design concepts, entities, relationships, and context in forms that can be connected.

02

High-quality domain data

Across domains such as brands and books, we build trustworthy metadata and knowledge structures.

03

Services for people and AI

We deliver knowledge information services for discovery, understanding, recommendation, analysis, and AI applications.

03 / SERVICE PORTFOLIO

One knowledge infrastructure.
Multiple domain services.

Built on Deepgraph as a common foundation, we expand knowledge services around the characteristics and needs of each domain.

BUILDING

Brandeep

Brand knowledge portal

A service for deeply exploring brand identity, products, categories, relationships, and market context.

BUILDING

the subtext

Book metadata and knowledge service

It structures authors, subjects, concepts, relationships, and context beyond surface-level bibliographic data.

CORE PLATFORM

Deepgraph

Large-scale knowledge graph platform

The core infrastructure providing connected knowledge structures and data capabilities across all Kraph services.

04 / PLATFORM

A common foundation connecting our services

05 / VISION

Knowledge infrastructure for people and AI

Kraph connects knowledge across domains and expands the foundation that enables each service to deliver more accurate discovery and understanding. Ultimately, we aim to improve how knowledge is found and used—and contribute to people's lives.

  • Structure over collection
  • Quality and provenance over scale
  • Relationships and context over string matching
  • Data designed for both people and AI