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HASH is a tool for turning raw information into knowledge and process graphs. It does this by allowing you to connect up and ingest both unstructured information (contained within documents and other files), as well as structured data (for example, from databases and applications). HASH then extracts semantically typed (SemType) entities from these, creating a unified knowledge graph and process graph, which is continuously checked, automatically maintained, and kept up-to-date.

HASH provides a graphical user interface atop hgres, along with a range of AI-powered entity and type extraction, workflow orchestration, and other capabilities. It provides individuals, as well as groups of users, with their own semantic "web" of information, drawn from different sources and platforms, or created directly with HASH.

With HASH, you can:

• aggregate information from lots of different places: reconcile and map information to semantic 'entities' and 'types' that represent the things you care about, in a linked graph
• sync changes to entities: allow information changed in one system (or edited directly in HASH) to be seemlessly synced to all of the others
• create, manage and update types: establish data contracts; understand how updates will break things for data consumers, and who those data consumers are; improve the availability and reliability of information through full versioning and provenance trails
• control access to information: set visibility and edit restrictions on information; ensure compliance across systems
• use information directly in new ways: in addition to enhancing existing applications through two-way sync, HASH lets users reference entities, their properties and links information in pages; render information on pages using blocks, separating data from visualization logic; build whole sites, tools and apps using blocks, without writing code
• use information to provide context to AI models: utilize a web of typed entities to provide context to AI models