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Prometheux Documentation

website·Indexed 32 days ago

https://docs.prometheux.ai

Prometheux is an ontology-native data processing platform. Its documentation covers on-premises and Databricks installation, the Vadalog expression language (including AI functions and operators), app development via the App Editor, and integrations with the Model Context Protocol (MCP) for tools like ChatGPT, Cursor, and Claude Code, as well as a dedicated CLI for context-as-code and CI/CD.

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What's inside Prometheux

  1. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that implements an ontology layer above existing data systems. Unlike traditional ETL, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This approach enables ontology-native queries—where queries are expressed via ontology concepts rather than physical schemas—and ensures full lineage and traceability from results back to the underlying data sources.

  2. Overview of the Context Layer and Note Scoping

    The Context Layer serves as the AI agent's knowledge base, storing 'context notes' (facts, preferences, observations, and document chunks) used for reasoning during inference.

    Notes use a specific scoping model:

    • global: The note is available workspace-wide.
    • ontology: The note is tied to a specific ontology via a scope_id (the ontology ID). Notes with this scope are only retrieved when the agent operates on that specific ontology.

  3. Overview of Prometheux Ontology-Native Data Processing

    Prometheux is an ontology-native data processing engine that treats ontologies as runnable models rather than static documentation. It defines entities, relationships, semantics, constraints, and processing logic that can be executed directly to query data across multiple systems.

    Key architectural features include:

    • Ontology Layer: Sits above existing data systems, applying logic at query or execution time instead of requiring data migration or ETL pipelines.
    • Distributed Data Access: Operates across multiple data sources simultaneously, resolving semantics at runtime.
    • Ontology-Native Queries: Queries are expressed using ontology concepts instead of physical schemas, reducing coupling to underlying data structures.
    • Lineage: All results maintain explicit links back to ontology definitions and original data sources.

  4. Overview of Prometheux Concepts

    A concept is a unit of logic in a project that produces an output predicate. There are six types of concepts:

    • Executable Programs: Vadalog (labeled as logic), SQL, Cypher, and Python.
    • Configured Concepts: context (exposes unstructured notes as a queryable window) and llm (calls a language model using a prompt template).

    The Concepts API allows for creating, running (individually or as a dependency chain), reading results, and tracking execution progress.

  5. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that provides an ontology layer above existing data systems. Instead of requiring data migration or ETL pipelines, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This ensures consistent semantics across analytics, applications, and AI systems while maintaining full lineage and traceability back to the underlying data sources.

  6. Overview of Prometheux Ontology-Native Data Processing

    Prometheux is an ontology-native data processing engine that implements an ontology layer above existing data systems. Unlike traditional ETL, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This approach enables distributed data access across databases, warehouses, and platforms while maintaining full lineage and traceability back to the ontology definitions and source data.

  7. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that provides an ontology layer above existing data systems. Unlike traditional ETL, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This enables consistent data processing across analytics, applications, and AI systems with full lineage and traceability.

  8. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that uses executable ontologies to query and process data across multiple systems. Unlike traditional documentation, a Prometheux ontology is a runnable model that defines entities, relationships, semantics, constraints, and query/processing logic. It acts as a layer above existing data systems, connecting to data in situ and applying logic at execution time, which eliminates the need for mandatory data migrations or ETL pipelines while maintaining full lineage and traceability.

  9. Overview of Prometheux Ontology-Native Data Processing

    Prometheux is an ontology-native data processing engine that provides an ontology layer above existing data systems. Unlike traditional ETL, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This enables consistent data processing across analytics, applications, and AI systems with full lineage and traceability.

  10. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that provides an ontology layer above existing data systems. Unlike traditional ETL, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This approach enables distributed data access across databases, warehouses, and platforms while maintaining full lineage and traceability back to the ontology definitions and source data.

  11. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that treats ontologies as runnable models rather than just documentation. It allows developers to define entities, relationships, semantics, constraints, and processing logic that can be executed directly against data across multiple systems. Instead of requiring data migration or ETL pipelines, Prometheux connects to data in its original location and applies ontology-defined logic at query or execution time, ensuring results have full lineage and traceability.

  12. Overview of Prometheux ontology-native data processing

    Prometheux is an ontology-native data processing engine that provides an ontology layer above existing data systems. Instead of requiring data migration or ETL pipelines, it connects to data in its original location and applies ontology-defined logic (entities, relationships, semantics, and constraints) at query or execution time. This ensures consistent semantics across analytics, applications, and AI systems while maintaining full lineage and traceability back to the underlying data sources.