Build Intelligent Operational Solutions Faster

Ontaura provides a semantic operational platform for developers and system integrators to build connected, data-driven, AI-ready solutions without reinventing core operational infrastructure.

Why Developers & Integrators Use Ontaura

Ontaura gives developers and integrators the foundation to create intelligent operational applications powered by connected data, automation, and AI

Semantic Operational Model

Understand data in context, not just as disconnected records and files.

Unified Data Foundation

Work with IoT, time-series, documents, images, events, and workflows in one operational platform.

Accelerated Solution Delivery

Reduce development time by leveraging built-in operational capabilities, automation, integrations, and data orchestration.

AI-Ready Architecture

Expose semantically structured operational data to AI agents, machine learning models, and intelligent workflows.

Technical Highlights

The Ontaura software platform is a Java-based, API-first semantic operational platform for building connected, data-driven solutions. It combines ontology modelling, time-series and multimodal data handling, automation, integration, and event-driven execution into a configurable platform designed for real-world operational systems.

Platform foundation

  • Built on Java

  • Runs on standard Java application servers such as Tomcat

  • Designed for enterprise deployment

  • Suitable for cloud, managed cloud, and on-premise/runtime-hybrid scenarios

API-first architecture

  • REST API access to core platform capabilities

  • Portal uses the same underlying API model

  • External systems can create, update, query, and interact with operational entities

  • Designed for integration rather than closed-system usage

Semantic data model

  • Ontology/knowledge-graph based entity model

  • Supports entities, relationships, attributes, tags, profiles, and status models

  • Designed to represent assets, locations, people, events, documents, sensors, workflows, and operational context

Data handling

  • Supports IoT and time-series data

  • Links data streams to real-world operational entities

  • Can manage multimodal data such as documents, images, scans, forms, and events

  • Semantic metadata gives data operational meaning

Automation and execution

  • Event-driven automation

  • Scheduled systems and jobs

  • Distributed processing through Ontaura Fabric

  • Multithreaded execution for high-volume workloads

  • Suitable for integrations, reporting, data processing, alerts, and workflow automation

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Developer extensibility

  • JavaScript-based scripting for reports, dashboards, dynamic fields, systems, and custom jobs

  • Custom integration logic

  • Custom dashboards and visualisations

  • Ability to model new operational domains through taxonomy configuration rather than rebuilding core software

Integration capabilities

  • APIs

  • Databases

  • MQTT

  • Queues

  • FTP/file ingestion

  • SMTP/email

  • Serial/device integration where required

  • Third-party systems and AI/ML services

AI readiness

  • Semantic context can be exposed to AI agents, LLMs, and ML models

  • Operational data is connected to meaning, not just stored as records

  • Supports AI-assisted analysis, automation, and decision workflows

Security and governance

  • User authentication and permission controls

  • Entity-level access patterns

  • Audit/journal capability

  • Configurable data models and controlled operational views