Enterprise-Grade AI

A graph-model fusion agent platform, from data to action.

Knowledge graph × LLM — one platform where your data, models and AI agents run operations together. Autonomous analysis, autonomous decisions, autonomous execution.

The Problem

73% of enterprise data never informs a decision

Phronesis Ontology closes that gap — one platform where your data, models and AI agents run operations together, instead of sitting in disconnected systems.

01

Data silos

Systems built apart — no single business view.

02

Semantic confusion

Technical fields disconnected from business language.

03

T+1 latency

Batch reports — too slow for real-time operations.

AI workflow orchestration canvas

AI workflow orchestration — drag-and-drop canvas with LLM, agent, retrieval and approval nodes

Architecture

Data → Semantics → Decision → Execution

One closed loop — from ingestion to intelligent execution, in milliseconds instead of T+1.

APPLICATIONS
Analytics & Workflow

Dashboards · process orchestration

Automation

RPA · scheduling · anomaly handling

Dev Tools

Low-code · ontology editor

ONTOLOGY CORE
PHRONESIS ONTOLOGY
Semantic layer

One business language for humans & agents

Logic layer

Business knowledge graph · rules

Execution layer

Agents act — governed & traceable

SOURCES
Data sources

Sensors · databases · logs

Logic sources

Rules · algorithms · models

Execution systems

Control systems · field devices

Agent Architecture

Orchestrate, execute, govern

Platform console
01

Agent — orchestration & decisions

Task planning, tool calling and visual workflow orchestration across specialized agents.

02

Skills — execution layer

Semantic-graph retrieval, sandboxed tools and built-in Skill templates for one-click integration.

03

Knowledge graph — cognitive substrate

Data, logic and action aligned on one ontology, injected on demand.

Platform console — built-in / custom / MCP tools, knowledge, models, evaluation, logs and approvals

Use Cases

Already running in production

01

Agent OS

Models, tasks, cost and audit in one enterprise control plane.

02

Knowledge Q&A

LLM + knowledge-base answers over policies, contracts and reports — every answer traceable.

03

LLM-Enhanced Modeling

The semantic layer guides LLMs in building production-grade analytical models.

04

LLM-Enhanced BI

Natural-language analytics over governed data — business teams query in their own words.

Built for the GCC

Palantir built the blueprint — we built it for the GCC.

An ontology-based operating platform in the model global enterprises know — re-engineered for the Kingdom.

01

AI-agent native

The ontology is designed for autonomous agent execution from day one — not an add-on layer.

02

Fully sovereign

All data stays in-country. Full private deployment, data-residency compliant by default.

03

Arabic-native

Arabic / English business workflows and language models, out of the box.

04

Governed execution

Full decision logs, permission control, human-in-the-loop — innovation with stability.

Private Deployment Ready

See Phronesis Ontology on your own data.