Prometheux

Prometheux

Mapping the Language of Data

Mission

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Long Story Short

About Project

Prometheux powers explainable reasoning over the world's largest Knowledge Graphs - From drug discovery to banking companies like Revolut.

Made scientists come from the Knowledge Graph labs across the University of Oxford and TU Wien.

Modern organizations are built on data — but most of that data lives in silos. It’s stored across spreadsheets, databases, and APIs that don’t “talk” to each other. Prometheux set out to change that by creating a knowledge platform that connects data through meaning, not just storage.

The platform uses ontology-based modeling to define relationships between entities — transforming raw data into a structured, living network of knowledge. Overcode joined the team to design and develop the core product experience — the Ontology Builder — the visual brain of Prometheux.

Challenge Accepted

Requirements

Enterprises have no shortage of data. What they lack is context.

Without a unified system of relationships, data scientists and business teams waste hours reconciling models, cleaning duplicates, and guessing how one table connects to another.

Prometheux want to building a product where users could design data relationships as easily as drawing a flowchart — and make those relationships drive intelligent insights across the platform.

Our challenge was to turn a deeply technical concept, ontology, into an elegant, approachable interface that anyone could use without losing analytical power.

UNLOCKING SUCCESS

Solution

Overcode designed and developed the Prometheux Ontology Builder — an interactive environment for creating, editing, and visualizing relationships between data entities.

We started with a discovery phase, mapping out how data engineers, analysts, and business users collaborate. That research guided every UX decision — from layout logic to color contrast — ensuring the product would work seamlessly across technical and non-technical roles.

The resulting system allows users to:

Define entities and their relationships through drag-and-drop interactions.

Automatically infer new connections using AI-assisted logic.

View and edit ontology data in split-screen mode — with the graph on one side and the underlying table or JSON on the other.

Connect multiple data sources into one unified schema.

Behind the clean visuals lies a robust rules engine that validates relationships, manages dependencies, and updates linked entities in real time.

Core Features:

Visual Ontology Editor: Build and adjust relationships in an intuitive, node-based interface.

Concept Library: AI-suggested relationships inferred from existing ontologies.

Split-Screen Workspace: Combine data visualization and tabular context in one place.

Custom Fields & Bulk Editing: Define and modify schema attributes efficiently.

JSON & SQL Integration: Allow technical users to fine-tune data logic directly.