A knowledge graph is a semantic data-fabric layer that connects every structured and unstructured source into one connected model — so people and AI can ask any question across all enterprise data and get accurate, explainable answers.
Knowledge graphs are interconnected networks of data points — nodes, attributes and the relationships between them — that can scale to trillions of connections. Graph Studio sits above your existing systems and adds real-world meaning to data, structured and unstructured alike.
Catalogue and connect internal and external sources into a single semantic model — eliminating silos and activating unused data.
Structured, semi-structured and unstructured — databases, lakes, APIs, PDFs, emails and chat logs — onboarded with no-code pipelines.
A high-performance, in-memory MPP engine with graph algorithms, OLAP and geospatial functions that scales linearly as you add servers.
Knowledge graphs constrain LLMs to the most relevant, accurate data — reducing hallucinations and making answers explainable. That's Graph Retrieval-Augmented Generation.
Onboard every source into RDF with parallel-loading pipelines — no rigid schemas required.
Layer business ontologies and semantic definitions over the data so terms map to real meaning.
Graph context feeds the LLM precise, connected facts instead of loose document chunks.
Accurate, explainable, low-hallucination responses — queried in natural language.
Unify CRM, support, billing and product signals into one entity graph for a true 360° customer view.
Surface hidden relationships and rings across transactions, accounts and entities that tabular data misses.
Integrate trials, literature and patient data with semantic reasoning to accelerate research insight.
Parallel-load enterprise data into RDF for in-memory transformation across complex production systems.
Distributed OLAP answers complex, resource-intensive questions in real time without straining downstream systems.
Provide comprehensive organizational context to every GenAI solution — the grounding layer for an AI fabric.
Altair Graph Studio is part of the Altair RapidMiner data analytics and AI platform — now part of Siemens Xcelerator, the world's most complete AI-powered portfolio of industrial software. MXTechies brings the Mendix apps and engineers that turn a knowledge graph into a working enterprise solution.
We'll scope a high-value use case and stand up a graph-grounded AI proof of concept — on your data, in weeks.
A knowledge graph is an interconnected network of entities and their relationships that adds real-world meaning to data — a semantic layer over structured and unstructured sources.
Graph Studio is an enterprise-scale knowledge-graph toolset (part of Altair RapidMiner, now Siemens Xcelerator) powered by the Graph Lakehouse MPP engine for fast, scalable graph analytics.
Through Graph RAG, knowledge graphs ground LLMs in connected, accurate facts — reducing hallucinations and making AI answers explainable.
We connect your sources into a unified graph, stand up graph-grounded AI proofs of concept, and integrate them with production Mendix applications.
Graph Retrieval-Augmented Generation grounds an LLM in a knowledge graph’s connected facts — improving accuracy and explainability over plain vector RAG.
A vector database retrieves similar text chunks; a knowledge graph captures entities and their relationships, giving AI structured, connected context.
Yes — Altair and Graph Studio are now part of Siemens Xcelerator, within the Altair RapidMiner platform.
Structured and unstructured sources alike — databases, data lakes, APIs, documents, emails and chat logs.