Graphicient
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Graph history Environment forking Access control Skills library
01Forged parts, volatile pricing 02One part, several brands 03Hidden talent, revealed pool 04Parts at risk, failures anticipated 05Securing the supply chain
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FROM SCATTERED DATA TO RELIABLE DECISIONS

Structure, explore, monitor, decide: four building blocks connected on a single graph, turning scattered data into reliable decisions.

Company

A team that comes from the field

We build Graphicient with the teams who use it, from Toulouse.

Resources

Shedding light on graph technology and its applications.

What we learn in the field, and answers to the questions we get asked most often.

What we learn in the field

Business modeling, enterprise AI reliability, project takeaways: articles written by the people building the platform.

6:40 a.m. The factory is on fire. What's affected? Supply chain October 27, 2026 Impact analysis: when a plant burns, know in seconds what is affected Supply chain impact analysis: by traversing your data graph, identify in seconds the products threatened by a plant shutdown and the sites able to take over. Read the article → From 87% to 98% correct answers by changing the model Artificial intelligence October 14, 2026 When the model becomes the ceiling: from 87% to 98% correct answers Four months of work on the ontology, the semantic layer and the agentic harness took us to 87% correct answers on a major carmaker's bill of materials. By changing only the model, we reached 98%, three times faster. Read the article → One part, two part numbers, two prices Procurement October 14, 2026 Consolidation out of reach: how a fragmented BoM strips away your negotiating leverage A BoM split across PLM, ERP and contracts hides the volumes you could pool. How a knowledge graph makes spend consolidation possible. Read the article → Graphicient and Neo4j technology partnership Partnership October 7, 2026 Graphicient Announces Technology Partnership with Neo4j to Bring Trusted, Explainable AI to Industrial Environments Graphicient’s Industrial Knowledge & Compliance Engine, built on Neo4j, helps aerospace, automotive, energy and manufacturing organizations structure engineering knowledge, govern AI systems and prepare for growing regulatory requirements. Read the article → Ontology makes AI 3 times more accurate Ontology October 5, 2026 Ontology: why start with meaning before data The data already exists; what's missing is agreement on what it means. Five reasons to start with an ontology. Read the article → How to never copy millions of records again Knowledge graph October 1, 2026 Context inheritance: never copy millions of records again Create variants of a context without duplicating the parent's data, and keep a single source of truth. Read the article → Governing an ontology at Graphicient Ontology August 18, 2026 Governing an ontology at Graphicient Building and evolving an ontology sustainably, without ever losing control. Read the article → Graphicient: trustworthy AI that doesn't monitor your employees Artificial Intelligence August 28, 2026 Graphicient: trustworthy AI that doesn't monitor your employees How Graphicient gives companies the means to configure guardrails against individual employee profiling. Read the article → Three factories connected by a data graph, each producing its own indicators BoM August 3, 2026 Multi-plant management: why your KPIs aren't comparable A real experience at a manufacturer — and why it isn't a reporting problem. Read the article → Augmented ontology: the shared language between your data, your teams and your AI Knowledge graph July 21, 2026 Augmented ontology: the shared language between your data, your teams and your AI Your data is full of answers. The problem isn't its volume, it's the lack of a shared language. Read the article → A rail bogie and its digital twin connected by a data graph BoM July 17, 2026 Industrial digital twin: blind without a reliable BoM The digital twin is billed as the holy grail of Industry 4.0. Without a reliable BOM, it sees nothing. Read the article → Compliance checklist for industrial AI: GDPR, Cloud Act sovereignty, AI Act obligations Artificial intelligence July 2, 2026 GDPR, sovereign hosting: what compliance for industrial AI? What a CISO or legal lead actually checks before approving an AI tool. Read the article → Your teams understand your data. Why aren't they in control of it? Data governance Business teams need to take back control of their data — the knowledge graph is the key Data belongs to those who understand it. Read the article → SQL sees columns. The graph sees meaning. Knowledge graph Product knowledge graph: structuring semantics where SQL falls short Your product catalog probably looks like a list of columns. Read the article →
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