Corpus & graph

We help you structure the company knowledge that AI needs to become useful: documents, data, numbers, entities, relationships and industry context. The corpus captures what the company knows. The graph connects what the company depends on.

This is where operational reality becomes usable intelligence. Products, suppliers, customers, contracts, KPIs, locations, processes, risks and constraints are no longer scattered across systems and documents. They become part of one connected foundation that AI can retrieve from, reason over and explain.

Sovereignty by design

Your corpus contains the core of the company: operational data, customer logic, supplier exposure, contracts, planning rules and strategic context. That intelligence belongs inside the company walls. Local, on-prem, secure. No cloud dependency. No concession.

This is not only a security choice. It is a strategic choice. The more complete the corpus becomes, the more valuable it becomes. That value should not move into external platforms, generic cloud services or vendor-controlled environments. The company keeps control over its data, context, permissions and intelligence layer.

Technology-independent

Once the corpus is in place, AI can finally be used to its full potential. Retrieval, agents, reasoning, scenarios and decision support all build on the same foundation. If a better model arrives tomorrow, we connect it locally. The corpus remains the asset.

That is the long-term strategy. Models will change, interfaces will change and new AI capabilities will keep arriving. A strong company corpus makes the organization ready for all of it. Instead of rebuilding from scratch, the company can plug new AI into a governed intelligence base that already understands the business.

Building

We identify, structure and connect the information that matters: documents, numbers, entities, rules, contracts, industry context and operational logic. The result is a governed corpus built on a graph.

Intelligence

We use that corpus to power AI workflows: retrieval, agents, scenarios, decision support and transparent answers. New models can be connected later; the company corpus remains the foundation.

A vertical AI system needs more than a document library. It needs a company corpus that captures the information that explains how the organization works: contracts, policies, process descriptions, product information, templates, surveys, plans, reports, data sources and external signals. This is where scattered knowledge becomes usable context.

The goal is not to ingest everything blindly. The goal is to build a healthy corpus: structured, traceable, searchable and relevant to the business questions the system must support. Every source should have a role. Every document should contribute to the intelligence layer.

The graph connects the information that matters: suppliers, materials, products, customers, locations, processes, risks, regulations, KPIs and decisions. This is what allows use to move beyond text retrieval and start understanding relationships, dependencies and consequences. Especially, the capability to run that numbers with the graph is really an asset.
A port disruption is not just a news item. It can be connected to shipping lanes, inbound materials, production sites, customer orders, service commitments and financial exposure. The graph makes those connections explicit, inspectable and usable for reasoning.

This foundation is built together with the people who understand the industry and the company. Our background in supply chain analytics, optimization and strategic decision support matters here. We have worked with business leaders, supply chain directors, planners, analysts and operational teams on the questions that define real-world performance.

We build this industry by industry, together with partners and domain experts. That takes time, but it is also what makes the vertical useful. We already have six verticals up and running: fashion, chemicals, maintenance, ingredients, hightech and medtech.

Industry Vocabulary

This is where the numbers, entities and relationships of the company are organized. Products, suppliers, materials, customers, locations, flows, inventories, service levels, risks, KPIs, costs and constraints are connected through our proprietary graph approach.

Operating Models

This is where the system starts to understand how a specific organization works. Contracts, SLAs, process descriptions, strategy documents, supplier files, customer agreements, planning procedures, meeting documents. It is the creation of a usable intelligence base for the company.

Standards & Practices

This is the part we bring. We have pre-build industry specific layers with domain context. This includes industry language, regulations, typical processes, legislation, common risks, decision frameworks, relevant standards. It enriches the total corpus.