Are you, too, investing millions in AI infrastructure and yet still do not know which networks have formed within your customer base? Without a robust, traceable data foundation, even high-performance models remain blind to the relationships that truly make the difference.
Customer data is scattered across CRM, transaction, and external systems. Without cross-linking, the underlying networks remain invisible.
Risks and business potential often emerge across multiple tiers – through corporate shareholdings, roles, and shared addresses. Pure text analysis fails to capture this.
AI results must be explainable and auditable. Without proof of sources, black-box answers remain unsuitable for decision-making.
The client licenses the engine, not a pre-configured tool. The definition of use cases rests entirely with the user and does not tie them to a vendor roadmap.
The entire dataset and all algorithms, without restrictions to individual use cases.
Multi-tier evaluation of relationship paths with source verification for each connection – reproducible and audit-compliant.
Client-specific nodes and proprietary data integrated into the BusinessGraph within a protected, multi-tenant layer.
You license the engine, not a pre-configured tool – you define the use cases.
Language models formulate answers. The Palturai BusinessGraph provides the context, sources, and economic relationships against which these answers can be verified. Only the interplay of both components enables traceable enterprise intelligence applications.
What matters is not the size of the dataset, but its provenance and depth of verification – European primary registers with verifiable source documentation.
Commercial registers, sanctions lists, ownership structures, and other public registers form the baseline of the graph.
Currently covered are Germany, Austria, Switzerland, and the United Kingdom, with the US integrated in a beta release. In addition, internationally active companies are captured through cross-border shareholder structures.
Every connection in the graph remains traceable back to its source – providing the foundation for verification and documentation throughout the procurement process.
The engine remains identical across every deployment variant. Deployment and data location are chosen by the client – this is the key difference to providers that monopolize the entire system landscape.
On-premises deployment, hybrid, or in a European cloud.
Integration with applications, language models, and existing data environments – the customer selects the model and infrastructure.
Multi-tenancy, role-based access control, encryption, and end-to-end audit logging.
Documentation covering functionality, architecture, operations, and compliance evidence – aligned with the EU AI Act, DORA, the EU Anti-Money Laundering Regulation (AMLR), and ISO 27001.
