d.AP review
A capable cloud ontology graph for enterprises that need semantic context and AI access.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
d.AP is an ontology-based knowledge graph and AI context platform for enterprises. It connects ERP, CRM, analytics, MES, IoT, and document systems through a federated semantic layer while leaving those systems in place. The Ontology Workbench supports visual RDF/OWL modeling of business classes, relationships, and rules. Aluna translates natural-language questions into graph queries, while dashboards, metrics, APIs, and agents use shared definitions. It is aimed at organizations that need ontology modeling, semantic reasoning, SPARQL, graph visualization, and governed AI access in one cloud platform.
Pricing is handled through sales, with licensing based on data sources and use cases. The published positioning describes a cloud deployment that can run in a customer's environment as a managed service or as SaaS. This structure may suit enterprises with varied deployments and integration requirements, but buyers will need a direct commercial discussion before comparing plans or estimating costs. d.AP provides REST, JDBC, and SOAP integrations, alongside REST, MCP, and A2A access, giving technical teams several ways to connect applications, dashboards, and agents.
The platform's main depth is its combination of ontology modeling, reasoning traces, provenance, SPARQL-backed dashboards, and natural-language graph queries. Role-based permissions and SSO/SAML support add governance for enterprise use. That breadth makes d.AP a fit for teams building a shared semantic layer across business systems and AI workflows. It is less suitable for organizations seeking a narrowly focused graph tool, a self-managed deployment, or straightforward published pricing. Buyers should choose d.AP when federated ontology graphs and AI-assisted querying are central requirements; teams that need deployment beyond cloud environments should consider another product.
d.AP pros and cons
- Where it wins
- Visual RDF/OWL modeling with ontology reasoning and provenance traces
- Natural-language queries through the Aluna AI agent
- REST, MCP, A2A, dashboards, permissions, and SSO/SAML access
- Where it doesn't
- Cloud-only deployment limits infrastructure choices
- Contact-sales pricing reduces upfront cost transparency
- Its enterprise scope may exceed narrower graph projects
d.AP fact sheet, pricing and score →
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