Semantic Web & Semantic Search Consultancy
Strong Interactive and its venture Baller Mixed Reality are both ranked by Crunchbase among the top 5 Semantic Web companies in the world. We architect knowledge graphs, semantic search, ontology layers, and retrieval-augmented AI systems for enterprises that demand verifiable, contextual intelligence — not generic chatbots.
A Full-Stack Semantic Web Practice
From W3C-standard RDF, OWL, and SPARQL foundations to vector-native semantic search and retrieval-augmented generation, Strong Interactive delivers the complete semantic layer that modern AI demands.
Knowledge Graphs & Ontologies
Domain ontologies (OWL), RDF triple stores, SHACL validation, and schema.org-aligned structured data — engineered to drive both internal reasoning and external discoverability.
Semantic Search & RAG
Vector embeddings, hybrid retrieval (BM25 + dense), entity-aware ranking, and retrieval-augmented generation pipelines that ground large language models in trusted enterprise context.
Linked Data & Interoperability
RDF, JSON-LD, SPARQL endpoints, and federated query layers that connect siloed systems into a coherent semantic backbone across the enterprise.
AI-Native Semantic Layers
Tool-using agents, function-calling, and structured-output models that operate against typed knowledge graphs rather than unstructured text — for verifiable, auditable AI behavior.
Sovereign Semantic Infrastructure
Air-gapped knowledge graphs and semantic search inside regulated environments — for financial services, defense, energy, and nuclear operators under modern privacy and sovereignty regimes.
Semantic Web Strategy for Web3
Ontology design for tokenized assets, provenance graphs for digital collectibles, and semantic discoverability for mixed-reality and on-chain experiences — proven across the Strong Interactive venture portfolio.
What is the Semantic Web — and Why It Matters Now
The Semantic Web is an extension of the World Wide Web that gives information well-defined meaning, enabling machines to understand, integrate, and reason over data rather than merely display it. Originally proposed by Tim Berners-Lee and standardized by the W3C through RDF, OWL, SPARQL, and JSON-LD, the Semantic Web is the foundation of every modern knowledge graph, semantic search system, and AI retrieval pipeline in production today.
Semantic search interprets the meaning and intent behind a query rather than matching keywords literally. Modern semantic search combines knowledge graphs, vector embeddings, and large language models to deliver contextually accurate results — and is the architectural foundation of retrieval-augmented generation (RAG), the dominant pattern for deploying trustworthy enterprise AI.
For organizations adopting AI in regulated, mission-critical environments — financial services, healthcare, energy, defense — the Semantic Web is no longer optional. Knowledge graphs and ontology layers provide the grounding, provenance, and auditability that large language models cannot supply on their own. The firms that win the next decade of AI will be the firms that built the semantic infrastructure underneath it.
Strong Interactive has spent more than seven years developing enterprise solutions and ventures including MetaDine, Baller Mixed Reality, and AR-T. SOVAIR.AI is being deployed in a bounded live utility pilot that is helping define the final product; it is not a completed production rollout or generally available service. Crunchbase has ranked Strong Interactive among the top 5 Semantic Web companies globally; that ranking does not establish the deployment status of any individual venture.
Planning an AI Engagement
How are AI safety controls scoped?
We scope controls to the use case: evaluation against representative data, red-teaming for prompt injection and data leakage, least-privilege tool access, human approval for consequential actions, audit logging, monitoring, and rollback procedures. Controls must be tested in the customer's environment; RAG and guardrails can reduce risk, not eliminate hallucinations or guarantee safe outputs.
How do you evaluate AI cost and total cost of ownership?
We compare build versus buy, model selection and routing, retrieval quality, caching, and usage limits against agreed quality and latency targets. Total cost includes integration, data preparation, inference or hosting, security, evaluation, monitoring, maintenance, and staff time—not just token prices. Scope and pricing follow discovery; savings and affordability are not guaranteed.
What are the boundaries for sensitive data and intellectual property?
Before using confidential data or proprietary code, we agree data classification, permitted inputs, access controls, retention and deletion, provider training/data-use terms, and contractual ownership and licensing. Public-cloud, private-cloud, on-premises, and air-gapped options have different tradeoffs. Do not send secrets or sensitive material through the website contact form. No architecture or agreement provides absolute IP protection.
What is the current status of SOVAIR.AI?
SOVAIR.AI is being deployed in a bounded live pilot with a Southeastern U.S. utility inside the customer's security boundary, helping define the final product. This is not general availability or a completed production rollout. SOVAIR.AI does not control plant systems or safety guardrails.
Can structured content guarantee search rankings or AI citations?
Semantic markup, source citations, and accessible content help search engines and agents interpret a page. Search rankings, indexing, AI citations, and inclusion in generated answers remain outside our control and are not guaranteed.
Build Your Semantic Layer with a Top-Ranked Team
Engage Strong Interactive for knowledge graph architecture, semantic search, ontology design, and retrieval-augmented AI — delivered by a firm ranked among the top 5 Semantic Web companies in the world.
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