Semantic Infrastructurefor Trustworthy Enterprise AI. Governed Context and Semantic Layer with Decision Intelligence for AI Agents, LangGraph Workflows, Claude Code, CrewAI Teams, LlamaIndex Pipelines, AutoGen, Production AI, Enterprise AI, Any AI Framework
The graph-native layer of context, business semantics, and provenance beneath your LLM, vector store, and agents, with causal reasoning so every AI decision can be traced back to why.
Ontologies and controlled vocabularies (OWL, SHACL, SKOS) make what an entity means to your business, its definitions, relationships, and rules, as explicit as the data itself, not just its embedding.
Built for high-stakes work. Proven in production.
Auditable by design. Every fact traced to its source.
Industrial Technology · Global EngineeringIndustrial Technology · Global EngineeringRaw Enterprise Data In.
Trusted AI Decisions Out.
Semantica sits between your data sources and your AI agents as a governed context and semantic layer, turning fragmented records into structured context, business semantics, and provenance your agents can reason over.
Raw enterprise data
Databricks
Unity Catalog · Delta Lake
Snowflake
Warehouses & tables
SAP
OData v2 / v4
Salesforce
CRM objects
Documents & PDFs
Contracts, reports, filings
Streams & APIs
Kafka · Kinesis · REST
Databases
PostgreSQL · MySQL · Oracle
Semantica
Governed Context / Semantic Layer
Ingest & Extract
Connectors · NER · relations · dedup
Context Graph
Entities · decisions · temporal facts
Ontology & Vocabulary
Classes · concepts · relationships
Business Semantics
OWL · SKOS · SHACL
Reasoning & Provenance
Rete · Datalog · W3C PROV-O
AI agents & apps
Claude Code
Plugin · MCP
Cursor
Plugin · MCP
LangChain
Native integration
CrewAI
Native integration
Agno
Native integration
Any agent
REST API · MCP
Keeps your stack
Your LLM, vector store, and agent framework stay exactly as they are.
Deterministic core
Graph construction, reasoning, and provenance need no LLM.
Governed by design
Conflicts flagged, ontologies enforced, every fact traced to its source.
Business semantics, explicit
OWL ontologies, SKOS vocabularies, and SHACL rules define what every entity means to your business.
See Semantica
in Action
A complete walkthrough of Knowledge Explorer, Context Graphs, Reasoning Engine, Decision Intelligence, and Ontology Hub.
From Fragmented Data
to a Governed Context / Semantic Layer
Every stage is a shipping module you can import on its own. Conflicting facts are flagged before they merge, and provenance is captured at every step.
Ingest
Files, warehouses, streams, Databricks, Snowflake, SAP, Git, email
Parse & Normalize
Documents, entities, dates, and numbers cleaned into one shape
Extract
Entities, relations, events, and triplets pulled from raw content
Resolve
Conflicts flagged and duplicates merged, never silently overwritten
Build the Graph
A queryable Context Graph with bi-temporal facts and analytics
The intelligence layer
Runs on the knowledge graph, deterministic and explainable
Ontology & SKOS
OWL ontologies, SKOS vocabularies, and SHACL rules make business semantics explicit
Reasoning
Rete, Datalog, and SPARQL with explainable paths
Provenance
W3C PROV-O lineage on every fact
Decisions
Causal chains, precedents, and policy gates
Polyglot storage
RDF triple stores, property graphs, and vector stores, swappable without touching your code.
Delivered your way
Plug agents and apps in through the interface that fits.
Every decision,
traceable to why.
A decision is not a log line. It is a first-class graph node, linked to its causes, precedents, policies, and source evidence, and exportable for the regulator who asks.
Causal chains. Every decision links to what caused it and what it influenced.
Policy gates. Decisions are checked against SHACL and business rules before they stand.
Source lineage. Every fact traces back to the document, table, or system it came from.
Loan A-7291 approved
loan_underwriting · decision node
Application passed intake
credit_application · confidence 0.88
Loan A-6120: similar DTI, approved
semantic match 0.91
Debt-to-income within limit
SHACL rule DTI ≤ 40% · passed
36-month credit history
Snowflake · CREDIT.SCORES
Income statement
income_2024.pdf · page 2
System-level explainability,
not foundation-model explainability
Semantica doesn't expose the LLM's internal reasoning. It explains what's outside the model.
What Semantica Explains
System-level explainability: everything outside the model, recorded as a first-class, auditable object.
- Context fed into the model
- The decision produced
- Full provenance & lineage
- Complete audit trail
What Semantica Doesn't Explain
Foundation-model explainability: Semantica doesn't expose or reconstruct an LLM's internal reasoning, which stays opaque, as it does for any external system.
- The LLM's internal weights
- Its hidden chain-of-thought
- Attention or activation internals
- Any foundation-model interpretability
Engineered for the domains
where mistakes aren't an option
No proprietary format, no closed pipeline, and no black box. Just infrastructure regulated teams can stand behind.
Built for High-Stakes, Regulated Domains
Energy, Finance, Healthcare, Pharma and Life Sciences, Climate and Marine Ecology, Nature Intelligence, Sovereign Infrastructure, and Legal teams run Semantica where GDPR, EU AI Act, and HIPAA audits are non-negotiable.
Start Free, Scale Your Way
Start free and prove value on your own data with a pilot. Then scale on Managed Cloud, a dedicated platform we run for you, or deploy on your own infrastructure with an Enterprise Forward Deployment. Same platform, your choice, backed by SLAs.
Zero Vendor Lock-in, Dedicated by Design
Every deployment is dedicated to your organization and never shared, even when data is pulled straight from Databricks, Snowflake, or your existing warehouse. Swap between Neo4j, FalkorDB, RDF triple stores, and labeled property graphs behind one API, and export your full graph back out cleanly if you ever want to leave.
Full, Exportable Provenance
W3C PROV-O compliant lineage on every decision, producing an audit trail a regulator can actually read.
Ready to Build
Trustworthy AI?
Give your AI systems a governed context and semantic layer, with business semantics, decision intelligence, and full provenance tracking. Start free, prove it on your data, then scale on Managed Cloud or your own infrastructure.
pip install semantica