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Semantica is used across academia, enterprise, and independent research. Below is a snapshot of the ecosystem being built by the community.

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Projects Using Semantica

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Research & Academia

Teams in academia are using Semantica to build structured, auditable knowledge from unstructured scientific literature.
  • Academic literature mapping: citation graph construction across multi-year corpora with temporal provenance
  • Biomedical knowledge graphs: connecting genes, proteins, drugs, and diseases from PubMed and preprint feeds
  • Social network analysis: community detection and influence analysis over entity-linked interaction graphs
  • Computational linguistics: coreference resolution pipelines with entity-linked output for downstream NLP tasks

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Enterprise & Industry

Production deployments span regulated and high-stakes industries where AI accountability is not optional.
  • Business intelligence: corporate knowledge bases built from filings, reports, and internal documentation
  • Cybersecurity & threat intelligence: adversary attribution graphs, CVE-linked threat feeds, incident timelines
  • Healthcare & clinical AI: patient safety graphs, drug interaction knowledge bases, HIPAA-compliant audit trails
  • Financial services: fraud detection graphs, regulatory compliance pipelines (SOX/GDPR/MiFID II), risk lineage
  • Legal & compliance: contract analysis pipelines, regulatory change tracking, evidence-backed research graphs
  • Critical infrastructure: supply chain risk graphs, energy grid event graphs, logistics provenance

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Independent & Open Source

  • GraphRAG toolkits: custom retrieval layers built on top of Semantica’s context + vector_store modules
  • Domain-specific extractors: NER and relation extractors for clinical, legal, and scientific text
  • Temporal graph dashboards: visual timelines built with Semantica’s TemporalKnowledgeGraph + custom visualization adapters

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Supported Integrations

StoreNotes
FAISSIn-process, CPU/GPU
PineconeManaged vector cloud
WeaviateSchema-first hybrid search
QdrantHigh-performance Rust-native
MilvusEnterprise-scale distributed
PgVectorPostgres-native for SQL stacks

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Community Extensions

The plugin system (PluginRegistry) makes it easy to add new capabilities without touching core code. The community has built:
  • Custom entity extractors: domain-specific NER for clinical entities, legal clause types, and financial instruments
  • Export adapters: specialized serialization formats for proprietary industry systems
  • Ingestor plugins: adapters for SharePoint, Notion, Confluence, and custom databases
  • Visualization plugins: enhanced dashboards with Plotly, D3.js, and custom graph renderers
  • Evaluation harnesses: domain-specific precision/recall benchmarks using semantica.evals

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Build Your Own Extension

Any Semantica component can be extended via the registry pattern: 
from semantica.ingest.registry import method_registry

def my_ingestor(source):
    return [{"text": "...", "metadata": {}, "source": source}]

method_registry.register("file", "my_format", my_ingestor)
See Architecture for the full extension guide.

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How to Contribute

Contributing Guide

Submit code, documentation, tests, or cookbook notebooks.

GitHub Issues

Report bugs, request features, or propose integrations.

Discord

Share what you’re building with the community.

GitHub Discussions

Long-form questions, design discussions, and ideas.