GStars
    semantica-agi

    semantica-agi/semantica

    Graph-Native Infrastructure for Context and Accountable AI Systems

    ai
    data-engineering
    developer-tools
    llm
    agent-memory
    ai-governance
    ai-infrastructure
    artificial-intelligence
    context-engineering
    Python
    MIT
    14.5K stars
    1.7K forks
    65 GitHub watchers
    Updated Nov 8, 2026
    View on GitHub

    Build with Backblaze B2

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 47 days ago, with 145 contributors on GitHub.

    Peaked at #1 in the weekly ranking the week of Aug 9, its best in the past year.

    Use Cases & Benefits

    • Provides graph-native infrastructure to build context graphs and knowledge graphs with full decision provenance for accountable AI systems.
    • Enables deterministic, explainable, and auditable AI decision intelligence with built-in conflict detection and compliance-ready provenance exports.
    • Use for building regulated AI systems requiring traceable, queryable decision records and audit trails in finance, healthcare, or legal domains.
    • Use for integrating enterprise data platforms like Databricks or Snowflake to create governed, lineage-tracked knowledge graphs without data export.
    • Use for data and knowledge engineers needing entity resolution, semantic deduplication, and multi-source graph construction with ontology governance.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    MIT

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Ingest your enterprise data, extract what matters, build a Context Graph and knowledge graph (KG), and run graph analytics and causal reasoning over all of it, with full decision provenance baked in. Explainable, traceable, and trustworthy by design.

    Decision Intelligence  ·  Context Management  ·  Deterministic Reasoning  ·  Ontology Management  ·  Knowledge Modeling  ·  End-to-End Traceability

    Open Source  ·  Self-Hostable  ·  Auditable  ·  Governed  ·  Zero Vendor Lock-In

    Polyglot Graph Storage  ·  RDF & LPG Support  ·  W3C Standards  ·  Interoperable

    Knowledge Explorer · Context Graphs · Reasoning Engine · Decision Intelligence · Ontology Hub

    Most AI agents act without a trail. They store embeddings, not meaning: context that can't be explained, decisions that can't be audited. In lending, that gap is a compliance exposure, not an inconvenience: an underwriting agent's approval has to survive a regulator's "why" months later.

    Semantica sits underneath your LLM, vector store, and agent framework as a deterministic infrastructure layer: no LLM required for graph construction, reasoning, or provenance.

    Excerpt from the semantica-agi/semantica README on GitHub (MIT license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 12: +838Aug 13: +836Aug 14: +1,011Aug 15: +439Aug 16: +279Aug 17: +322Aug 18: +471Aug 19: +527Aug 20: +322Sep 3: +156Sep 4: +130Sep 5: +96Sep 6: +84Sep 7: +111Sep 8: +120Sep 9: +113Sep 10: +89Sep 11: +91Sep 12: +60Sep 13: +59Sep 14: +67Sep 15: +28

    +9,739 stars over 90 days across 28 snapshot days; best day +1,011 on Aug 14.

    Forks

    1.7K+1.2K

    Open issues

    117+62

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth

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