Mohd KaifandClaude Sonnet 4.6
b282487b17
- Rewrote index.md to match README (tagline, badges, Problem/Solution text) - Improved getting-started, concepts, quickstart, installation, faq, use-cases, contributing, glossary, learning-more, examples, modules, architecture, cookbook, deep-dive pages: tighter prose, fixed headings/bullets, removed inconsistencies and duplicate sections - Removed overuse of emojis from headings in integration pages (docling, snowflake) - Fixed change_management reference page: closed unclosed JSON code block that broke the right TOC, demoted noisy sub-headings to bold text - CSS layout: widened content area (max-width 1440px grid, left sidebar 11rem, right TOC narrowed to 11rem for broader content), tightened TOC spacing and font size, fixed word-wrap/overflow on TOC links - Added mkdocs_local.yml for local serving without mkdocs-jupyter plugin Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
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Use Cases
Real-world applications of Semantica across domains, with linked cookbook notebooks for each.
Overview
| Use Case | Domain | Difficulty | Estimated Time |
|---|---|---|---|
| Biomedical Knowledge Graphs | Healthcare | Intermediate | 1–2 hours |
| Financial Data Integration | Finance | Intermediate | 1–2 hours |
| Fraud Detection | Finance | Advanced | 2–3 hours |
| Blockchain Analytics | Finance | Intermediate | 1–2 hours |
| Cybersecurity Threat Intelligence | Security | Advanced | 2–3 hours |
| Criminal Network Analysis | Security / Intelligence | Intermediate | 1–2 hours |
| Intelligence Analysis Orchestrator | Intelligence | Intermediate | 1–2 hours |
| Supply Chain Optimization | Operations | Intermediate | 1–2 hours |
| Renewable Energy Management | Energy | Intermediate | 1–2 hours |
| GraphRAG | AI | Advanced | 1–2 hours |
Difficulty levels:
- Beginner — basic Semantica knowledge only
- Intermediate — some domain knowledge helpful
- Advanced — domain expertise + advanced Semantica features
Research & Science
Biomedical Knowledge Graphs
Connect genes, proteins, drugs, and diseases from scientific literature and databases to accelerate drug discovery and understand disease pathways.
Cookbooks:
- Drug Discovery Pipeline — PubMed RSS ingestion, entity-aware chunking, GraphRAG, vector similarity search
- Genomic Variant Analysis — bioRxiv RSS, temporal KGs, deduplication, pathway analysis
Finance & Trading
Financial Data Integration
Unify financial data from APIs, MCP servers, and real-time streams into a single queryable knowledge graph.
Cookbook: Financial Data Integration (MCP) — Alpha Vantage API, MCP servers, seed data, real-time ingestion
Fraud Detection
Detect complex fraud rings using temporal graphs and pattern detection over transaction, device, and user data.
Cookbook: Fraud Detection — temporal KGs, cycle detection, fraud pattern analysis
Blockchain Analytics
Map transaction flows, analyze DeFi protocols, and detect illicit activity across wallet and exchange networks.
Cookbooks:
Security & Intelligence
Cybersecurity Threat Intelligence
Ingest threat feeds (CVE databases, security RSS), detect anomalies in streaming data, and build threat intelligence knowledge graphs for proactive defense.
Cookbooks:
Criminal Network Analysis
Build knowledge graphs from police reports, court records, and OSINT feeds to identify key players, communities, and suspicious patterns using network centrality analysis.
Cookbook: Criminal Network Analysis
Intelligence Analysis Orchestrator
Process multiple intelligence sources in parallel using an orchestrator-worker pipeline pattern with multi-source conflict detection and integration.
Cookbook: Intelligence Analysis Orchestrator-Worker
Industry & Operations
Supply Chain Optimization
Map suppliers, logistics routes, and inventory levels to identify bottlenecks and optimize global supply chains.
Cookbook: Supply Chain Data Integration
Renewable Energy Management
Connect sensor data, weather forecasts, and maintenance logs to predict equipment failures and optimize grid operations.
Cookbook: Energy Market Analysis
Advanced AI Patterns
GraphRAG (Graph-Augmented Generation)
Use knowledge graphs to retrieve precise, structured context for LLM responses — with hybrid retrieval, logical inference, and source attribution.
Cookbooks:
- GraphRAG Complete — production-ready implementation
- RAG vs. GraphRAG Comparison — side-by-side comparison
Next Steps
- Cookbook — full notebook catalog organized by topic and difficulty
- Modules Guide — every module with examples
- API Reference — complete technical documentation
!!! info "Have a use case to add?" Open a PR or start a discussion on GitHub.