Case studies
Open-source tools, applied research, and production-grade delivery outcomes.
OntoGuard: Production-Grade Ontology Firewall for AI Agents
Built and open-sourced a production-grade ontology firewall that validates AI agent actions against OWL-encoded business rules in real-time. Enforces role-based access control, amount constraints, time windows, and compliance rules. Provides human-readable explanations for every blocked action and a full audit trail for regulatory compliance.
8
GitHub stars
3
Enterprise domains demonstrated
5.2K
Views on launch article
Power BI Ontology Extractor: Unlocking 20M Hidden Ontologies
Built a tool that transforms Power BI data models into AI-ready ontologies — automatically extracting entities, relationships, and business rules from DAX measures. Generates OWL ontologies and MCP-compatible semantic contracts, enabling AI agents to reason over existing dashboard intelligence.
8
GitHub stars
25K
Views on companion article
20M+
Addressable Power BI dashboards globally
Self-Healing Multi-Agent System with MCP
Built an open-source multi-agent system that uses OWL ontologies and Model Context Protocol (MCP) to automatically adapt when database schemas change. Zero manual code fixes required on schema drift — the ontology layer detects changes and re-maps agent queries in real-time.
11
GitHub stars
4
Forks
5.4K
Views on companion article
AI Agent Backend Benchmark: PostgreSQL vs Vector DB vs OWL Ontology
Conducted a rigorous three-way benchmark testing PostgreSQL, vector databases (Pinecone), and OWL ontology as backends for AI agent decision-making. Tested across loan approval domain with regulatory constraints. Conclusion: none of them won alone — a query router combining all three is the production answer.
3
Backend approaches benchmarked
19
Files in companion GitHub project
1.1K
Views on companion article
Open source
Production-grade tools we build and maintain. Featured projects first.
ontoguard-ai
Production-grade ontology firewall governing AI agent behaviour in enterprise environments. Semantic validation, role-based access, constraint checking.
ontology-mcp-self-healing
Self-healing multi-agent system using OWL ontologies and MCP to auto-adapt on database schema drift. Zero manual code fixes.
powerbi-ontology-extractor
Transforms Power BI data models into AI-ready ontologies, unlocking semantic reasoning across 20M+ existing dashboards.
universal-agent-connector
MCP infrastructure with ontology-driven semantic routing enabling AI agents to connect to any enterprise data source.
legacy-to-logic
Transforms legacy database schemas into AI-ready ontology infrastructure. The CLI tool behind the Extract-Model-Deploy methodology.
ai-agent-backend-benchmark
Three-way benchmark: PostgreSQL vs vector DB vs OWL ontology as AI agent backends. Spoiler: none of them won.
from-protege-to-production-python
End-to-end codebase for integrating OWL ontologies built in Protégé directly into Python-based AI pipelines.
the-napkin-architect
Sketch-to-infrastructure-blueprint tool. Draw on a napkin, get production architecture. AI-powered technical design.