Production AI systems: autonomous platforms, content pipelines, ticket triage, and business reporting automation.
Self-hosted autonomous AI platform: planner→helpers→synthesizer LLM loop, autonomous multi-task crew board, bench-driven model router, tiered memory, and an hourly self-auditing agent that files its own improvement tasks.
1,973 automated tests · 6-scanner self-audit loop · Prompt-injection screening at every LLM boundary
End-to-end editorial automation: scraper agent surfaces trending topics, analysis agent synthesizes angles, generation agent drafts, a simulated audience panel scores drafts, and the top 30% publish with AI-selected imagery — minimal human intervention.
Replaced a fully manual editorial workflow · Audience-panel scoring selects top 30% of drafts · Runs end-to-end: research → draft → review → publish
AI-assisted support triage using a local LLM: reviews incoming tickets against historical data, surfaces relevant solution tickets and documentation in-ticket, and reclassifies type, board, and priority before assignment.
Solution candidates surfaced in-ticket, automatically · Auto-reclassification before an engineer ever opens it · Extending to skills-based auto-routing
Claude + Microsoft Fabric pipeline that turns raw ticket metrics from Power BI into client-ready narrative QBR reports with charts — distributed automatically by email and Teams, with on-demand generation via a Copilot agent.
Quarterly reports generated and distributed hands-free · On-demand ad hoc QBRs from a Copilot agent · Raw metrics → client-ready narrative, automatically