The Platform

This site reflects the engineering approach I use to build enterprise AI systems: reliable foundations, clear tooling boundaries, and measurable outcomes.

Core building blocks

• Retrieval & Knowledge: structured chunking, embeddings, search, citations, evaluation
• Agents: planner + specialist roles (PM/Writer/QA patterns), tool calls, guardrails
• Tool layer (MCP/connectors): Jira/ServiceNow/KB integrations with scoped permissions
• Reporting: templates, charts, export to HTML/PDF, review/approval workflows
• Cost & governance: multi-model routing, quotas, telemetry, chargeback dashboards

Reference workflow

1. A user opens a ticket (or submits data) requesting an outcome.
2. The system selects the right template/agent workflow.
3. Agents gather context (tools + KB), draft the artifact, and validate against QA rules.
4. Outputs are published (report, FAQ, action items), and alerts are generated when thresholds are met.

Live demos

• AI Engineering Assistant (demo) — scoped to platform + delivery questions
• Report generation outputs — templates + charts + PDF export (examples)

If you want, I can embed a read-only preview of your real dashboard/report pages here (safe demo, no auth exposure).