AgentOps
About this demo

AgentOps — an AI agent governance control tower

A portfolio demonstration by Trevor Fischer · Fischer Product Lab — secure AI systems for trust, risk, and enterprise execution.

Why AgentOps

Enterprises are deploying AI agents faster than they can govern them — ticket triage, release notes, support summaries, policy Q&A. Each is spun up by a different team, touches different data, and holds different tool permissions. Leadership rarely has one place to answer the questions that matter: which agents exist, who owns them, what can they touch, and which are actually safe to scale?

AgentOps turns that sprawl into a single governed, measurable, executive-ready view — so the decision to scale, pause, or govern an agent is backed by evidence rather than instinct.

How readiness works

Every readiness verdict is a pure, deterministic function — no AI calls — which is what makes it explainable and auditable.

  1. 1Seven weighted criteria (scored 0–4) are normalized into a 0–100 score.
  2. 2The score maps to a band: Launch (80+), Conditional (60–79), Needs Review (40–59), or Do Not Launch (<40).
  3. 3Hard safety gates override the band: if data safety or tool-permission risk hits the critical floor, the verdict is capped or blocked — a strong average can never bury a critical risk.

The thesis in one line: a strong agent that is unsafe is still unsafe — and the scoring encodes that judgment so it can't be averaged away.

Security posture

  • Synthetic data only — no real customer, employer, or personal data.
  • Read-only — no write endpoints, forms, or admin surface.
  • No client-side secrets; zero environment variables required.
  • Deterministic scoring — explainable, auditable, no black box.
  • Documented STRIDE threat model and security policy.
  • Hardened supply chain — Dependabot, secret scanning, CodeQL.

Part of the Fischer Product Lab suite

AgentOps governs AI initiatives before they ship. Its sibling products cover the rest of the lifecycle — each a read-only, synthetic-data demo with a deterministic engine at its core.

Built with

  • Next.js 16
  • React 19
  • TypeScript (strict)
  • Tailwind CSS v4
  • Recharts
  • Zod