# Agent Governance — AI Visibility at the Agent Layer > 9 runtime governance modules for the agent layer. The APM stack agents always needed — what mature teams stitch together from LangSmith + Datadog APM + W&B + a custom dashboard layer, shipped as one product. Canonical URL: https://neuralseek.com/agent-governance Alternate (HTML): https://neuralseek.com/agent-governance Content-Type: text/markdown; charset=utf-8 ## Hero Stats - **9** Agent Governance Modules - **5-axis** Component Attribution - **5-layer** Performance APM - **200+** Models Benchmarked - **AI-graded** Red Team Security - **100%** Audit Attribution ## Trust Anchors - Component-level attribution — every millisecond mapped to LLM / KB / REST / ML / parallel. - AI-graded red-team testing with auto-generated remediation guidance. - Customizable governance dashboards — add panels, edit views, build your own KPIs. - Cache savings tracked as a first-class FinOps metric. --- ## Three Pillars - **Component-Level Attribution.** Every agent run decomposed across five axes — Parallel · LLM · KB · ML Models · REST. APM-grade resolution applied to agentic workflows. - **AI-Audited Security.** Run the adversarial suite against any agent on demand. An LLM reads the results, scores the posture, and writes the remediation report. - **Customizable Governance.** Add Panel · Edit · Delete on every dashboard. Build governance views around your own KPIs instead of consuming a fixed set. --- ## The 9 Modules ### Module 01 · Flow Insights — Component-Level Agent APM Know exactly where every agent spends its time — and which component is the bottleneck. Four KPI tiles, a radar chart that attributes every agent's runtime across 5 component classes (Parallel · LLM · KB · ML · REST), and a run-time line chart by named agent. See whether an agent is LLM-bound, KB-bound, REST-bound, or parallelization-bound — at a glance. Tags: 5-axis radar · Component attribution · Equivalent seeks per run. Underplayed angle: the radar chart is a genuinely rare viz choice for agent observability. Most platforms give you a flat bar chart of latency. This shows shape — this agent is REST-heavy, that one is LLM-heavy — at a glance. ### Module 02 · Red Team Testing — AI-Graded Agent Security An AI auditor that tests your agent, grades it, and tells you exactly how to fix what's broken. Pick an agent, click Run Test. The platform runs the adversarial suite, then an LLM reads the results, scores the posture, identifies risks, and writes the remediation report — secret redaction, prompt-isolation, authorization enforcement, parameterized queries, retry/scope limits. An automated security analyst, built in. Tags: Self-serve · Per-agent scoring · Auto-generated remediation · 5 attack categories. Underplayed angle: Run Test → Grading Tests → Score is a self-serve security audit loop. CISOs can run this themselves, on demand, per agent. ### Module 03 · mAIstro Logs — Agent Run Forensics Every agent run. Every user. Every runtime. Searchable. Replayable. Every agent run, every user, every runtime — tabular, sortable, searchable, with a deep-link from each row into the full execution trace. System runs and named-user runs distinguished in the same log, so attribution covers both human-triggered and automated agent calls. Tags: Per-run audit · User attribution · Step-by-step replay. Underplayed angle: each row drills into the full agent execution trace. Step-by-step replay = forensic gold for any post-incident review. ### Module 04 · Token Insights — FinOps with Cache Economics Track every token. See exactly how much our cache is saving you. Ten gauges: total tokens, cost, input / generated per run, tokens per second — plus a unique class of cache metrics (NeuralSeek Cache Savings, Cached Input Tokens per run, Cached Generated Tokens per run, Cache Savings per 1k runs). The platform quantifies the dollar value of its own caching layer. Tags: Cache savings · Cost-per-1k · Tokens-per-second · Self-justifying ROI. Underplayed angle: NeuralSeek Cache Savings is a product self-justification metric — it literally quantifies the ROI of the platform's caching layer in dollars, every day. ### Module 05 · Cost Insights — Live Model Cost at the Agent Layer See cost by agent, by model, by run. No more black-box AI spend. The same 200+ model cost benchmark from /llm-governance, applied at the agent layer. Customers can attribute cost to specific agents, then drill into which models those agents called. The managed-tier models showing $0.00 are NeuralSeek's hosted offering, essentially included. Tags: 200+ models · Per-agent attribution · Managed-tier $0.00. Underplayed angle: the managed-tier models showing $0.00 is a "free credits" story buried in a cost chart. ### Module 06 · Model Comparison — Bake-Offs with Agent Score Test models head-to-head — at the agent level, not just the LLM level. Pick configured models, select an agent, run side-by-side. Results table shows Response Time, Response Score, and — uniquely — Agent Score, which evaluates not just LLM response quality but whether the agent completed its workflow correctly. Workflow-completion benchmarking, not just response quality. Tags: Agent Score · Workflow completion · Previous Runs archived. Underplayed angle: Agent Score is a different and more demanding evaluation than raw LLM Rank. It captures whether the agent achieved its goal — which is what enterprises actually care about. ### Module 07 · Agent Growth — Customizable Governance Dashboards Build governance dashboards tailored to your KPIs. Add Panel · Delete Dashboard · Edit toggle on every dashboard. Admins construct their own governance views — not just consume the canned ones. Most observability platforms ship fixed dashboards. This one lets the customer build their own around the KPIs they care about. Tags: Add panel · Edit dashboard · Delete dashboard · 280 agents tracked. Underplayed angle: customizable dashboards deserves its own marketing moment. Most governance tools are rigid; this one is user-extensible. ### Module 08 · Users — Identity-Aware Governance Every action. Every user. Every login. Tracked. Three panels: a list of every GUI login with last-login timestamps, a count of Seek users, and a donut chart of mAIstro users segmented by session ID and email. Human-email users and machine-session callers tracked in the same view — important for service-account governance. Tags: Login recency · Service-account governance · Per-user audit. Underplayed angle: login recency tracking is the data a CISO needs to detect dormant or compromised accounts. Standard SIEM input. ### Module 09 · System Performance — Three-Tier Infrastructure APM Your AI is slow. Here's exactly which component to blame. Three stacked area charts decompose AI runtime by guardrail / processing layer — Categorization, PI Protection, KB, Answer Generation, Scoring. Three tiers (Instance · Instance Detail · Universe) let you triangulate: is the issue a single instance, a guardrail layer, or the whole deployment? Tags: 5-layer APM · Instance · Detail · Universe · Guardrail-stack timing. Underplayed angle: the per-layer breakdown (Categorization / PI Protection / KB / Answer Generation / Scoring) maps directly to the guardrail categories — governance data for the guardrail stack itself. --- ## Cross-Cutting Themes Five disciplines that distinguish the agent-governance plane from a thin observability dashboard: - **Component-level attribution.** Every millisecond mapped across 5 axes. - **AI-audited security.** Automated security analyst writing remediation reports. - **Customizable governance.** Add Panel · Edit · Delete on every view. - **Cache economics.** Cache savings as a first-class FinOps metric. - **Agent Score (≠ LLM Score).** Workflow-completion evaluation, not just response quality. --- ## Related Resources - HTML page: https://neuralseek.com/agent-governance - 118 AI Guardrails (configurable control surface): https://neuralseek.com/guardrails - LLM Governance (LLM-layer counterpart): https://neuralseek.com/llm-governance - Platform overview: https://neuralseek.com/ - Documentation: https://documentation.neuralseek.com/ - Trust Center: https://neuralseek.com/trust-center - Contact us: https://neuralseek.com/contact