The only AEO platform
where the AI shows its work.
39 agents watch your AI visibility while you work. When something changes — a competitor surges, a citation drops, an AI bot gets blocked — GetCited queues the exact fix in your inbox and tells you why. Not a black box. Not just an alert. You see the reasoning.
Detect. Decide. Queue. Show the reasoning.
Every competitor has alerts. No competitor shows you why the alert fired or what to do about it.
Signal detected
An agent detects a threshold crossing — citation rate drop, competitor surge, AI bot block, content decay, hallucination, schema error. 24 distinct signal types across 39 agents.
LLM decides
Before creating a task, the agent routes through an LLM with your full brand context. It weighs the signal, checks recent agent history, and decides: act, suppress, or escalate.
Reasoning shown
You see the situation report, the ranked action list, the confidence level, and the decision — in plain language. Not a black-box notification. Not just a badge count.
Task queued
If the agent acts, a structured inbox task is created with the recommended fix already attached. One click routes it to the Fix Dispatch Engine.
What agents monitor.
A sample from the 39-agent set. Every agent fires a structured inbox task — not a notification you dismiss.
Signal
Citation rate drops below threshold
What happens
Creates task: recover citation share
Signal
Competitor SOV surges ahead of your brand
What happens
Creates task: competitive analysis + rank-optimize
Signal
Brand uncited on a specific engine for N days
What happens
Alert + task: investigate engine gap
Signal
AI engine makes false claims about your brand
What happens
Creates task: fact-check + rebuttal content
Signal
GPTBot or ClaudeBot blocked in robots.txt
What happens
Creates task: unblock AI crawlers
Signal
Schema error detected on key pages
What happens
Creates task: schema validation + fix dispatch
Signal
Content not updated in 90+ days
What happens
Creates task: refresh content for citation recapture
Signal
Negative review detected on GBP or Trustpilot
What happens
Alert + creates task: draft reply
Signal
Wikipedia vs Wikidata vs site entity mismatch
What happens
Creates task: reconcile knowledge graph
Signal
Rapid citation velocity drop detected
What happens
High-priority alert + task
Every competitor with agents treats them as black boxes.
GetCited shows the work.
Profound has agents — opaque, no reasoning visible, no inbox integration. Semrush has threshold email alerts — no brand context, no action recommendation. Peec has a daily monitoring update — pull-based, you have to log in. GetCited is the only platform where the agent tells you what it saw, what it decided, and why — and drops the task directly in your inbox.
Common questions
How many agents are there?
39 agents across two modes: 23 trigger-based monitoring agents that fire when a specific signal threshold is crossed, and 16 scheduled cron agents that run on a set cadence (daily, weekly) to check for drift, decay, and opportunity.
What makes this different from a dashboard alert?
Three things. First, agents don't just alert — they create a structured inbox task with the recommended fix already attached. Second, every agent decision routes through an LLM that reads your full brand context before deciding whether to act, suppress, or escalate. Third, the reasoning is shown: you see the situation report, the action list, and the confidence level — not a black-box notification.
What is the LLM decision layer?
Before creating a task, each agent can optionally pass the triggering signal through an LLM call. The LLM receives the signal magnitude, your brand context (voice, products, competitors, keywords), and recent agent history for your account. It outputs a situation report, a ranked action list, a confidence level (high/medium/low), and a decision: act, suppress, or escalate. Every run is logged in full.
Can agents fire too often?
No — cooldown logic prevents the same rule from firing more than once per 24-hour window per client. This is built in to prevent alert fatigue, not bolted on as an afterthought.
Can I see what the agents did?
Yes. Every agent run — detection, LLM decision, and task creation — is logged in the agent_llm_runs and cron_run_log tables. You can audit exactly what the system decided last week and why. This is especially important for enterprise and agency clients who need to explain AI decisions to stakeholders.
Do I need to configure the agents?
No. Agents run automatically from the moment you connect your site and fill in your brand context. Thresholds use sensible defaults (e.g., citation rate drop >20% triggers an alert). Threshold customisation is available for clients who want tighter or looser sensitivity.
How do agencies use this across multiple clients?
Each client workspace runs its own agent set with client-specific brand context. Agents create tasks in the client's inbox, not a shared queue. Agency users see activity across all clients in the agency dashboard — flagged by severity so you know which client needs attention first.
Let the agents watch. You just approve and act.
Get access to the platform. Agents start monitoring from day one — no configuration required.