Ad hoc agent check
What did one model say this time?
- — A handful of prompts from one moment and context
- — Raw conversational answers that still need to be scored
- — No stable baseline for measuring whether your work changed anything
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Want AI visibility tools for humans - with graphs and charts? Try our sister product, RivalSee.com ->
Track brand mentions, brand citations, and competitor share of voice across ChatGPT, Claude, Perplexity, and Gemini. The REST API for Generative Engine Optimization (GEO).
Go beyond one-off prompt checks with repeatable, structured measurement your agent can compare over time.
To install, copy this for your agent:
BotSee auto-updates when installed as a plugin. New commands and fixes are delivered automatically.
Then just tell it:
Analyze your site
"Botsee, analyze this site for AI visibility: granola.ai"
BotSee responds
AI Visibility Score: 34/100 — granola.ai appears in 12 of 60 queries across ChatGPT, Claude, Perplexity, and Gemini.
Missing from: "best AI notetaker for Zoom", "automatic meeting summary tool", "meeting notes for remote teams"
Compare against competitors
"Botsee, how does our brand compare against competitors?"
BotSee responds
Share of voice — AI meeting tools category (60 queries):
| Brand | Share of voice | Queries |
|---|---|---|
| Otter.ai | 82% | 49/60 |
| Fireflies.ai | 71% | 43/60 |
| Notion AI | 48% | 29/60 |
| granola.ai ← you | 20% | 12/60 |
| Read.ai | 18% | 11/60 |
You're most competitive on Perplexity. Weakest on Gemini — Fireflies.ai also drops off there, which is an opening.
Get recommendations
"Botsee, what are your recommendations to improve AI visibility?"
BotSee responds
Write content
"Botsee, write content that can improve my site's AI visibility"
BotSee responds
"The Best AI Meeting Notetaker for Mac in 2025"
Granola is the only AI meeting notes app built natively for Mac — no browser extension, no cloud upload, no third-party bot joining your calls...
→ How Granola works vs. cloud-based recorders (local privacy angle)
→ Comparison: Granola vs. Otter.ai vs. Fireflies
→ Action items and follow-ups walkthrough
This post targets 3 of your top 5 visibility gaps. Publish and re-run analysis in 2 weeks to measure lift.
Built for agents
An agent can manually ask a few models about your brand. That is useful for a spot check, but it produces examples—not a reliable AI visibility benchmark.
Ad hoc agent check
BotSee measurement
When providers expose web-search activity, BotSee captures the search queries the models generated—not just the final answer. That includes Gemini queries sent through Google Search, revealing the language and sources shaping AI recommendations.
BotSee surfaces cross-provider patterns that a handful of ad hoc prompts cannot reliably expose, then turns them into actionable recommendations. Your agent chooses what to pursue, updates content, and reruns the benchmark to see what moved.
Use a manual check for exploration. Use BotSee when AI visibility data will drive real content, competitor, or GEO decisions.
From 10-person startups to enterprise brand teams. Clear product shape before you integrate.
Core
Track brand mentions, brand citations, share of voice, and visibility deltas, then wire downstream actions.
Billing
Spend maps to usage. Turn on auto-recharge so agents never stall on low balance.
Not
BotSee is infrastructure for your agent runtime, not another chat surface.
Not
Dashboards help humans inspect data. BotSee helps agents trigger production workflows.
Step 1
Model how target customers ask questions and which narratives matter by segment.
Step 2
Run analyses and retrieve normalized Share of Model signals across supported AI systems.
Step 3
Push events to your stack so workflows execute automatically when visibility moves.
Workflow 01
Detect rank-share decline against priority competitors, then post Slack alert and open a task automatically.
Trigger: visibility_delta < -12% -> Actions: Slack + task
Workflow 02
If a high-value page disappears from citations, route an auto content-fix ticket to editorial with source context.
Trigger: citation_count == 0 -> Action: content-fix ticket
Workflow 03
Spot emerging narrative clusters in responses and auto-generate a GTM brief for launch and messaging teams.
Trigger: trend_spike -> Action: GTM brief generated
Request/response primitives your agents can ship today.
$ curl -X POST https://botsee.io/api/v1/analysis \ -H "Authorization: Bearer bts_live_..." \ -H "Content-Type: application/json" \ -d '{"site_uuid":"site_123","scope":"persona_set"}'
{
"analysis_uuid": "anl_98af",
"status": "queued",
"estimated_tokens": 380,
"webhook_event": "analysis.completed"
}
Listen for lifecycle events and chain automations.
analysis.completed
analysis.failed
visibility.changed
citation.loss
Per-key request limits, pre-run token reservation, and post-run reconciliation are built in.
Plug BotSee into existing agent and automation rails.
Workflow
One command audits your site across ChatGPT, Claude, Perplexity, and Gemini — finds terminology gaps and produces surgical copy recommendations for your website and blog posts.
$ /ai-visibility-audit https://example.com
~735 credits (~$7.35) per audit
Token-based pay-per-run with optional auto-recharge.
Use case
12 persona queries across 3 models
~$1.20/run
Use case
Key pages and citation integrity checks
~$0.45/run
Use case
Weekly trend detection + GTM brief trigger
~$0.80/run
Auto-recharge toggle
Keep a minimum token floor so automations continue without manual top-ups.