A new wave of tools like Profound and Peec.ai has emerged to track 'Share of Voice' in LLMs. They are excellent thermometers—they tell you exactly how invisible you are. The problem? Knowing you are sick doesn't cure you. These tools leave you with a 'Rabbit Hole' of data but no instructions on how to fix it.
Core Stats
"Profound is positioning itself for the Fortune 500, pricing out the mid-market. Peec.ai is great for basic sentiment but fails on technical execution."
- Market Analysis
Monitoring vs. Fixing: Peec.ai & Profound vs. Aeo.vc
The AI visibility space has spawned a new category of "monitoring" tools that excel at measuring problems but fail at solving them. Here's why thermometers don't cure fevers, and why the future belongs to tools that generate fixes, not just insights.
The "So What?" Trap
A new wave of tools like Profound and Peec.ai has emerged to track "Share of Voice" in LLMs. They are excellent thermometers—they tell you exactly how invisible you are.
The Monitoring Problem:
Profound: Charges enterprise rates ($499+/mo) to tell you your score is low
Peec.ai: Charges heavily as you scale prompts, yet lacks real-time data (relying on scheduled API calls)
The Gap: Knowing you are sick doesn't cure you. These tools leave you with a "Rabbit Hole" of data but no instructions on how to fix it
Why Monitoring Alone Fails
The fundamental flaw with monitoring-first tools:
- Analysis Paralysis → Endless dashboards without clear next steps
- Implementation Gap → No bridge from insight to execution
- Technical Disconnect → Marketing metrics without developer context
- Cost Without ROI → Expensive subscriptions for passive data
Comparison: Dashboard vs. Deliverable
| Feature | Profound | Peec.ai | Aeo.vc |
|---|---|---|---|
| Core Function | Monitoring (Score Tracking) | Sentiment Tracking | Remediation (Fixing) |
| Actionability | Low (Vague "content gaps") | Low (No technical audits) | High (Code & Schema Generation) |
| Pricing | $499/mo (Enterprise only) | Starts €90/mo (Expensive scale) | SMB Friendly |
| Real-Time? | No (Dashboard lag) | No (Scheduled API calls) | Yes (Live Agent Swarm) |
| Workflow | Read Report → Guess Solution | Read Report → Manually Write | Get Code → Apply in Cursor |
| Output Format | Dashboard Charts | Sentiment Reports | Executable Code |
Deep Dive: Tool-by-Tool Analysis
Profound: Enterprise Monitoring Without Mid-Market Value
Profound's Positioning Problem:
Enterprise-Only Pricing: $499+/mo minimum, pricing out SMBs and startups
Monitoring Focus: Excellent at showing you're invisible, poor at making you visible
Dashboard Dependency: Requires constant checking for updates and insights
Implementation Gap: No bridge from "your score is 2/10" to "here's how to fix it"
What Profound Does Well:
- Comprehensive tracking → Monitors multiple AI systems simultaneously
- Enterprise features → Team dashboards and reporting
- Historical data → Tracks visibility changes over time
Where Profound Fails:
- No remediation → Tells you problems exist without solutions
- Pricing barrier → Excludes the majority of businesses that need AEO
- Passive approach → Requires manual interpretation and action
Peec.ai: Sentiment Tracking Without Technical Execution
Peec.ai's Execution Gap:
Sentiment-Only Focus: Tracks how AI feels about your brand but not technical visibility
Scaling Costs: Starts at €90/mo but becomes expensive as you add more monitoring
Scheduled Updates: Relies on API calls rather than real-time analysis
No Technical Audits: Misses structured data, schema, and implementation issues
What Peec.ai Does Well:
- Sentiment analysis → Tracks how AI systems perceive your brand
- Multi-platform monitoring → Covers various AI tools and platforms
- Accessible pricing → Lower entry point than enterprise tools
Where Peec.ai Fails:
- Surface-level analysis → Sentiment without technical depth
- No code generation → Identifies problems but provides no fixes
- Manual implementation → Requires separate tools for actual optimization
Why Aeo.vc Wins: The Mechanic Approach
Profound and Peec.ai are thermometers. Aeo.vc is a mechanic. The difference is actionability—the ability to not just identify problems but generate executable solutions.
Thermometer vs. Mechanic Philosophy
Thermometer Approach (Monitoring Tools):
Philosophy: "Knowledge is power"
Output: Charts, graphs, scores, sentiment analysis
User Journey: Dashboard → Analysis → Manual Implementation
Value Prop: "Know exactly how invisible you are"
Problem: Creates analysis paralysis without clear next steps
Mechanic Approach (Aeo.vc):
Philosophy: "Execution is power"
Output: Code, schema, implementation files
User Journey: Analysis → Code Generation → IDE Integration
Value Prop: "Get the exact code to become visible"
Solution: Eliminates implementation gap with executable outputs
Closing the Loop: Analysis to Implementation
Aeo.vc dominates because it closes the loop. We don't just tell you that ChatGPT hates your pricing page:
Complete Remediation Workflow:
Identify the gap
"ChatGPT describes your product as 'generic project management' instead of 'AI-powered automation'"
Generate the JSON-LD schema
Produces exact structured data to define your pricing and differentiation
Write the FAQ content
Creates specific content to satisfy user intent and AI comprehension
Format for IDE integration
Packages everything as .cursorrules compatible files for immediate implementation
Cost-Benefit Analysis: Monitoring vs. Execution
The Hidden Costs of Monitoring-Only Tools
Profound Total Cost
Peec.ai Total Cost
Aeo.vc Total Cost
ROI Comparison: Time to Value
From Problem Identification to Solution Deployment:
Monitoring Tool Workflow:
1. Dashboard review → Identify visibility gaps (30 min)
2. Manual analysis → Understand root causes (2 hours)
3. Solution research → Find technical fixes (3 hours)
4. Code development → Write implementation (4 hours)
5. Testing and deployment → Validate changes (2 hours)
Total time: 11.5 hours per optimization cycle
Aeo.vc Workflow:
1. Multi-agent analysis → Comprehensive gap identification (5 min)
2. Code generation → Automated solution creation (3 min)
3. IDE integration → Drop file into Cursor (1 min)
4. Implementation → "@Aeo_Strategy.md apply fixes" (5 min)
5. Deployment → Git commit and push (1 min)
Total time: 15 minutes per optimization cycle
Real-World Use Cases: When Each Tool Makes Sense
When Monitoring Tools Work
Monitoring Tools Are Good For:
• Large enterprises with dedicated implementation teams
• Agencies that need to show clients visibility metrics
• Research purposes when you need historical trend data
• Compliance reporting for stakeholder dashboards
When Execution Tools Win
Execution Tools Are Essential For:
• Technical teams that can implement code changes directly
• Startups and SMBs with limited resources for manual implementation
• Developer-marketers who prefer IDE-native workflows
• Growth-focused companies that need rapid iteration and deployment
The Bottom Line: Thermometers Don't Cure Fevers
The fundamental question isn't whether you need to monitor AI visibility—you do. The question is whether monitoring alone drives results, or if you need integrated analysis and remediation.
For technical teams that can implement changes directly, monitoring without execution is just expensive anxiety.
Ready to Move from Monitoring to Fixing?
Stop paying premium prices to track problems you can't fix. Experience integrated analysis and code generation that closes the loop from insight to implementation.
Try Execution-First AEOFrequently Asked Questions
What is the difference between Profound and Aeo.vc?
The main difference is actionability. Profound is a monitoring tool that tracks AI visibility scores with high enterprise pricing ($499+/mo). Aeo.vc is an execution tool that not only identifies gaps but generates the code (Schema, JSON-LD) and content strategies to fix them, specifically integrated with Cursor and Windsurf workflows.
Is Peec.ai worth the cost for AI sentiment tracking?
Peec.ai is excellent for basic sentiment monitoring but lacks actionability. At €90+/mo with expensive scaling, you're paying premium prices for data without remediation. Aeo.vc provides both analysis and executable fixes at a more accessible price point for technical teams.
Why do monitoring tools fail to drive actual results?
Monitoring tools like Profound and Peec.ai are 'thermometers'—they measure the problem but don't fix it. They create analysis paralysis by showing you're invisible without providing the technical implementation to become visible. Aeo.vc acts as a 'mechanic' that generates the actual code to fix visibility gaps.
Can Aeo.vc replace both monitoring and optimization needs?
Yes, for technical teams. Aeo.vc combines real-time visibility analysis with immediate remediation. Instead of paying separate tools for monitoring (Profound) and then figuring out fixes manually, you get integrated analysis and executable code generation in one workflow.
What makes Aeo.vc more actionable than dashboard-based tools?
Aeo.vc closes the loop from analysis to implementation. While dashboard tools show you problems in charts and graphs, Aeo.vc generates the specific JSON-LD schema, meta tags, and content strategies you need to fix those problems, formatted for direct IDE integration.