Are there APIs for tracking AI search visibility? Need to build internal dashboards

Let me map the current landscape:

AI Platform APIs (NOT for visibility tracking):

These APIs let you USE AI, not track your VISIBILITY in AI.

Dedicated Visibility Tracking:

Am I Cited:

• Tracks citations across platforms
• Has dashboard and reporting
• API access available (check with them)
• Best current option for integrated data

Custom solutions: Some companies build their own by:

• Programmatically querying AI platforms
• Parsing responses for citations
• Storing and trending data
• Expensive to build and maintain

The gap you’ve identified: This market is early. There’s no “Ahrefs of AI visibility” yet with full API ecosystem. It’s developing rapidly.

My recommendation: Start with Am I Cited for data. Check if they offer API access for your dashboard needs. Building from scratch is rarely cost-effective at this stage.

I use Am I Cited. Here’s what I know about their data access:

What the platform provides:

• Web dashboard with visibility metrics
• Citation tracking across ChatGPT, Perplexity, Claude
• Competitive analysis
• Historical trending
• Export capabilities

Data you can get:

• Citation rate by platform
• Position in AI answers
• Share of voice vs competitors
• Query categories triggering citations
• Trend data over time

For dashboard integration: Reach out to them directly about API access. They’ve been responsive to custom needs in my experience.

What I export for our dashboards: Weekly CSV export of key metrics. Not ideal but works for now.

The workflow: Am I Cited → Weekly export → Google Sheets → Looker Studio

Manual but gets the data where we need it.

If you’re building any solution, here’s the data model to think about:

Key entities:

Brand/Domain
├── AI Platforms
│   ├── ChatGPT
│   ├── Perplexity
│   ├── Claude
│   └── Google AI Overview
├── Queries
│   ├── Query text
│   ├── Category
│   └── Frequency
├── Citations
│   ├── Timestamp
│   ├── Platform
│   ├── Query
│   ├── Position in response
│   ├── Citation type (link, mention, quote)
│   └── Sentiment
└── Competitors
    └── Same structure

Metrics to derive:

• Citation rate: Citations / Queries tested
• Share of voice: Your citations / Total citations
• Position score: Weighted by position (1st > 3rd)
• Platform breakdown: % by platform
• Trend: Change over time

Data freshness:

• Real-time isn’t practical (API costs, rate limits)
• Daily is achievable for key queries
• Weekly is typical for comprehensive tracking

If building custom: Start with 50-100 key queries. That’s enough to establish patterns without breaking the bank on API costs.

Some alternative approaches to pure API:

1. Browser automation

• Use Playwright/Puppeteer to query AI platforms
• Parse rendered responses
• Cheaper than API but fragile
• Violates ToS for most platforms

2. Webhook integration

• If Am I Cited offers webhooks, set up event-driven updates
• Push data to your warehouse when visibility changes
• More efficient than polling

3. Email reports to data pipeline

• Many tools offer email reports
• Parse emails programmatically
• Route data to your systems
• Hacky but works

4. Zapier/Make integration

• Check if visibility tools integrate
• Connect to your dashboard tools
• No-code option

5. Manual + automation hybrid

• Weekly manual spot-checks for calibration
• Automated high-level metrics
• Combine for accuracy

Reality: The “perfect” API integration doesn’t exist yet. Most teams are cobbling together solutions. Pick the least-painful option that gets you directionally correct data.

For your internal dashboard, here’s what I’d include:

Overview section:

• Overall AI visibility score
• Week-over-week change
• Platform breakdown pie chart
• Trend line (last 90 days)

Detailed metrics:

• Citation rate by platform
• Top queries where you appear
• Top queries where you DON’T appear (opportunity)
• Share of voice vs top 3 competitors

Content performance:

• Which URLs get cited most
• New citations this week
• Lost citations this week

Comparison view:

• AI visibility vs Google rankings
• AI visibility vs organic traffic
• Correlation analysis

Alerts:

• Significant visibility change (±20%)
• Competitor visibility spike
• New query category citations

Data source strategy: For most of this, you need one of:

• Am I Cited API/export
• Custom tracking solution
• Manual data collection

Start with the highest-value metrics, don’t try to build everything at once.

Practical suggestion: Start simple.

Phase 1: Manual baseline

• Pick 20 key queries
• Test monthly in ChatGPT, Perplexity
• Track in spreadsheet
• Establish baseline

Phase 2: Tool adoption

• Get Am I Cited for automated tracking
• Export data weekly
• Build simple Sheets dashboard

Phase 3: Integration (if needed)

• Contact Am I Cited about API
• Build integration to internal dashboards
• Automate reporting

Why this order: Don’t over-engineer before you know what data matters. Manual baseline helps you understand the patterns. Then automate what’s valuable.

What we learned: We thought we needed real-time AI visibility data. Turns out weekly is fine. The patterns don’t change that fast. Saved us a lot of engineering complexity.

Current state: Am I Cited → Weekly export → Power BI Total automation time: 2 hours/month Good enough for executive reporting.

Thanks everyone. My approach:

Decision: Buy, don’t build (for now)

The custom build sounds painful and expensive. Better to use existing tools until the market matures.

My plan:

Week 1:

• Sign up for Am I Cited
• Establish baseline metrics
• Explore export capabilities

Week 2:

• Contact Am I Cited about API access
• If available: Build integration
• If not: Set up manual export workflow

Week 3:

• Add AI visibility section to our Looker Studio dashboard
• Include: Citation rate, platform breakdown, competitor comparison

Week 4:

• Set up alerting for significant changes
• Train marketing team on new metrics
• Document the workflow

Metrics I’ll prioritize:

1. Overall citation rate
2. Platform breakdown
3. Share of voice vs competitors
4. Top cited URLs
5. Week-over-week trend

What I’m NOT doing:

• Building from scratch
• Real-time tracking (weekly is fine)
• Over-complicating the dashboard

Future consideration: If the market matures and better APIs emerge, we can revisit. For now, practical > perfect.

Thanks for the reality check on build vs. buy!