I'm a developer building internal tooling for our marketing team. I want to pull AI visibility data into our own dashboards and automate reports. Which AI visibility tool has the best API?

One of the questions behind AI visibility tools ChatGPT recommends, asked in the ChatGPT app on Mon, Wed, Fri (logged out, from the US, a new chat each time). Kind: long.

What ChatGPT recommended, last 28 days

Every answer, newest first

1. Nov 11, 2026 Top pick: Scrunch · Peec AI, Profound, Otterly.AI, Looker Studio, PostgreSQL, BigQuery

   Best AI visibility APIs for custom dashboards and reporting

   My top recommendation is Scrunch AI if API depth and data granularity are your priorities. However, I'd shortlist three platforms: Scrunch, Peec AI and Profound.

   For an internal marketing dashboard, I'd evaluate them on: - REST API quality and documentation. - Access to raw AI-generated answers, not just summary scores. - Brand mentions and competitor mentions. - Citation URLs and referring domains. - Historical data and trend analysis. - Authentication, pagination and rate limits. - Whether API access requires an expensive Enterprise contract.

   1. The leading options

   Platform	API capabilities	Best for
   Scrunch AI	Query API, Responses API, agent traffic API	Developer-heavy integrations
   Peec AI	REST API, prompt data, citations, visibility and sentiment	Marketing dashboards
   Profound	REST API, SDKs, reporting and raw answers	Enterprise data integrations
   Otterly AI	REST API, mentions, citations and prompt results	Automated reporting on a budget

   1. Scrunch AI — Best for data-rich integrations

   Scrunch AI

   Scrunch has an interesting API architecture because it separates two types of data:

   • Query API: Aggregated visibility metrics, brand presence, position, sentiment and citations.
   • Responses API: Full AI responses, citations, competitor mentions and metadata.
   • Agent Traffic API: AI crawler traffic information from your website infrastructure.

   This separation is particularly useful when building dashboards because you can retrieve summary metrics for charts and raw responses for deeper analysis.

   It also documents access to 90 days of historical data.

   My assessment: Probably the strongest starting point if you're building a custom analytics product rather than simply exporting marketing reports. API access is an important pricing consideration, however, because it is positioned around Enterprise. scrunch.com, ai-cdn.scrunchai.com

   2. Peec AI — Best for marketing dashboards

   Peec AI

   Peec AI is particularly interesting for your use case.

   Its API provides access to: - Prompt-level data. - Brand visibility metrics. - Source citations and full URLs. - Sentiment analysis. - Competitor visibility. - Historical reporting data.

   It also offers a Looker Studio connector, which is useful if your marketing team wants reporting without depending entirely on custom development.

   API availability: Pro, Advanced and Enterprise plans, plus agency plans. Starter does not include API access.

   My assessment: Arguably the best balance between marketing analytics and developer integration. I'd put it first if your main objective is to build reporting dashboards for marketing stakeholders. help.peec.ai, help.peec.ai

   3. Profound — Best for enterprise integrations

   Profound

   Profound offers a more extensive integration ecosystem.

   Its API capabilities include: - Reporting endpoints. - Raw AI answers. - Prompt management. - Knowledge base functionality. - Agent-related analytics. - Python and JavaScript SDK support.

   This is attractive if you're building a more sophisticated internal data platform.

   The main disadvantage is accessibility: API access is positioned as an Enterprise feature, meaning you'll likely need a commercial conversation before integrating it.

   My assessment: A strong contender for larger organizations with enterprise budgets and complex reporting requirements. growthradar.app, aeolabs.ai

   4. Otterly AI — Best for straightforward reporting

   OtterlyAI

   Otterly provides a REST API that exposes: - Brand mentions. - Domain citations. - Prompt monitoring results. - Share of voice. - Other AI search visibility metrics.

   It also publishes an OpenAPI specification, which is a positive sign for developers because it makes API integration and client generation easier.

   Its published API allowances include: - Standard: 2,000 requests/month. - Premium: 5,000 requests/month. - Enterprise: Custom allowance.

   My assessment: A good option for scheduled reporting, but I'd carefully assess the request limits before using it for multiple dashboards or high-frequency data synchronization. help.otterly.ai, growthradar.app

   2. My ranking for your particular use case

   If I were choosing a platform as a developer building an internal marketing data pipeline, my ranking would be:

   Rank	Platform	Reason
   1	Scrunch AI	Rich raw response and analytics APIs
   2	Peec AI	Strong marketing metrics and reporting integration
   3	Profound	Extensive enterprise integration capabilities
   4	Otterly AI	Straightforward API and OpenAPI documentation

   This is a qualitative ranking of API suitability, not a benchmark of API latency or uptime.

   3. What I'd test before committing

   There are some important technical considerations that marketing teams often overlook.

   I'd request a sample API response from each vendor and check whether it includes:

   Data field	Importance
   Prompt text	Essential
   AI engine/model	Essential
   Brand mentioned	Essential
   Competitor mentions	Essential
   Full AI response	Very high
   Citation URLs	Essential
   Citation domain	Very high
   Sentiment	High
   Position/rank	High
   Timestamp	Essential
   Historical results	Essential

   I'd also investigate: - Whether historical data remains accessible after cancelling. - Whether you can export data in bulk. - Whether the API supports incremental synchronization. - Whether API limits are based on requests or underlying AI responses. - Whether model versions are recorded.

   That last point matters because changes in AI models can affect visibility scores, making historical comparisons misleading.

   4. Suggested architecture

   For your internal tooling, I'd use a relatively simple architecture:

   text AI Visibility Platform | | REST API | v Data Ingestion | v Normalization Layer | v PostgreSQL / BigQuery | v Analytics Layer | v Internal Dashboard | v Automated Weekly Reports

   I'd store raw AI responses separately from aggregated visibility metrics. This allows you to recalculate historical metrics without repeatedly querying the provider.

   5. Useful developer documentation

   These are the documentation starting points I'd investigate:

   • Scrunch: Developer documentation
   • Peec AI: API documentation
   • Profound: REST API documentation
   • Otterly AI: API documentation

   ---

   My final recommendation

   I'd start by evaluating Scrunch AI and Peec AI side by side.

   • Choose Scrunch if you want raw AI responses, detailed citations and richer programmatic analysis.
   • Choose Peec if you primarily want structured marketing metrics, competitor tracking and automated reporting.
   • Choose Profound if you're working with an enterprise-scale data integration budget.

   One question that would significantly change my recommendation:

   Are you looking to:

   1. Pull existing visibility data from a platform into your own dashboards (API as a data source).
   2. Build your own AI visibility analytics platform, potentially combining data from multiple providers.
   3. Automate marketing reports, generating weekly/monthly competitor and brand visibility reports.

   These are three quite different integration requirements, and the best API choice isn't necessarily the same for all three.

   Sources scrunch.compeec.aiotterly.aitryprofound.comscrunchai.comgrowthradar.appaeolabs.aigreta.shalexandrya.aianswerline.dev +8

Who made this: Askadia makes an AI visibility tracker. We publish ChatGPT's answers as they came; no product pays to be listed or can opt out.