Best AI Visibility Tools With CSV Export + API Access (2026 Guide)

Peec AI, Otterly and SE Ranking put API access on plans you can buy without a sales call, while Profound and Promptmonitor keep theirs on Enterprise. A CSV button proves little. Only a row-level file with prompt, engine, timestamp and citation columns can feed a warehouse, so ask for a sample before you pay.

This holds for teams that need the data in a warehouse or BI tool. A team that only reads dashboards can ignore the API tier. Plans and API tiers change often, so each fact here links to the vendor page it came from, and you should confirm your tier in writing before you pay.

• Best for teams that want CSV + an enterprise API: Peec AI (CSV + API docs; API is beta/enterprise).
• Best for enterprise-grade data + CSV export + API/SDKs: Profound (CSV export for Answer Engine Insights + API docs/SDKs).
• Best for organizations already running SEO programs who want AI search reporting + export + “data API” story: Conductor AI Search Performance (exports + data/API positioning).
• Best budget-friendly option with explicit CSV export: Promptmonitor (pricing includes “Export to CSV”; changelog notes CSV export features).
• Best for teams that want AI visibility tracking inside a broader SEO platform: SE Ranking (AI visibility reporting plus traditional SEO workflows, with export/reporting options that fit a CSV export-focused tool comparison).
• Best for teams that build their own AI visibility reporting from raw data: cloro (an API for the AI answers themselves, on every plan).

Best AI Visibility Tools with CSV Export + API Access (Quick Comparison)

The 3 export layers: UI export, scheduled export, API

1. UI export (manual CSV/XLSX download). Good for ad-hoc analysis, quick audits, and sharing snapshots. Tools like Conductor document UI export to XLSX in their product UI.
2. Scheduled export (automation without coding). Good for predictable weekly stakeholder reporting. Some tools emphasize email reports and export convenience (Promptmonitor’s plans list weekly email reports plus CSV export).
3. API access (programmatic). This is what technical buyers and RevOps want: authenticate, pull raw data, transform, and load it into your warehouse/BI. Peec’s docs describe a customer API (beta, enterprise-limited). Profound provides API docs and SDKs (Python/TypeScript).

A simple decision tree

Step 1: Do you need programmatic automation (warehouse/BI/alerts)?

• Yes → prioritize API-first options (or at least documented APIs), like Peec’s API (enterprise beta) or Profound’s API/SDKs.
• No → CSV/XLSX export may be enough (Promptmonitor CSV export, Conductor XLSX export).

Step 2: Who is the primary buyer/user?

• RevOps / Analytics: wants raw tables + stable IDs + API keys (often owned under business functions).
• SEO / Content: wants prompts, topics, citations, and action loops.
• Leadership: wants a clean weekly scorecard plus “what changed?” explanation.

Step 3: What’s your operating model?

• In-house teams: care about governance, reliability, and integration.
• Agencies: care about exporting, client-ready dashboards, and multi-project structure, especially when working with a SaaS SEO agency model.

1. Peec AI

Peec positions itself as AI search analytics for marketing teams and highlights both CSV exports and an API integration path for tracking brand visibility in AI search.

What it does

Peec AI monitors how your brand appears across AI platforms and provides reporting features like exports and connectors (e.g., Looker Studio community connector), plus an API mention on its site.

Why teams use it

Because it can move beyond “a visibility dashboard” into data you can reuse, exported CSV for analysis and a documented customer API for programmatic workflows (with plan limitations).

What it’s good for

• Building a weekly/monthly reporting pipeline (marketing + leadership)
• Joining AI visibility metrics with web analytics and pipeline data
• Creating custom dashboards in BI tools using exported or pulled data

When it’s a good fit

• You have an analytics function (RevOps, BI, data analyst) that needs raw tables
• You want API-driven automation (alerts, ETL jobs, warehouse integration)
• You can live with “API is beta / enterprise-limited” if that matches your org size

When it’s not a good fit

• You need guaranteed API access on a low-budget plan (verify plan eligibility first)
• You don’t have anyone to operationalize exports into dashboards/alerts (you might be better with a simpler “dashboard-only” workflow)

How to use it

1. Start with 25–50 prompts: branded + category + competitor + “best” queries, then refine using structuring AI-era AEO content principles.
2. Tag prompts by intent (buying vs research) and funnel stage
3. Export weekly CSV (or pull via API if available to you)
4. Build a Looker/Power BI page with: visibility trend, top gaining/losing prompts, top cited domains, competitor SOV
5. Trigger an alert if top prompts drop for 2 consecutive runs

Key capabilities

• CSV exports emphasized on the product site
• API documentation exists; docs describe API as beta and limited to Enterprise customers

Pricing

Peec AI’s pricing starts at $95/month, and its Enterprise plan is custom-priced.

Free tier?

Peec AI doesn’t offer a free tier, but it does offer a free trial (“Start for free”).

Downsides / limitations

• API is described as beta and limited to Enterprise customers (so don’t assume it’s included).

• Export and API: CSV export is on every plan, and the API starts on Pro.

2. Profound

Profound is a GEO/AI visibility platform that explicitly states you can export raw data to CSV and also provides API documentation and SDKs.

What it does

Profound tracks brand visibility in AI-generated answers and includes a feature set around “Answer Engine Insights,” with visibility measurement and citations.

Why teams use it

Because it’s built for programs that need:

• consistent monitoring across multiple AI experiences,
• exportable raw data, and
• an integration surface (API/SDK) to bring visibility metrics into internal systems.

What it’s good for

• Enterprise-scale AI visibility programs (multiple business lines, markets, teams)
• Analysts who want to model AI visibility changes over time
• Joining AI visibility with content performance, PR, and competitive intelligence

When it’s a good fit

• You need CSV exports for raw analysis (Profound states you can export raw data from Answer Engine Insights to CSV).
• You need an API/SDK approach for integration (Profound docs include REST API intro + SDKs).
• You run governance-heavy workflows (security, approvals, multi-team alignment)

When it’s not a good fit

• You’re early-stage and only need lightweight exports
• You don’t plan to operationalize the data beyond the dashboard (you may not use the platform’s depth)

How to use it

1. Build an entity map: brand + competitors + product categories + “money prompts” using an LLM brand visibility audit approach.
2. Track prompts by topic clusters (e.g., “best {category} software”, “{category} pricing”, “{category} alternatives”)
3. Export raw CSV weekly for QA and trend analysis, and validate coverage with a B2B SaaS content audit checklist.
4. Use API for:
   • loading prompt-run rows into your warehouse
   • enriching with CRM and pipeline data
   • powering internal alerts (drop in “recommendation rate” for high-intent prompts)

Key capabilities

• CSV export: Profound’s Answer Engine Insights page says raw data can be exported into CSV.
• API + SDKs: Profound provides API docs and SDKs for Python and JS/TS.
• GEO guide content also references Profound's API and CSV exports in workflows.

Pricing

Profound’s pricing starts at $99 per month.

Free tier?

Profound doesn’t offer a free tier, but it does offer a demo.

Downsides / limitations

• Enterprise orientation may mean heavier onboarding and higher cost (verify with vendor)

• Export and API: The Trial includes no export or API, while Enterprise lists CSV, JSON and API.

3. Conductor

Conductor positions AI Search Performance as a way to track visibility across AI search experiences and provides export guidance (XLSX export) plus public “API vs scraping” thought leadership referencing a data API concept.

What it does

Conductor’s AI Search Performance pages describe tracking AI visibility and insights across AI experiences (e.g., ChatGPT, Perplexity, Google AI experiences).

Why teams use it

• It can fit into existing SEO/content workflows (especially if Conductor is already your platform)
• It supports exporting tracked topics/prompts via XLSX from the UI per Conductor support documentation
• Conductor emphasizes an “API-first” / data integrity narrative in its academy content

What it’s good for

• SEO orgs that want AI visibility reporting connected to broader organic performance
• Topic-level AI visibility programs (vs one-off prompt experiments)
• Teams that need easy exports for stakeholder reporting

When it’s a good fit

• You already use Conductor and want AI visibility integrated with your workflows
• XLSX export is sufficient for your initial reporting needs
• You want an “enter data” story and vendor support around how the data is collected

When it’s not a good fit

• You want a lightweight, low-cost tool specifically for prompt runs
• You need a clearly documented public API surface for your own ETL immediately (validate your specific Conductor plan and available APIs)

How to use it

1. Define topics and prompts that match revenue-driving queries
2. Export topic/prompt tables (XLSX) into your reporting system weekly/monthly
3. Normalize exports into a consistent schema (topic_id, prompt_id, engine, date, visibility metric) using a programmatic SEO approach.
4. Use exports to:
   • show topic-level share of voice
   • prioritize content updates where AI citations are drifting away from you
   • brief content and PR teams on “what sources AI is citing”

Key capabilities

• UI export to XLSX for tracked topics and prompts
• Conductor academy content discusses API vs scraping and references Conductor’s data API framing

Pricing

Conductor’s pricing is not publicly listed; it’s value-based and tied to a usage model of AI Response Credits.

Free tier?

Conductor doesn’t offer a free tier, but it does offer a 3-week free trial.

Downsides / limitations

• Export is XLSX (fine), but you still need an internal pipeline to operationalize it
• API details depend on plan and may not be fully public, verify in sales/security review

• Prompts tab export: Conductor's AI search FAQ says you can download the table and responses, which adds AI Response and fan-out columns.

4. Promptmonitor

Promptmonitor focuses on tracking visibility across AI platforms and is explicit about CSV export in its plan features; its changelog also references export improvements.

What it does

PromptMonitor tracks brand visibility across AI platforms and provides monitoring and optimization features.

Why teams use it

• It’s approachable for SMBs and startups
• It includes “Export to CSV” in plan features (useful if you want to build your own reporting)

What it’s good for

• Quick setup prompt monitoring
• Exporting prompt/source data to CSV for your own analysis
• Lightweight, “get moving fast” AI visibility programs

When it’s a good fit

• You need CSV exports but don’t necessarily need a full API
• You want to validate whether AI visibility tracking is valuable before upgrading into a heavier enterprise platform

When it’s not a good fit

• Your workflow requires guaranteed programmatic API pulls into a warehouse (not clearly documented publicly, verify)

How to use it

1. Start with 25 prompts that map to your top product category + competitor comparisons
2. Export CSV weekly
3. In Sheets/BI, compute:
   • presence rate per prompt
   • top citation domains (if exported)
   • “prompts with largest visibility drop” week over week
4. Feed those outputs into an editorial backlog: refresh pages, add comparisons, improve “citable” assets

Key capabilities

• “Export to CSV” appears in pricing/plan feature lists
• Changelog references exporting prompt sources to CSV

Pricing

Promptmonitor has a $0/month Agency Plan, and its paid plans start at $39/month.

Free tier?

Promptmonitor offers a free tier ($0/month Agency Plan) and a 7-day free trial for paid plans.

Downsides / limitations

• API access is not clearly documented in the public sources above, treat it as “unknown” until confirmed in sales/docs.

• Export and API: Promptmonitor's pricing page puts API access and SSO on Enterprise only and does not list CSV export.

5. SE Ranking

SE Ranking is an SEO and GEO platform that treats AI visibility as a part of a broader ecosystem. It connects signals such as search performance, traffic, LLM presence, and social analytics, and helps you identify connections among them to better understand the brand’s digital footprint.

What it does

SE Ranking monitors brand mentions, citations, and competitor presence in AI answers, with prompt-level data, placement tracking, historical trends, and citation source identification. Its AI Search API exposes the same visibility data programmatically for integration into external systems.

Why teams use it

Because AI visibility that lives in a silo is hard to analyze and even harder to connect to outcomes. SE Ranking gives teams a structured path to pull mention and citation data alongside organic ranks, traffic, and social signals, so reporting reflects what’s actually happening across channels, not just in one.

What it's good for

• Building BI dashboards that combine AI mention frequency, citation sources, and organic rankings in one model
• Tracking competitor AI presence across AI platforms and spotting gaps
• Automating SEO and GEO workflows across multiple client projects

When it's a good fit

• You need daily AI visibility data (not just monthly snapshots) at the project and prompt level
• Your BI setup uses Data Studio. SE Ranking has pre-built connectors that support data blending
• Your team uses n8n or Make.com for automation. Both have native SE Ranking connectors covering AI Search

When it's not a good fit

• You only need dashboard-level monitoring before committing to a more comprehensive stack
• You prefer first-party SDKs; SE Ranking’s integration path is REST + Postman collection, no SDK

How to use it

1. Set up AI Result Tracker projects; Start with tracking 20–40 prompts, distributed across journey stages (awareness, consideration, brand evaluation)
2. Use AI Competitor Research to benchmark competitor AI presence by platform and identify citation gaps
3. Export data in CSV or pull via the AI Search API: brand mentions, citation URLs, position data, and prompt-level insights
4. Join with organic rank data from SE Ranking and traffic data from GA4 integrations to build a combined view
5. Use Data Studio connector for stakeholder dashboards without maintaining a custom pipeline or native n8n/Make.com connectors to build custom scenarios or alerts

Key capabilities

• Comprehensive SEO and GEO suite with GA4 integrations and access to social analytics via Planable
• CSV data export and API access across projects and tools
• MCP server to query SE Ranking data from AI assistants without manual exports
• Integrations with Data Studio, n8n, Make.com, and more

Pricing

API is included in every plan starting from $129/month. Minimum deposit for pay-as-you-go is $50, credits don’t expire.

Free tier?

No free tier, but a 14-day free trial includes 100K API credits and full endpoint access.

Downsides / limitations

• Designed as an integrated SEO + AI search suite. Teams wanting a minimal standalone AI visibility tool without the broader platform may find the scope larger than needed

• API limits: SE Ranking's AI Search API page lists 10 requests per second on research endpoints and 5 on prompt-tracking endpoints, with JSON output.

6. cloro

cloro is an API that returns the answers from ChatGPT, Perplexity, Gemini, Copilot, Google AI Mode and Google AI Overviews as structured JSON, with the answer text, the cited sources and the position of each link. There is no dashboard to log into — you send your own prompts and own both the data and the reporting layer on top of it.

What it does

cloro runs a prompt against an AI engine and hands back the raw result as JSON. Each response includes the answer text (plain or markdown) and a sources array, where every citation carries its position, URL, label and description. Teams aggregate those responses themselves into mention rate, share of voice and competitive position.

Why teams use it

• The underlying data is theirs, not a vendor’s chart. Metrics can be defined however the business already defines them.
• AI visibility can sit in the same warehouse as organic, paid and pipeline data, so it joins to revenue instead of living in a separate tool.
• Engineering controls the prompt set, the countries and the schedule, rather than working around a fixed UI.

What it’s good for

• Building an internal AI visibility dashboard in Looker Studio, Power BI or Tableau.
• Feeding AI answer data into BigQuery or Snowflake alongside existing marketing tables.
• Tracking a large or frequently changing prompt set without paying per-seat for a platform.
• Agencies that want one data source behind client-facing reporting they already own.

When it’s a good fit

You have a data or analytics function that can call an API, store the results and build the reporting. The value is in owning the pipeline.

When it’s not a good fit

You want to open a tool and see your AI visibility this afternoon. cloro ships no dashboard, no alerts and no prebuilt reports — that work is yours.

How to use it

1. Sign up and take the API key from the dashboard; the free plan starts with 500 credits a month.
2. Build your prompt list — the questions where your brand should appear, plus the competitor and category queries you want to track.
3. Call the monitor endpoint with the prompt and a country code, either synchronously or through the async endpoint with a webhook for results.
4. Store each response, then parse the sources array to flag your own domain, competitor domains and the position of every citation.
5. Run it on your own schedule with cron, Airflow or Temporal, and point your BI tool at the stored table.

Key capabilities

• Coverage of ChatGPT, Perplexity, Gemini, Copilot, Google AI Mode and Google AI Overviews from one API.
• Per-request country targeting, so answers can be tracked market by market.
• Structured citations with position, URL, label and description on every source.
• Official Python and TypeScript SDKs, plus sync and async (webhook) delivery.

Pricing

The free plan includes 500 credits a month. Paid plans start at $30 a month for 37,500 credits, with Hobby at $100 for 250,000 credits and higher tiers scaling to enterprise volumes. Credits are deducted only on a successful extraction, so failed requests are not billed.

Free tier?

Yes. Every account gets 500 credits a month, which covers roughly 20 prompts run across all the monitor engines — enough to test the response shape before committing.

Downsides / limitations

• No dashboard, no scorecards and no alerting: every metric and chart is something you build.
• No built-in scheduling, so recurring tracking needs your own orchestrator.
• Credit spend scales with prompts × engines × frequency, so a wide prompt set tracked daily needs cost modelling up front.

• Output: cloro's pricing page lists no export feature, since output is API JSON, and states a rate limit of 1,000 requests per second.

What CSV Export And API Access Mean For AI Visibility Data

Most teams buy an AI visibility tool for the insights, then hit a wall when someone asks for the numbers in the warehouse. The word "export" covers three different things, and which one you get decides what you can build.

• UI export: A manual download from the product, useful for audits and one-off snapshots.
• Scheduled export: A file or email sent on a timer, useful for weekly stakeholder reporting without code.
• API access: Programmatic pulls that load rows into a warehouse or BI tool, which makes it the only route to a pipeline you own.

Whichever layer you use, the file is only as good as its columns. If an export carries the six field groups below, you can build almost any reporting layer on top of it.

The citation columns are the ones summary exports drop first. If you care about which pages the engines cite, our guide to URL-level citation attribution shows what that analysis needs. Competitor fields do the same job for benchmarking, and the guide to competitor benchmarking tools covers that side. A file with no timestamps or citations cannot show drift, and you cannot build a governance loop on it.

Which AI Visibility Tools Offer True Raw CSV Export, Not Summaries?

A raw export has one row per prompt run. Each row carries a prompt ID, the engine, a timestamp, the mention status, the citation URLs and any competitor mentions. A summary export has none of that. It is a chart saved as a file, with no per-run data, no timestamps and no citations.

The test is mechanical. If the file has no timestamp, engine or citation column, it is a summary. The row count gives it away too. It should equal prompts times days times engines, or run higher if citations are normalized into one row each.

Watch for these red flags:

• Dashboard-level only: The export works on a whole report, not on each prompt run.
• No run IDs or timestamps: You cannot measure drift or volatility.
• No citations: Source URLs appear only in the interface.
• No prompt-level export: You get one overall visibility score and nothing underneath it.

The fastest vendor test is to ask for a sample before you pay. Ask for 10 prompts across 7 days on 2 engines, with timestamps and citations included. If each run is one row, that file should hold 140 rows. A vendor that cannot send it quickly is selling a dashboard, not a dataset.

Vendor documentation is thin on this. Conductor's Prompts tab lets you download the table and responses, with AI Response and fan-out columns, but the FAQ gives no file format. Keyword.com's support article lists three routes, UI exports as CSV or Google Sheets, an API and a Looker Studio connector, and it describes no per-run fields. Surfer's announcement limits its AI Tracker API and Looker Studio integration to Enterprise plans from 23 January 2026, and it does not say whether the data is per run or aggregated.

Raw citation rows are also what citation gap analysis runs on, because a gap needs a source URL for every run.

Is The API Included On The Plan Or Enterprise-Only?

It depends on the vendor, and the answer sits on the pricing page, not the homepage. This is where each tool puts its API.

Peec AI's pricing page shows the API on Pro, Advanced and Enterprise but not on Starter. Otterly.AI's pricing page lists 2,000 API requests a month on Standard and 5,000 on Premium. SE Ranking says its AI Search API is included in every plan, with 10 requests per second on research endpoints and 5 on prompt-tracking endpoints. Profound's pricing page puts CSV, JSON and API on Enterprise, and Promptmonitor's pricing page puts API access on Enterprise with SSO. Surfer's announcement limits the AI Tracker API and Looker Studio integration to Enterprise plans from 23 January 2026. cloro's pricing page has no export feature, only an API that returns JSON and charges credits on every request.

The rule is simple. If the API sits on a plan you can buy online, you can test it this week. If it sits on a contract, you cannot, so get the tier in writing.

When the API is Enterprise-only, plan for a contract and security review before you pull a single row. Expect usage quotas, and ask which endpoints the key opens, because raw prompt runs and summary reports may not sit behind the same access.

Ask these five questions before you sign:

1. Which plan includes API access, and can you confirm it in writing?
2. Which endpoints are included, and do they return raw prompt runs and citations?
3. What are the rate limits?
4. Do you support backfills of historical data?
5. What happens to my data and my access if I downgrade?

How To Choose An AI Visibility Tool If You Need To Pipe Data Into Your Stack

Pick by the pipe you need, not by the feature list. Four if-then lines cover most buyers.

1. If you need a warehouse: Choose a vendor with a documented API on a plan you can buy, such as Peec AI from Pro or SE Ranking on any plan, then confirm the endpoints return one row per prompt run.
2. If you only need BI dashboards: A scheduled or UI export is enough, as long as the file carries timestamps, engine and citation columns.
3. If you only need alerts: A light API pull or a built-in alert does the job, and you can skip the warehouse.
4. If you want to build from raw answers: cloro's pricing page lists an API that returns JSON and no export feature, so the reporting layer is yours to build.

Prompt volume drives credit spend on credit-based APIs, so read our guide to large-scale prompt monitoring before you size a plan.

Ask these seven questions in every demo:

1. Can I export raw prompt runs with timestamps and engine metadata?
2. Do exports include citations and source URLs, not just mention counts?
3. Is there a documented API, and what is the rate limit?
4. Is API access on my plan, or Enterprise only?
5. Can I tag prompts and filter exports by tag, topic and location?
6. What happens to my data when an engine changes its behavior?
7. Can I export at project and prompt level, not just aggregate dashboards?

Then take the one step that settles it. Request a sample raw export and confirm the API tier in writing. Once the data is flowing, our generative engine optimization work is what turns it into content decisions.

Integration Playbook: Getting AI Visibility Data Into BI And Alerts

A tool is only as useful as the decision its data drives. The pipeline below has four steps, and each one hangs on a single field.

1. Pull: Call the API, or schedule the export, for every tracked prompt and engine. The field that keeps pulls apart is run_id.
2. Land: Write each pull into a warehouse table or a sheet as new rows, and never overwrite the last pull. The field that matters is timestamp, because it is what shows drift.
3. Join: Line up the AI rows against organic rank and traffic by prompt or topic. The field is prompt_id mapped to a topic or a page.
4. Alert: Send a Slack message or open a ticket when a high-intent prompt stops mentioning you for two runs in a row. The field is mention_present.

The join is the step most teams skip. Semrush covers the traditional half of that join, keyword rank tracking and organic traffic reports, which you can line up against the exported AI rows to see where a Google ranking and an AI mention agree or split.

Once the rows sit in one table, the dashboard is the easy part. Our guide to Looker Studio integrations covers which AI visibility tools connect there. Share of answer and share of voice come straight out of the same rows, and the guide on share of answer and share of voice shows how to read them. For the alert step, the guide to citation loss alerts covers tools built for it.

If you would rather not build and maintain this yourself, our ongoing GEO and SEO reporting runs it alongside the content work.

API-First Collection Versus UI-Based Monitoring: Which Is More Accurate?

No. An answer pulled through an API can differ from the answer a user sees in the product, so an API feed does not prove the data is right.

There are two ways tools collect answers. API-first collection requests answers through an engine's programming interface. UI-based monitoring automates the product's own interface and records what appears. Either can drift from what your buyers see, because location, personalization and context can change the answer.

The only accuracy question that matters is whether the tracked answer matches what a user sees. Check it in the demo with three steps:

1. Sample: Pick ten prompts the tool tracks for you.
2. Re-run: Run each one by hand in the live product, with the same location and language.
3. Compare: Check the mention and the cited URLs against the rows the tool stored.

A mismatch is a question for the vendor. For more on checking tracked answers against the product, see our guide to ChatGPT answer monitoring.

Final Next Step

Before you pay for anything, ask the vendor for a sample raw export and get the API tier confirmed in writing. A file with timestamps, engine and citation columns is a dataset, and anything less is a dashboard with a download button.