A client asks whether their brand shows up when buyers query ChatGPT, Perplexity or Google AI Overviews. So do dozens of your other clients. A screenshot per prompt does not scale. Neither does a per-seat dashboard that bills by client and keeps the numbers locked inside someone else’s interface.
Agencies need structured answers with citations, delivered by API into Looker Studio, Google Sheets or an in-house portal. Then they render them in their own branded client reports. Generative engine optimization reporting still needs rankings, keywords and backlinks next to the AI numbers. We compared six providers on platform coverage, citation-level output, integration options, pricing model and fit for multi-client volume.
How We Cut the Shortlist
We started with providers that expose AI answers or AI visibility data programmatically. Anything without documented structured output dropped out. This audience wires its own reporting and has no use for screenshots or a locked interface.
Coverage came next. Which engines does each provider read? Do answers arrive with their cited sources? Does classic SERP or keyword data live in the same account? We read endpoint documentation, output formats, listed integrations and stated pricing models.
User reviews on Trustpilot and G2 filled in the human side. We scanned them for recurring complaints about onboarding, support and reliability. Ratings quoted below are verified public figures only. The rest rests on public information, not private benchmarks.
Raw Feeds Versus Finished Dashboards
Platform coverage
Agencies track client brands across ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews. A provider that reads only one or two engines forces a second vendor into the stack.
Citations over HTML
Parsed answers with source URLs feed a mention report directly. Raw HTML means building and maintaining the parser yourself.
Dashboard versus raw API
An AI visibility dashboard is quick to start, but it fixes the metrics and the branding. Raw API access for LLM mentions takes integration work and returns reporting the agency fully owns.
Cost at client volume
Seat-based and per-client billing climbs with the roster. Usage-based billing follows the prompts and brands you actually monitor.
Classic metrics alongside AI
Rankings, keyword and backlink data in the same account keep one source behind the whole report.
The List
1. DataForSEO
DataForSEO’s AI Optimization API is built from four modules. LLM Mentions tracks how often a brand is named and cited across ChatGPT and Google AI Overviews. LLM Scraper captures ChatGPT and Gemini answers in the form a user sees on screen. LLM Responses runs custom prompts against ChatGPT, Claude, Gemini and Perplexity through a single interface, and AI Keyword Data adds AI search volume with a 12-month trend.
Output is raw and structured, so the agency renders it in its own reports under its own brand. Connectors cover Google Sheets, n8n, Make, Zapier and Airtable, and an MCP server lets Claude and ChatGPT query the same data. As an AI visibility API for SEO agencies, DataForSEO lets one account cover many client brands, billed pay-as-you-go with no monthly subscription, so spend follows prompts and brands monitored rather than client count.
Trustpilot lists DataForSEO at 4.5/5 (62 reviews). A reviewer there, using the API on their own sites, wrote that “the data has been solid so far. Docs are decent too, had it hooked up in an afternoon.”
SERP, keyword and backlink data come from the same account, so AI answers and classic SEO metrics can land in one Google Sheet.
Best suited for: growth managers, SEO software builders, consultants and SEO agencies after an AI visibility API wired into Looker Studio, Sheets or an in-house portal.
2. Sellm
Agencies that want a purpose-built AI visibility product, not a general data platform, tend to start with Sellm. It is aimed at tracking how brands surface in AI-generated answers.
Engine coverage deserves a check against current documentation before a whole client roster moves over. For a lean team reporting on a modest set of prompts per client, the narrow focus keeps setup short. As a mid-tier subscription product, it suits agencies that budget by plan rather than by request.
Best suited for: boutique agencies tracking a modest prompt set per client who prefer a dedicated AI visibility tool.
3. cloro
Structured answers from AI engines, ready to pipe into reports, are the whole pitch at cloro. It is an API for pulling responses from LLM-driven search products, not a dashboard to log into.
That shape fits agencies with a developer or an n8n workflow already running. Prompts go in. Parsed answers come out. The agency decides how citations and brand mentions get scored.
Next to infrastructure vendors the scope is tighter, which many agencies will count as a feature.
Best suited for: developer-led agencies wanting parsed AI answers they can score and chart in their own reporting.
4. MentionsAPI
MentionsAPI is named for the job: brand mentions, delivered by API. It frames the problem as one question: where does a brand get named in AI answers?
For an agency, that maps onto a recurring client report. Mention counts, shifts over time, competing brands named alongside. The agency picks the chart. The API stays out of the way.
Agencies comparing it with broader platforms should check whether rankings, keyword and backlink data need a separate source. Narrow scope, clear job.
Best suited for: agencies wanting a single-purpose feed of AI brand mentions to chart in monthly client reports.
5. Oxylabs
Oxylabs comes from the web data infrastructure world, where proxy networks and scraper APIs are the core product categories. Teams with engineers who already run scraping pipelines will know the territory.
Control is high. So is the amount of assembly. It is an infrastructure-first offer, and any AI visibility reporting is something a team builds on top. That suits agencies with in-house data engineering, while smaller teams may feel the build burden given its premium, subscription-billed positioning.
Best suited for: agencies with in-house data engineers who want scraping-grade control over their own data pipelines.
6. Bright Data
Proxy networks, scraper APIs, a SERP API and ready-made datasets sit under one roof at Bright Data. That breadth appeals to agencies already collecting web data at volume.
Output arrives as raw web data, so parsing and scoring for client reporting fall to the agency. Reporting is a build, not a switch.
G2 shows 4.7/5 from 320 reviews. The scale is built for engineering teams, and agencies without one may find the surface area large.
Best suited for: engineering-heavy agencies already collecting web data at volume who build their own reporting layers.
Matching an API to Your Client Roster
Agencies building their own reporting layer. DataForSEO suits agencies, in-house marketers and solo operators that wire an API into Sheets, Looker Studio or a portal and want AI metrics and classic SEO data from one account. cloro fits developer-led shops that only need parsed AI answers to score themselves.
Focused AI visibility tools. Sellm suits boutique agencies that prefer a dedicated product for AI visibility tracking. MentionsAPI suits teams that want a single-purpose mentions feed for monthly reports.
Infrastructure-scale scraping. Oxylabs and Bright Data suit agencies with data engineers already running pipelines, where client reporting is assembled on top of a web data platform. Bright Data brings the wider product range. Oxylabs offers the same engineering-first route.
| Provider | Best for | Pricing approach |
| DataForSEO | Growth managers, SEO software, consultants, agencies | Mid-range, pay-as-you-go |
| Sellm | Dedicated AI visibility tracking | Mid-range, subscription |
| cloro | Developer-led parsed AI answers | Mid-range, subscription |
| MentionsAPI | Single-purpose brand mentions feed | Mid-range, subscription |
| Oxylabs | Engineering-first scraping pipelines | Premium, subscription |
| Bright Data | Broad scraping stack at volume | Premium, subscription |
Count the prompts, brands and clients you will report on a year from now. Then ask which option still fits your team’s engineering hours and your budget when that number doubles.