AI Search Visibility Tools: Honest Comparison From a Builder

Originally published on rikuq.com. Republished here for Dev.to's readers.

I built one of these tools (Citare) and tried every other one I could get an account on. Most of the category is converging on the same UI and the same marketing copy, but underneath there's a question that decides accuracy more than anything else — and most buyers don't know to ask it.

The question: Is the tool querying LLMs via their API, or via a real browser session? Almost every tool in this space takes the API path because it's cheaper to build. The answers an API returns are not the answers a real user sees. If you're optimizing for what someone typing into chatgpt.com actually reads, API-based tracking is measuring the wrong thing.

That's the structural difference. Everything else — pricing, dashboards, integrations — is downstream of it.

TL;DR

The two real categories under the marketing

Strip the buzzwords and there are two jobs being done by tools in this space:

1. Audit / measurement — "Where does my brand surface today? Where do my competitors surface? How does that change over time?" Most tools sit here. The output is dashboards, trend charts, citation logs.
2. Optimization / content suggestion — "What should I change to surface more?" Fewer tools claim this credibly. Recommendations usually devolve into "write more content matching keywords X, Y, Z" — basically AEO-flavored content briefs.

You need (1) before (2). Anyone selling you (2) without (1) is selling you a content service in tool clothing.

What to actually look for

In rough order of how much each one will affect the accuracy of your decisions:

1. API vs browser test

Already covered above. This is the headline feature even though almost no tool's marketing leads with it.

When I was researching to build Citare, I noticed nearly every competitor was hitting the LLM APIs directly. Quick math told me why: API is one HTTP call; running a real browser session is an order of magnitude more infrastructure (Playwright/Chromium, session management, cookie handling, anti-bot evasion, etc.). API gives you a number fast and cheap. The number is just wrong.

The one moment that decided Citare's whole architecture: I ran the same prompt through ChatGPT's web interface and through its API back-to-back. Different answers. Different citations. Sometimes the API returned a model the interface doesn't currently route to. If a tool is measuring what the API says about your brand, and you're optimizing based on that, you're optimizing for a phantom audience.

2. Platform coverage

The 5 that matter: ChatGPT, Google AI Overview (AIO), Gemini, Claude, Perplexity. Most tools cover 3-5. Brandlight claims 11+ including Amazon Rufus, Meta's Llama-powered surfaces, and others.

The trap: "coverage" is binary on a feature checklist but in practice it's a quality spectrum. ChatGPT coverage is well-trodden by everyone. AIO is harder because Google personalizes heavily. Perplexity is straightforward. Claude with browsing is volatile because the feature itself changes.

Ask vendors specifically: how often do you refresh per platform per query? If they hedge, refresh frequency is bad.

3. Query volume + refresh cadence

A 50-prompt cap (which is where some Starter tiers land) means you're tracking your brand against ~5 competitors across maybe 10 query themes. That's enough for an audit, not enough for ongoing optimization where you want to see weekly drift across dozens of query intents.

At Citare we run 10-20 client audits per day for outreach — each audit is hundreds of cells (queries × platforms × competitor sets). That volume needs different infrastructure than a tool tuned for "show me my brand on 50 prompts once a week."

4. Pricing model

Two flavors: per-query-style (Otterly's tiers, AthenaHQ's plans) vs flat-with-enterprise-gate (Profound, Brandlight). The flat-with-gate model gates the volumes you actually need behind enterprise pricing. Read the fine print on what "enterprise" means — it's usually $1000+/mo with annual commit.

For a solo founder, the per-query tiers are friendlier because you can start small and grow into a higher tier as your tracking needs scale.

The comparison matrix — feature-by-feature

If you only read one row, read the "Method" column. The choice between API and browser is doing more work than any other column in this table.

Picks by use case

Enterprise brand marketing team ($10M-$500M revenue, 50+ marketing FTEs, $1000+/mo software discretion) → Profound. The category leader, raised $96M in Feb 2026, the enterprise tooling is the most polished. You'll pay for it. Brandlight is the alternative if you need platforms beyond the big 5.

SEO agency tracking client visibility → Otterly.ai. White-label support and 40+ countries make multi-client accounting clean. The API method is fine because your clients aren't asking deep questions about API-vs-browser accuracy — they want a presentable dashboard at a defensible cost-per-client.

Solo founder or small team wanting accuracy on a tight budget → Citare. Cheapest in the field while using browser testing instead of API. Skip the enterprise tools entirely; you're not their ICP and you'll feel it in the contract terms. (Disclosure: Citare is my product. The honest alternative I'd recommend if Citare isn't a fit is Peec AI — same browser-test method at a slightly higher price.)

DIY for first 60-90 days → Skip all tools. Open 5 browser tabs. Run your queries. Log a spreadsheet. You'll learn the category faster from doing it manually than from any tool's dashboard. Move to a paid tool once the manual work is taking >2 hours/week.

Where Citare wins and where it doesn't

Wins:

• Real browser testing across all 5 major platforms — measures what users actually see
• Daily refresh, brutally tested (we eat our own dogfood with 10-20 client audits/day for outreach)
• Below the $300/mo floor most competitors sit at
• Built by someone who ships rather than someone who pitches — the product moves fast

Doesn't win:

• We don't have years of historical SEO data like Ahrefs or DataForSEO. If you're trying to triangulate AI search visibility against classical SERP history, those tools own that lane. But — and this is the part that's worth re-reading — that classical SEO data matters less now that GEO is in play. The era of keyword stuffing and spam-volume content is over. Citation behavior on AI platforms is its own measurement domain, and history-of-classical-SERP is not strongly predictive of it.
• Less polish than the enterprise tools (Profound's UI is gorgeous; Citare's is functional).
• No enterprise SLAs yet. If your buyer needs SOC 2 + DPA + 24/7 support, we're not your tool — pick Profound or Brandlight.

What I'd actually pick, by situation

What's next

• The fundamentals of why these tools exist at all: The Four-Index Reality: Why AI Search Isn't One Thing
• Google's official position on what AIO means for SEO (and the parts that don't hold up): GEO vs SEO in 2026 — What Google's May Guidance Changed
• How Citare itself got built end-to-end in 12 days: How I Built Citare V2 in 12 Days After Throwing V1 Away

The category will consolidate over the next 12 months. The API-vs-browser distinction will become table stakes; tools that took the API shortcut will either rebuild on browser infrastructure or get acquired and rolled into bigger marketing suites. Pick now based on accuracy and price; revisit in 6 months as the dust settles.