Best AI Visibility Platform for Your Brand in 2026

The 73+ platforms in this space fall into three distinct categories, and understanding which category a tool belongs to matters more than comparing feature lists.

Pure-play AI visibility tools were built specifically for monitoring and optimizing how AI engines perceive brands. This category includes Profound, Peec AI, Otterly AI, Goodie, Scrunch, Bear, Knowatoa, and Sill. These platforms were designed from the ground up for non-deterministic LLM outputs, where the same query can produce different results each time, where citation behavior varies dramatically across platforms, and where traditional keyword-ranking mental models do not apply.

Legacy SEO platforms with AI features bolted on include BrightEdge, Semrush, and Ahrefs. These are excellent SEO tools that added AI visibility modules in 2025-2026 as the market emerged. The bolt-on approach means AI features inherit the underlying platform's architecture, which was designed for deterministic search rankings. This creates structural mismatches: AI visibility is not a ranking problem, and tools that treat it as one tend to oversimplify the measurement challenge.

Enterprise-only or acquired platforms include Bluefish (Fortune 500 focused, closed pilot access) and xFunnel (acquired by HubSpot in October 2025, no longer available as a standalone product). These platforms are either inaccessible to most buyers or no longer independently purchasable.

Category matters because the design assumptions baked into each tool determine what it can and cannot measure accurately. AI-first tools were architected for probabilistic outputs; bolt-on tools often force AI data into deterministic frameworks, which can be misleading.

The table below covers 13 platforms across pricing, AI engine coverage, free tier availability, and the key tradeoffs each one makes. Pricing reflects publicly available information as of March 2026; enterprise and custom tiers may differ.

Most AI visibility platforms are observation-only: they show you where your brand appears but offer no guidance on what to do about it. The consistent complaint in reviews of nearly every major GEO monitoring tool is the same sentence: "tells you what is happening but offers very little guidance on what to do about it." The table below compares the features that separate diagnostic platforms from dashboards.

GEO recommendations: what to change and why

Most AI visibility platforms stop at observation. They show your SOV score, track it over time, and leave interpretation entirely to you. The consistent complaint across reviews of Peec AI, Otterly, and most pure-play monitoring tools is the same: "tells you what is happening but offers very little guidance on what to do about it."

Sill generates specific, actionable GEO recommendations tied to individual prompts and citation patterns. Across 62 brands analyzed to date, the pipeline has produced 748 recommendations, with 87% identified as on-site content fixes: statistics integration, answer-capsule formatting, schema implementation, comparison table additions. Each recommendation is linked to the prompt cluster it targets and the citation sources that the AI platform is currently drawing from. The goal is not a generic checklist but a prioritized set of changes tied to measurable SOV impact. Profound's Actions feature generates content briefs (a different approach to the same problem); Otterly's GEO audit evaluates 25 on-page factors. Most other platforms in the market provide no optimization guidance at all.

Experimentation: separating content impact from noise

No platform in the current market offers rigorous experimentation for AI visibility. Every GEO monitoring tool, including Sill today, relies on before-and-after SOV comparisons that cannot distinguish content impact from model updates, competitor shifts, or the 40-60% monthly turnover in citation sources. This is the proof gap that the entire market shares.

Sill is building a counterfactual simulation layer to close that gap: within-brand query controls (prompts that should not respond to a content change, serving as a baseline), hierarchical Bayesian estimation for effect sizing, and placebo-calibrated confidence badges that flag whether an observed SOV movement is likely real or likely noise. The output is not "your SOV went up" but "your SOV on purchase-intent prompts increased 7 points following the schema change, with no corresponding movement on control prompts, over a 12-week window." This feature is in development and not yet shipped. It is listed here because the experimentation problem is what separates attribution from observation, and it is the capability gap that most practitioners identify when they outgrow monitoring dashboards. No other platform in the market is publicly building toward this.

Brand Watchdog: monitoring what AI says about you, not just whether it mentions you

SOV tracking answers whether your brand appears in AI responses. It does not answer what AI platforms are saying about your brand when they mention it. Sill's Brand Watchdog monitors the specific factual claims AI engines make about your brand: pricing, features, founding date, team size, competitive positioning. It builds a fact profile for your brand, classifies each claim by accuracy, and sends alerts when misinformation appears or existing facts change. For brands in regulated industries (financial services, healthcare, legal) where factual accuracy in AI-generated content carries compliance risk, this is a different category of monitoring than SOV tracking. Bluefish offers brand perception scoring with safety and accuracy dimensions for Fortune 500 brands. Scrunch identifies misinformation as part of its content gap analysis. Neither provides the structured fact-profile approach with automated alert classification that Watchdog delivers.

AI perception scans: how each platform sees your brand in its own words

Sill's perception scan shows how each AI platform describes your brand when asked directly. This is distinct from sentiment analysis (positive/negative scoring) offered by Profound, Peec, and BrightEdge. A perception scan surfaces the specific language, positioning, and competitive framing that each AI engine uses when talking about your brand. Two brands with identical SOV scores can have radically different perception profiles: one positioned as an industry leader, the other as a budget alternative. The perception scan reveals that difference and connects it to the source content driving the AI's characterization.

Platform divergence analysis: why one number is not enough

In Sill's analysis of 7,442 AI responses across 139 brands, 55% of brands have a 10-point-or-greater SOV spread between their best and worst AI platform. The maximum observed spread was 50 points. The reason is sourcing: 91.6% of URLs cited by AI platforms appear on only one platform. ChatGPT, Gemini, and Perplexity are not drawing from a shared source pool; they retrieve different pages and produce materially different recommendations for the same query. Sill's platform divergence analysis surfaces these differences and connects them to the citation sources driving each platform's behavior. Most monitoring tools present a single cross-platform average or per-platform SOV numbers without explaining why they differ. The divergence data is what makes multi-platform monitoring actionable rather than merely informational.

Profound is the market leader by every measurable dimension. $155M raised, $1B valuation, 700+ enterprise customers, and a dataset of 680M+ citations. Their unique differentiator is Prompt Volumes: real AI search demand data that shows how often specific queries are actually asked across AI platforms. No other vendor has this. Their $99/mo Starter plan covers ChatGPT only; meaningful multi-platform coverage requires Enterprise pricing that starts at $5K/mo and scales from there. If you have the budget and a dedicated analytics team, Profound is the most complete platform available.

BrightEdge brings 17 years of SEO data and a 3B+ keyword database, which is valuable context for teams transitioning from SEO to GEO. Their AI visibility features launched in 2025-2026 and are layered onto the existing platform architecture. The strength is the integrated view; the weakness is that AI features inherit the assumptions of a system designed for deterministic search rankings. Contracts are rigid and typically run $12K-$100K+/yr depending on the scope.

Bluefish ($24M raised) focuses on brand perception and source influence diagnostics for Fortune 500 companies, particularly in CPG and financial services. Their approach to mapping which sources influence AI recommendations for specific brands is genuinely novel. Access is limited to closed pilots with quote-based pricing, which makes evaluation difficult for most buyers.

The common limitation across all three: they require enterprise budgets and dedicated analytics teams. If you are not Fortune 500 or large mid-market with $2K+/mo budget, these platforms are not designed for you.

Peec AI is well-funded (EUR 29.1M raised, 1,300+ customers) and has the strongest multi-language support in the market at 115+ languages. Their platform supports 9 AI engines, but only 3 are included in the base price; each additional engine costs EUR 20-30/mo. The core limitation is that Peec is monitoring-only. It shows the problem but does not help fix it. There are no optimization recommendations, no content audit, and no diagnostic layer explaining why visibility scores are what they are.

Goodie has the widest engine coverage in the market at 11+ AI platforms and includes a built-in content writer for creating AI-optimized content. Starting at approximately $399/mo, it is positioned for brands that want both monitoring breadth and content production tools in one place. The tradeoff is no SOC-2 compliance, which may be a blocker for regulated industries.

Scrunch ($300/mo) introduced the Agent Experience Platform (AXP) concept: serving AI-optimized content to AI crawlers, similar to how AMP served mobile-optimized pages to Google. The concept is novel, but the credit-based consumption model means costs scale with the number of engines and queries monitored. At enterprise volumes, this can exceed the sticker price significantly.

Sill includes 6 AI engines in all plans with no add-on fees: ChatGPT, Gemini, Google AI Overviews, Perplexity, Claude, and SearchGPT. The free tier covers 5 prompts; paid plans start at $90/mo. Where Sill differs from the other mid-market platforms is the diagnostic layer. Instead of observation-only dashboards, Sill generates GEO recommendations (748 generated across 62 brands to date) and is building counterfactual simulation for content attribution: the ability to measure what would change in AI visibility if a specific piece of content were modified. The limitation is a smaller customer base compared to Peec, and the experimentation features are still in development.

The mid-market tier is where the observation-versus-diagnosis distinction matters most. Monitoring dashboards answer "what is my score?" Diagnostic tools answer "why is my score what it is, and what should I change?" Most platforms in this tier, and in the market overall, are observation-only.

Sill bridges the SMB and mid-market tiers with a genuine free tier (5 prompts across all 6 AI platforms) and a $90/mo Basic plan that includes 120 prompts with full multi-platform coverage. For startups and small teams evaluating AI visibility for the first time, the free tier provides real data from ChatGPT, Gemini, AI Overviews, Perplexity, and Claude without a credit card. The $90/mo Basic plan offers 120 prompts across all 6 platforms with no per-platform add-on fees, which is more total coverage than most competitors provide at double the price. As teams grow, the Pro tier ($225/mo, 360 prompts) adds actionable GEO recommendations and priority support. The counterfactual simulation layer (in development) is designed for the teams that start here and scale into needing content attribution evidence.

Bear ($100/mo, YC F25) is the most action-oriented platform in this tier. It includes a blog agent that generates AI-optimized content and an automated PR/outreach workflow for building the off-site signals that drive AI visibility. The tradeoff is maturity: Bear raised $500K in funding, has approximately 60 customers, and multi-platform monitoring is limited to Enterprise plans. For startups in the YC ecosystem that want to move fast on content creation, it is a compelling option. For teams that need depth of monitoring data, the early-stage limitations are real.

Otterly AI ($29/mo entry) has strong G2 ratings and a notable Adidas case study. Their GEO audit evaluates 25+ on-page factors, which is useful for content teams looking for specific optimization guidance. The constraint is scale: the Lite tier at $29/mo covers only 15 prompts. A brand needing to monitor 100+ queries across competitive categories will quickly outgrow the entry plan and land on the Standard ($189/mo) or Premium ($489/mo) tiers.

Knowatoa also offers a free tier: 2 brands, 10 prompts per brand, but limited to ChatGPT only. Their unique feature is the AI Search Console, which monitors how AI bots crawl your site, similar to Google Search Console but for AI crawlers. Paid plans range from $59/mo to $749/mo. For budget-conscious startups that want bot crawl visibility without a financial commitment, Knowatoa fills a niche that other platforms do not.

The common limitation across this tier (excluding Sill, which includes all platforms at every level) is prompt-based pricing that scales poorly, often combined with per-platform add-on fees. A brand needing 200+ prompts across 5 platforms quickly outgrows entry tiers, and the jump to meaningful coverage can bring costs in line with mid-market platforms. Evaluate total cost at your expected volume, not just the entry price.

Both Semrush and Ahrefs are excellent SEO platforms that added AI visibility features as the market emerged. Neither is a primary AI visibility tool, and neither claims to be. They are supplementary modules for SEO teams expanding into GEO.

Semrush's AI Visibility Toolkit ($99/mo add-on to an existing Semrush subscription) is the most cost-effective way to layer GEO monitoring onto an established SEO workflow. It tracks 5 AI engines and includes a free AI visibility checker tool that requires no subscription. For teams already paying for Semrush and looking for a lightweight AI signal, the add-on is straightforward. The limitation is depth: it was designed as a feature within an SEO suite, not as a standalone AI visibility platform.

Ahrefs Brand Radar has a massive 320M+ prompt database and unique backlink-to-AI correlation data from their study of 75,000 brands. The research data is genuinely valuable for understanding what drives AI visibility. The pricing structure is less straightforward: $199/mo per AI engine, which means full 6-engine coverage runs $699+/mo or more. Ahrefs also offers a basic free tier for initial exploration.

Neither platform is built for teams where AI visibility is the primary concern. If you already use Semrush or Ahrefs for SEO and want a lightweight AI layer on top, the add-ons make sense. If AI visibility is your primary investment, a purpose-built tool will serve you better.

Instead of comparing feature matrices, answer these five questions. Your answers will narrow the field to two or three candidates.

For detailed feature-by-feature analysis, pricing breakdowns, and specific guidance on which platform fits your use case, see the individual comparisons below.