AEO Competitive Landscape · 2026
The AEO space is moving fast — new tools appear monthly. Here's an honest, feature-by-feature breakdown of every platform optimizing for AI-generated answers, so you can pick the right tool for your team.
The field
The "AI Engine Optimization" category has exploded since late 2025. Here's every player we're tracking, grouped by approach.
Head to head
Every capability that matters for AI Engine Optimization — mapped across the top platforms.
| Feature | Kepten.AI | Profound | Otterly.AI | Peec AI | Semrush AI | BrightEdge |
|---|---|---|---|---|---|---|
| AI Models Tracked | ||||||
| ChatGPT / GPT-4o | ✓ | ✓ | ✓ | ✓ | ✓ | — |
| Claude | ✓ | ✓ | — | ✓ | — | — |
| Perplexity | ✓ | ✓ | ✓ | ✓ | ◐Beta | — |
| Gemini | ✓ | ✓ | — | ✓ | — | — |
| Microsoft Copilot | ✓ | — | — | ◐ | — | — |
| Grok | ✓ | — | — | — | — | — |
| Google AI Overviews | ◐Planned | ✓ | ✓ | ✓ | ✓ | ✓ |
| OSS models (Llama, Mistral) | ✓via OpenRouter | — | — | — | — | — |
| Core Tracking | ||||||
| Mention detection | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| Position tracking (rank in list) | ✓ | ✓ | ✓ | ✓ | ◐ | — |
| Share of Voice | ✓ | ✓ | — | ✓ | ◐ | — |
| Recommendation strength (primary / secondary / incidental) | ✓ | — | — | — | — | — |
| Verbatim excerpt extraction | ✓ | ◐ | — | ✓ | — | — |
| Deep Analysis (Extraction Layers) | ||||||
| Sentiment analysis | ✓3-axis scores + phrases | — | — | ◐Basic pos/neg | — | — |
| Citation / source tracking | ✓URL + domain + publication | ◐Perplexity only | — | ✓ | — | ◐Google only |
| Competitor extraction per response | ✓All brands + positions | ✓ | ◐ | ✓ | ◐ | — |
| Attribute / claim extraction | ✓"Why AI recommends you" | — | — | — | — | — |
| Comparison framing analysis | ✓ | — | — | — | — | — |
| Prompt Management | ||||||
| Custom prompt library | ✓ | ✓ | ✓ | ✓ | — | — |
| Intent-typed prompts (recommendation, comparison, segment…) | ✓ | — | — | — | — | — |
| Tiered scheduling (daily / 48h / weekly) | ✓ | ◐Daily only | ◐Weekly only | ✓ | — | — |
| Multi-language prompt translation | ✓Cached translations | ◐ | — | ✓ | — | — |
| Per-vertical prompt templates | ✓Hotels, SaaS, Finance… | — | — | — | — | — |
| Reporting & Insights | ||||||
| Heatmap view (prompt × model) | ✓ | ✓ | — | ◐ | — | — |
| AI-generated action plans | ✓AEO Action Plan | — | — | — | ◐Generic SEO tips | ◐Enterprise only |
| Agent Voyage visualization | ✓Unique to Kepten | — | — | — | — | — |
| Visibility trend (90-day timeline) | ✓ | ✓ | ◐30 days | ✓ | ✓ | ✓ |
| Shareable report links | ✓ | ✓ | — | ✓ | ✓ | ✓ |
| PDF / email digest export | ✓ | ◐ | — | ✓ | ✓ | ✓ |
| Weekly Captain's Log digest | ✓Signal-over-noise digest | — | — | — | — | — |
| Architecture & Deployment | ||||||
| Self-hosted / on-prem option | ✓Docker compose | — | — | — | — | — |
| API access | ✓Full REST API | ✓ | — | ✓ | ✓ | ✓ |
| Bring your own API keys | ✓ | — | — | — | — | — |
| Open source | ◐Planned | — | — | — | — | — |
| Raw response storage | ✓Every response archived | ◐ | — | ✓ | — | — |
Cost
What you actually pay for AI visibility monitoring. Prices as of May 2026.
Every AI response is analyzed by 5 specialized extractors running in parallel: mention detection, sentiment analysis, citation tracking, competitor mapping, and attribute extraction. No other tool goes this deep.
Our signature visualization shows the full journey of how AI models discover, evaluate, and recommend your product — from the prompts that trigger attention to the sources that anchor trust.
Most AEO tools show you data. Kepten tells you what to do: which pages to publish, which reviews to address, which editorial coverage to pursue. Every insight maps to a specific move.
ChatGPT, Claude, Perplexity, Gemini, Copilot, Grok, plus any open-source model via OpenRouter. The widest model coverage in the category — because your buyers use more than one AI.
Bring your own API keys, deploy with Docker Compose on your infrastructure. Full data sovereignty — your competitive intelligence never leaves your servers. No other AEO tool offers this.
Every single AI response is stored verbatim and re-extractable. When extraction prompts improve, you can re-process historical responses without re-querying the models.
AI Engine Optimization (AEO) is the practice of monitoring and improving how AI models (ChatGPT, Claude, Perplexity, Gemini, etc.) describe, recommend, and cite your product or brand. As more consumers use AI assistants to make purchasing decisions, being visible in AI-generated answers is becoming as important as ranking in Google search results. AEO tracks your "AI visibility" — whether models mention you, where they rank you, what they say about you, and which sources they cite.
Simple mention tracking tells you "yes/no — you were mentioned." Kepten goes 5 layers deeper: it extracts your exact position in the recommendation list, analyzes the sentiment of how you're described, identifies which sources the AI cited, maps every competitor mentioned in the same response, and extracts the specific attributes and claims the AI makes about you. Most importantly, Kepten turns all of this into actionable recommendations — not just data.
Different AI models recommend different products. In our data, a brand that ranks #1 on Claude might not appear at all on Gemini — because each model draws from different training data and citation sources. If you only track ChatGPT and Perplexity, you're blind to 60%+ of AI-driven discovery. Kepten covers ChatGPT, Claude, Perplexity, Gemini, Copilot, Grok, and any OSS model via OpenRouter.
Yes. Kepten is the only AEO platform that lets you use your own LLM API keys. This means full cost transparency (you see exactly what each model API call costs), no markup on API usage, and the ability to self-host the entire platform on your own infrastructure with Docker Compose. Your competitive intelligence data never leaves your servers.
Kepten ships with prompt templates for hospitality (hotels, restaurants), SaaS products, financial services, e-commerce, and consumer tech. The prompt bank and extraction pipeline are vertical-agnostic — you can monitor any product, brand, or entity that appears in AI-generated recommendations. Custom vertical templates can be configured during onboarding.
If you use our hosted service, plans start at $99/month with unlimited prompts and full model coverage. If you self-host, the only cost is the LLM API usage — approximately $15–25/month per tracked entity across all models, dominated by the Claude extraction calls. This is significantly cheaper than competitors charging $149–$499/month with fewer features.
Not yet, but it's planned. The core AEO engine is built with Python, FastAPI, and PostgreSQL. We're currently in private beta with select teams. The self-hosted Docker deployment is available today for all customers, and we plan to open-source the core engine in late 2026.
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