Agentic AEO on Autopilot
Most brands are losing ground in AI search while their teams are still deciding what to write next.
Kojable reverse-engineers how answer engines choose what to cite. Then runs the entire growth loop autonomously, while you stay at the strategy level.
Not a content tool. Not a dashboard. An agentic system that studies answer-engine behaviour, finds citation opportunities, and executes on them. Without waiting to be told.
Optimized for
Powering business worldwide
AI search is rewriting who gets found. Most teams have no system to win it.
Answer engines don't rank pages. They decide which sources to trust, cite, and repeat. Based on signals most teams have never studied and most tools can't read.
So teams keep publishing. The agent keeps ignoring them.
The problem is not effort. It is the absence of a system that understands how answer engines actually behave and acts on that understanding autonomously.
Your competitors are not just ranking higher. They are being cited more often, more accurately, and in more contexts than you.
Kojable identifies exactly where those gaps are, why they exist, and what it would take to own them. Then it executes.
How the system works
Research
Market Radar
Gap Assessment
Entity Depth
Autonomous
Intelligence
Research
Kojable starts by studying how answer engines actually behave. Which source formats get extracted by RAG pipelines. Which domains get cited consistently. Which content structures appear in AI Overviews. This is the research moat no tool can replicate.
Market Radar
A daily sweep discovers new query opportunities, harvests high-intent questions AI models are actively answering, and surfaces the competitor gaps representing the highest-value citations you are not winning yet.
Gap Assessment
The agent grades existing sources on factual density and answer-readiness. A poorly structured page being cited by default is a displacement opportunity. Kojable finds them before your competitors do.
Entity Depth
Individual articles do not build authority. Interconnected knowledge does. The agent builds Hub and Spoke clusters that give answer engines full entity coverage. The depth LLMs assess before deciding what to cite.
Autonomous Execution
Answer-ready content. Multi-agent peer review. Strategic velocity adjusted in real time based on what is gaining traction. The system doubles down on winners and cuts what is not working. Without requiring a quarterly review.
Compounding Intelligence
Every cycle feeds back into a domain-specific intelligence layer. Model behaviour research. Domain performance history. Proven cluster templates. The longer it runs, the smarter it gets, and the less direction it needs.
A research-driven agentic system.
| Capability | Kojable | MarketMuse | SurferSEO | Jasper | Relixir |
|---|---|---|---|---|---|
| Agentic - human steers, agent executes | ✅ | ❌ | ❌ | ❌ | ❌ |
| Research-first LLM behaviour analysis | ✅ | ❌ | ❌ | ❌ | ❌ |
| Progressive autonomy, learns your domain | ✅ | ❌ | ❌ | ❌ | ❌ |
| Self-improving domain dataset | ✅ | ❌ | ❌ | ❌ | ❌ |
| Financial SAM / Share of Voice north star | ✅ | ❌ | ❌ | ❌ | ❌ |
| Strategic auto-scaling per cluster | ✅ | ❌ | ❌ | ❌ | ❌ |
| Daily Market Radar sweep | ✅ | ❌ | ❌ | ❌ | ❌ |
| Multi-agent peer review engine | ✅ | ❌ | ❌ | Partial | ❌ |
The difference is not incremental. It is architectural.
Pricing
1. Free Brand Audit
See what AI actually cites
In 30 seconds, see how ChatGPT, Claude, and Perplexity position your brand against 3 competitors. And identify exactly where you are losing citations.
- ✓ 3-Competitor citation analysis
- ✓ AI Perception score
- ✓ Prioritized gap assessment
2. Founder-Led Sprint
Agentic deployment
A 4‑week sprint deploying the full agentic AEO system against your domain. Proving citation lift and building the intelligence layer.
We execute:
- ✓ Deep Market Radar deployment
- ✓ Entity Depth cluster generation
- ✓ Autonomous multi-channel execution
📅 Limited availability
Working directly with the founder.
3. Self‑Serve
Full autonomy
For teams ready to run the agentic engine themselves. Full access to Market Radar, Entity Clustering, and the Execution layer.
- ✓ Custom SAM / Share of Voice tracking
- ✓ Unlimited cluster generation
- ✓ Direct CMS integration
Why Founder‑Led?
Agencies scale headcount. I scale software.
You don't need another account manager; you need the architect.
For 4 weeks, you get my direct focus. Every problem we solve
together feeds back into the intelligence layer, making the system smarter and
your compounding moat deeper.
The Trade: You get category-defining AI citation growth
without the retainer bloat. I get the real-world data to harden
Kojable's autonomous execution engine.
Why Marketing Leaders Choose Kojable
The competitive edge your team needs in the AI-first era
Research Moat, Not Keyword Reports
Most tools show you’re ranking #5 for a keyword. We research why answer engines choose to cite specific structures and formats for that query. This proprietary behavioural research forms the foundation of every execution decision.
Autonomous Execution
Your competitors hire agencies for manual content. Kojable's agent automatically builds Hub-and-Spoke entity clusters and deploys answer-ready content. Multi-agent peer review ensures output quality scales without you.
A Moat That Compounds
Content decays. Agentic domain intelligence compounds. Every cycle feeds back into local memory: proven cluster templates, citation velocity, and format winners. The longer the system runs, the less direction it needs.
Strategic Control
You never give up the steering wheel. You define the financial north star. The SAM and Share of Voice targets. And review the execution. The agent handles the tactics, letting you manage the strategy.
Every cycle you wait is a compounding advantage for someone else.
When competitors start deploying agentic AEO systems, they aren't just publishing more content. They are building a self-improving dataset that answer engines learn to trust.
Authority in AI search compounds. The domains that establish their entity depth today will be the default citations tomorrow. Once a competitor trains the models to use them as the primary source, displacing them takes exponential effort.
You can't catch a compounding system with a manual content team. You have to deploy your own.
Supporting Partners & Recognition
Frequently Asked Questions
Most tools analyze keyword rankings or generate generic content. Kojable is a research-first agentic system. We deploy our Market Radar to reverse-engineer exactly why answer engines (ChatGPT, Perplexity, Claude) prefer certain brands, then automatically build the Entity Depth required to displace them. We don't chase visibility; we engineer authority.
LLMs don't rank pages; they synthesize concepts. If you don't understand the specific structures, schema, and reasoning patterns an LLM uses to answer a query, your content will be ignored. We research the exact logic applied to your category so you can provide the definitive answer.
While you set strategic targets (SAM and Share of Voice), our system executes autonomously. It continuously sweeps the market for citation gaps, scores your domain's authority, generates new Hub and Spoke content clusters, implements AI-readable schema, and deploys it to your CMS. All while running multi-agent peer reviews to guarantee quality.
Kojable builds local memory specific to your domain. Every successful citation, every content format that wins, and every piece of brand context is fed back into your entity graph. This compounding intelligence means the system needs less guidance and produces more accurate, highly-tailored execution the longer you use it.
We designed Kojable for growth-focused marketing leaders, technical founders, and B2B brands in complex, high-consideration markets where being misunderstood by AI means losing enterprise deals. If your product requires nuance, you need agentic AEO.
AI Share of Voice measures how frequently and favorably your brand is cited by LLMs across your core commercial queries compared to competitors. We track this daily across major models, giving you a definitive metric for your AI market penetration.
While algorithmic SEO can take 6 months, agentic AEO operates on LLM training cycles. By fixing critical gaps and deploying correctly structured Entity Depth, our clients typically measure citation frequency improvements within 30 to 45 days.
No. The Kojable engine handles the technical heavy lifting, from schema generation to CMS deployment. The workflow is designed to be steered by strategists and marketers, requiring zero engineering hours from your team.
SEO optimizes for search engine ranking pages (blue links). GEO (Generative Engine Optimization) focuses on getting mentioned in AI overviews. AEO (Answer Engine Optimization) goes deeper. It's about becoming the trusted source of truth that LLMs rely on to construct their answers, requiring a fundamental shift from keyword density to entity authority.
Our Market Radar continuously tracks citation patterns across the major answer engines defining B2B research: ChatGPT, Perplexity, Google Gemini, and Claude.