One platform that shows the gap and defines the next step
Gencko is built for teams that want a clear answer to three questions: where are we losing in AI, why is it happening, and what do we need to change next?
Pain points
What is broken in AI commerce today
AI-led discovery is growing fast, but most brands and merchants still operate blind.
You cannot see the decision
AI shapes product discovery, but most teams still do not know when, where, or why they are losing.
You do not know what to fix
Even when a competitor wins, the real causes across content, sources, and technical product data remain unclear.
AI traffic does not convert cleanly
Without structured product access, variant logic, and buy paths, AI-driven demand leaks before checkout.
The platform
Gencko makes AI commerce visible, actionable, and buyable
We connect monitoring, recommendations, and commerce enablement in one workflow.
Monitor the AI channel
Track prompts, models, competitors, and recommendation movement across the AI channel.
Prioritize the right actions
Translate source and competitor signals into clear next steps your team can actually execute.
Enable AI-native buying
Expose clean product data and buying logic so agents and LLMs can choose and buy correctly.
What we do
A simple operating model for teams that want to win
Three focused workstreams. One shared commercial goal.
Improve the pages AI and buyers read
Close the gaps on PDPs, categories, and landing pages that weaken recommendation quality.
- Content and comparison improvements
- Missing FAQs and buyer objections
- Technical clarity and structured context
Improve the sources AI cites
Prioritize the media, reviews, communities, and guide pages that already influence recommendations.
- Media and guide targets
- Review, Reddit, and forum signals
- Fixes for weak external representation
Improve how AI accesses product data
Make products easier to recommend, resolve, and purchase through MCP and APIs.
- Structured product and variant data
- Compatibility and recommendation logic
- Cart and checkout actions
Concrete capabilities
What Gencko actually provides in the product
Not just workstreams and recommendations, but concrete product capabilities teams can use to operate the AI channel.
Prompt and model tracking
See in which prompts, categories, and models products, brands, or shops appear.
- Prompt research and daily tracking
- Presence and preference development
- Comparison across multiple models
Source and competitor analysis
Understand which sources AI cites and why competitors are preferred in specific situations.
- Review, guide, and community sources
- Competitors by prompt and category
- Reasons behind recommendations
Onpage action suggestions
Turn signals into concrete improvements for PDPs, category pages, and landing pages.
- FAQs, buyer objections, and use cases
- Content and comparison gaps
- AI readability and structure
Offpage prioritization
See which external sources, media properties, and communities matter most for recommendation visibility.
- Media and guide opportunities
- Reddit, review, and forum signals
- Fixes for weak mentions
MCP and API access
Expose product data for LLMs and agents in a structured, reliable, and transaction-ready way.
- Product recommendation and variant resolution
- Compatibility and constraint logic
- Agent-ready commerce interfaces
Buyable AI flows
Connect AI recommendations to real buy paths instead of visibility alone.
- Cart and checkout readiness
- Fallback and native checkout logic
- Foundation for agentic purchasing
See how Gencko turns AI signals into concrete actions
Run an analysis or book a demo to walk through monitoring, actions, and the AI commerce layer.
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