Enterprise pricing for multi-domain marketing teams
Kachi offers consolidated enterprise licensing for marketing teams managing large multi-domain portfolios, featuring unified log ingestion and cross-domain citation analytics.
CMOs and Portfolio Directors managing 50+ digital properties.
Small businesses with single-domain presence.
Scale-ready infrastructure is required to normalize data across diverse business units.
A global media holding company saved 45% on attribution costs by consolidating their AI visibility tracking onto Kachi's enterprise plan.
Part of Kachi's Technical Insight Series on Answer Engine Optimization.
Managing the AI Attack Surface
For an enterprise, AI isn’t just a search opportunity; it’s an attribution challenge. With content spread across global subdomains, maintaining a cohesive view of how LLMs are using your data is critical.
The Unified Ingestion Model
Kachi allows you to “Logpush” data from your entire network directly into our normalization engine. This eliminates the need to install individual trackers on every property, ensuring 100% coverage from day one.
Board-Ready Reporting
We turn raw log bytes into “Share of Answer” metrics that clearly demonstrate to stakeholders how your brand is performing in the AI ecosystem relative to competitors.
How Kachi Compares
Evaluating AI visibility and attribution capabilities.
| Dimension | Kachi AI | Traditional SEO Tools |
|---|---|---|
| Scale | | |
| Centralization | | |
| Enterprise Features | | |
Technical Assurance
This content is based on our analysis of server-side data from active Kachi deployments and official AI bot documentation.
Sources & References
Frequently Asked Questions
How does Kachi handle 1,000+ subdomains?
Our pipeline is designed for massive scale, using distributed ingestion to process billions of log rows per month.
Can I partition data by business unit?
Yes, Kachi supports RBAC (Role-Based Access Control) to limit visibility to specific domains per team.
Explore AEO Research
Technical guides on navigatig the AI-first web.