This project is in development and not publicly usable yet. The purchased domain is confirmed, but there is no public live version yet.
FindabilityKit
Planned privacy-first audit for SEO and AI visibility
FindabilityKit should help website owners understand visible technical and content-related findability signals. The planned analysis considers search engines, AI Overviews, ChatGPT/LLM answer contexts and modern discovery flows as orientation, not as a promise.
Status
Processing
Account
Live version
01
About FindabilityKit
FindabilityKit is planned as a privacy-first web app/SaaS idea around traffic readiness, SEO and AI visibility. The project should review how visible, understandable and discoverable a public website appears to search engines, AI Overviews and LLM-based answer systems.
This page describes the planning state. FindabilityKit is not publicly usable yet and therefore has no live URL, no launch button and no launch date.
02
Planned Analysis Workflow
The plan is an audit for public websites. A user enters a URL, the interface normalizes the input and a separate analysis service fetches publicly visible signals.
The MVP should be able to start without AI dependency. Rule-based and algorithmic checks can combine metadata, indexability, structured content, internal links, sitemap/robots hints and AI-readiness signals into a report.
03
Use Cases
FindabilityKit is planned for small website owners, indie projects, SaaS landing pages, content sites and agency pre-checks.
The tool should provide hints about where a website could become clearer, more structured or technically easier to discover for search engines and modern discovery flows. It does not replace an SEO strategy and gives no ranking, traffic or AI visibility guarantee.
04
Planned Technical Implementation
The core is planned as a web app with a separate VPS analysis service. The start can initially work without a database as long as reports are point-in-time results and are not stored or connected to accounts.
A later data model, accounts or stored reports would need to be described separately. For the start, it is important to separate public URL review from private user data.
05
Privacy, Limits and No Ranking Guarantees
FindabilityKit should review public website signals. It must not claim to analyze private content, improve rankings or reliably trigger mentions in Google, AI Overviews, ChatGPT or other LLM answers.
A privacy-first direction here means data-minimal processing, clear purpose limitation and transparent limits. Technical operational logs or later storage features would need to be explained specifically in the privacy notes.
Planned FindabilityKit Architecture
A server-assisted analysis flow should review public website signals and interpret them in a report.
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Legend
- Local in browser
- Server
Features
Website visibility audit planned
Review public website signals in a structured way.
SEO/indexability hints
Interpret metadata, robots, sitemap and technical accessibility.
AI-readiness checks
Review content clarity and structure for LLM contexts.
Rule-based score
The MVP can start without AI dependency.
Report UI
Present hints and recommendations clearly.
Privacy-first approach
Review public signals without claiming unnecessary storage.