How Kojable works
Monitor. Diagnose. Improve. Verify.
Kojable turns scattered AI answers into a repeatable workflow for understanding company representation, deciding what deserves attention, guiding practical changes, and checking what moved.
Kojable is an AI answer alignment platform. It does not control third-party AI systems; it gives teams a structured way to investigate and improve the public evidence associated with observed answers.
The workflow
Four connected steps, not a monitoring-only dashboard
Monitor
Select the topics and questions that matter to buyer research, then observe how ChatGPT, Claude, Gemini, and Perplexity describe, compare, cite, recommend, or omit the company. Explore AI visibility monitoring.
Diagnose
Analyse answer patterns, competitor framing, source domains, cited pages, owned evidence, and missing information. Separate likely drivers from unsupported causal claims. Explore AI citation monitoring.
Improve
Prioritise the gaps that matter, explain why they deserve attention, identify where a change can realistically be made, and provide practical implementation guidance.
Verify
Retest comparable questions after changes and continue monitoring so teams can see what moved, what stayed stable, and what needs further investigation.
Inputs and scope
Start with the buyer questions that define the category
A useful baseline depends on the company, market, competitors, product language, and questions buyers use during discovery and vendor selection. Topic and question selection should cover category understanding, use cases, comparisons, evidence, risk, implementation, and pricing where relevant.
Different platforms and models can return different answers. Kojable preserves that variation instead of collapsing every observation into one unqualified score.
From diagnosis to action
Prioritised guidance should stay tied to available evidence
Recommendations can involve clearer owned pages, stronger proof, better claim support, missing comparison information, source coverage, or realistic third-party opportunities. They explain what needs attention, why it matters, where to act, and how to carry out the change.
Observed source patterns do not prove causation, and no workflow can guarantee a citation, ranking, recommendation, or revenue result. Verification therefore uses comparable retesting and ongoing monitoring rather than one-off certainty.
Next step
Establish the baseline before choosing a cadence
Start with the free AI brand audit, review the supporting research, or compare the ongoing options on the pricing page.
Run the free AI brand audit