Goodie AI is an artificial intelligence-based SEO software that optimizes your visibility in AI engines and response assistants. It transforms data into concrete actions to understand and control your presence in AI environments.
In a world where results are also built in AIs and generated responses, traditional SEO shows its limits. Optimized pages no longer guarantee visibility when AI engines prioritize context and synthesized signals. Goodie AI is responding to this change by monitoring, recommending, and orchestrating your presence on the most used AI platforms in order to remain relevant and audible.
It responds to the AI gap and favors relevance and consistency for trust.
Goodie AI brings together clear and complementary functionalities: AI Visibility Monitoring to track where your brand appears in real time; AI Optimization Hub to convert insights into concrete actions; AEO Content Writer to generate content aligned with AI requirements; Traffic and Attribution to link visits to AI results; Topic Explorer to identify high-potential topics. Together, they offer Time saver, precision and strategic alignment on AI engines and assistants.
In practice, the tool transforms these insights into concrete actions: prioritization of semantic keywords, AI-friendly editorial calendar and alerts on emerging opportunities, with clear traceability of results over time.
Goodie AI is not a traditional SEO tool that focuses only on keywords. It is not an automated content builder without a strategic framework, nor is it a simple analytics tool that is content with dashboards. It is an AI-First Optimization platform, designed to understand AI dynamics and guide the company in mastering its digital story on AI engines and assistants.
To avoid confusion, it is a results-oriented and strategic solution, not a replacement for human teams. Its aim is to inform choices, not to write the content for you or to ensure effortless performance.
In short, Goodie AI offers an approach adapted to new AI-assisted search environments. It makes it possible to capture emerging opportunities, monitor efficiency in real time, and align teams around a coherent story. For marketing leaders, it is a pragmatic way to reduce uncertainty and guide decisions towards measurable gains in the AI ecosystem and offers a clear trajectory for the team.
MentionLab is an SEO software powered by AI. It helps teams understand and improve their visibility in the results and responses generated.
Today, SEO is guided by evolutionary algorithms and AI systems that define results. Teams struggle to track relevant mentions, prioritize opportunities, and measure the impact of actions. MentionLab centralizes analysis, automates monitoring and transforms data into actionable recommendations. This approach guarantees better traceability of actions and reduces duplication in SEO efforts. It also makes it possible to quickly demonstrate the impact of optimizations to management.
Fundamental, MentionLab integrates 4 key functionalities. Query analysis to identify areas with high potential and guide optimizations. Source mapping in order to target the influences that fuel AI results. Sentiment tracking that measures the opinion around your brand and informs reputation actions. Visibility and traceability a transparent crawler that explains how content is found and interpreted. At the same time, the platform offers clear data visualization, relevant alerts, and adaptable reports for teams and agencies.
To avoid confusion, MentionLab is not an automated writing platform, or an advertising solution, or an uncontrolled scraping tool. It does not replace human expertise but supports strategic decisions and alignment with your goals. This software doesn't promise results without action; it turns information into recommendations that your teams can validate. It's not just a data connector either: it integrates to support clear governance of SEO initiatives.
By bringing together data, insights and actions around AI, MentionLab offers a measurable approach to modern SEO. It helps brands and marketing teams gain clarity about opportunities, reduce uncertainty, and align their efforts with concrete results, without forced software commitments. Neutral testing can be useful to quickly assess the impact on your workflows. This approach makes it possible to communicate results more transparently and prepares for the evolution of internal practices towards useful and ethical AI. In practice, this means concise reports, relevant alerts, and gradual integration with teams, so everyone can act quickly without unnecessary complexity and with confidence.
