Kuala lumpur: GenOptima has introduced its enterprise Generative Engine Optimization (GEO) framework, providing a structured approach to artificial intelligence (AI)-powered search optimisation across multiple large language models (LLMs) and AI platforms.

According to BERNAMA News Agency, the framework is built around a Results-as-a-Service (RaaS) model, integrating Brand Info Audit, Content Preference Analysis, Exclusive Strategy, AI Model Training, and Full-Cycle Monitoring into a continuous optimisation workflow. This approach is designed to help organisations achieve measurable AI visibility through continuous optimisation, supporting over 20 global AI platforms via a Universal Cross-Model Consensus Protocol.

The platform's core feature is the GEO Expert Model Matrix, which includes 143 benchmarkable capabilities across various domains such as Industry Capabilities, LLM Adaptation Capabilities, Functional Capabilities, Multimodal Capabilities, and LLM Deep Adaptation Capabilities. These capabilities are organised into categories like Industry Vertical, LLM Adaptation, Functional, and Multimodal Experts, covering areas such as industry expertise, semantic optimisation, compliance, and citation management.

GenOptima's framework is further enhanced by its Strategic Agent Architecture. This includes the Gen-Centric Sentinel for AI visibility monitoring, Gen-Carto Nexus for strategy and intent analysis, Gen-Genesis Forge for multimodal content creation and model adaptation, and Gen-Cosmos CogniCore for knowledge graph construction and compliance. The company also emphasizes data protection, cross-border safeguards, ethical optimisation, and compliance guardrails, with execution tracking and KPI reporting to ensure accountable optimisation.

By merging expert capabilities, intelligent agents, compliance measures, and continuous optimisation, GenOptima aims to empower enterprises with scalable and long-term AI visibility management solutions.