Brand Presence in AI — Generative Engine Optimization
When a buyer asks an AI assistant whether your company is credible, who wrote the answer?
Major large language models carry perception gaps, outdated information and negative hallucinations about many companies, and that shapes buyer decisions directly. Most mid-sized exporters have no budget for Generative Engine Optimization (GEO) across markets.
Monitor → Diagnose → Build → Publish
- 1Monitor
Periodic monitoring of how major global LLMs describe your brand and products.
- 2Diagnose
Identify perception gaps, outdated information and negative hallucinations, and trace their sources.
- 3Build
Structured knowledge injection, credibility reinforcement, multilingual dynamic content generation.
- 4Publish
Multi-channel publication, then back to monitoring: a closed loop.
How we do it
Perception monitoring reports
Brand, product and competitor dimensions; how model outputs change over time.
Structured knowledge injection
Publish company facts in forms models can rely on, correcting outdated and inaccurate outputs.
Multilingual content
Credible content generated for target-market languages with a consistent narrative.
Two deployment options
Cloud SaaS for a low-barrier baseline report; a private appliance where data must stay in the domain.
- Runs on the same global trade AI-Ready Data as GoGlobal
- Perception gaps found by GEO feed directly into ACR concept tests
Subscriptions, objective packages and engineering co-creation. Pricing is agreed on a commercial basis.
Related productsStart with one concrete scenario, not a product list.
Tell us which scenario is still not in production: where the data lives, who uses it, and who signs off. One workshop gives you a verifiable path forward.