Nevar

Search behaviour has shifted: a growing share of buyers now get their shortlist from an AI answer rather than a page of links. Nevar targets that shift directly. Instead of reporting on keyword positions, it reports on whether your brand actually appears in AI-generated answers, which questions trigger a mention, and whether those references are consistent. The platform frames this as a verification layer for AI search, which is the part most marketing teams currently lack.

On the optimisation side, Nevar approaches AI visibility as a data problem. It starts with brand data accuracy, then uses Model Context Protocol templates to give models a structured picture of the business. From there it simulates the kinds of questions users ask AI, identifies the highest-value ones, and applies a strategy model that the team updates weekly. The platform handles CMS management, including WordPress today with more platforms planned, AI crawler management so site content is fully usable by models, and multimodal brand optimisation that seeks third-party and user validation rather than only self-promotion.

The commercial structure is aimed at teams that need repeatable output rather than a one-off audit. Plans bundle quotas for WordPress sites, brand MCP entries, keyword mining, article generation, and GEO optimisation runs per month, with an enterprise tier handled by the founding team. Nevar publishes named case results, such as one brand reporting a one-month visibility increase, and maintains a template library covering e-commerce, technology, manufacturing, service and general enterprise use cases.