Findrix - 2026 Pricing, Features, Reviews & Alternatives

Findrix is an AI brand intelligence platform designed to audit, optimize, and monitor how generative AI engines perceive and cite business entities in their responses. The platform tracks answers from major AI models including ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, Google AI Mode, and Grok for market relevant queries. It delivers prioritized technical, content, and off-site recommendations to enhance brand citation performance across monitored engines. The solution addresses brand visibility within generative engine optimization and answer engine optimization disciplines.

The platform operates a three-phase workflow of detection, correction, and measurement. In detection, category specific prompts run across all monitored AI models to establish citation share benchmarks and competitive positioning. A comprehensive technical audit spanning over thirty validation checks evaluates structured data implementation, metadata quality, schema markup presence, and content signals. Detection results form the basis for corrective action planning.

During correction, the platform delivers fully written recommendations with detailed instructions for content management systems. Proposed changes range from meta description updates and JSON-LD schema additions to robots dot txt adjustments and enhanced llms dot txt files. Each recommendation includes side-by-side before and after comparisons and is ranked by impact based on audit weight and current status. A source mapping component identifies the external publications and community threads that feed AI responses and guides targeted outreach. A fact checker tracks user defined brand facts such as pricing, founding dates, product specifications, and compliance certifications across AI answers and source materials and flags discrepancies.

In measurement, Findrix conducts weekly re-audits to track citation share progression, AI preference ratings from one to ten, prompt by prompt performance breakdowns by model, source mix analysis, and competitor benchmarking. All metrics display confidence intervals and uncertainty indicators to support data accuracy. Generated reports are exportable as branded PDF documents. Prompt sets are sized to each market until new competitors cease appearing and results undergo multiple checks for source coverage, ranking stability, sample validity, and competitor count to ensure defensible metrics.