# A Field Guide to Claim Decay > Published by **Knowledge Company** (knowledgecompany.ai). > Canonical source: https://knowledgecompany.ai/blog/field-guide-claim-decay > Markdown mirror, generated 2026-09-02. Cite the canonical URL. A practical framework for finding, prioritizing, and correcting the company claims most likely to become stale. Claim Verification Published Jul 15, 2026 Updated Sep 1, 2026 Verified Sep 1, 2026 1 min read In short Claim decay, as Knowledge Company defines it, happens when statements that were accurate at publication quietly stop being true β€” customer counts grow, pricing changes, integrations launch, and compliance language expires. The highest-risk claims are both specific and widely repeated: numbers, dates, certifications, product availability and comparative statements. A durable process records the current claim, its source of truth, its verification status and the suggested replacement, so every correction is explainable and assignable. ## What claim decay looks like Customer counts grow, pricing changes, integrations launch, and compliance language expires. The claims that were accurate at publication can become misleading long before anyone remembers to review the page. The highest-risk claims are usually both specific and widely repeated. Numbers, dates, certifications, product availability, and comparative statements deserve a clear source and review cadence. ## A reviewable workflow A durable process records the current claim, the source of truth, its verification status, and the suggested replacement. That makes every correction explainable, assignable, and ready for human review. Knowledge Company builds that process as software β€” claim, source of truth, verification status and suggested replacement, each carrying the date its check expires. ## More from the knowledge library ### Why Knowledge Freshness Is AI Infrastructure What the research actually shows about stale documents in AI systems β€” and why freshness is now being built into the retrieval layer rather than left to whoever last edited the page. ### Introducing The Knowledge Company Why maintaining accurate company knowledge has become essential infrastructure for AI systems. --- ## Related documents in this mirror - [Blog](https://llms.knowledgecompany.ai/blog.md) - [Why Knowledge Freshness Is AI Infrastructure](https://llms.knowledgecompany.ai/blog/knowledge-freshness-ai-infrastructure.md) - [Introducing The Knowledge Company](https://llms.knowledgecompany.ai/blog/introducing-the-knowledge-company.md) - [AI Systems Are Serving Outdated Company Information](https://llms.knowledgecompany.ai/blog/ai-outdated-company-information.md) - [Different AI Engines Give Different Answers About the Same Company](https://llms.knowledgecompany.ai/blog/conflicting-ai-answers.md) - [9 GEO Tools, 4 Measurement Methods](https://llms.knowledgecompany.ai/blog/geo-tools-what-they-measure.md) - [What 9 GEO Tools Actually Cost in 2026](https://llms.knowledgecompany.ai/blog/geo-tools-pricing.md) - [9 GEO Tools Track Whether AI Mentions You. Almost None Check Whether It’s True.](https://llms.knowledgecompany.ai/blog/geo-tools-accuracy-gap.md) *This document is the markdown mirror of https://knowledgecompany.ai/blog/field-guide-claim-decay, published by Knowledge Company - a knowledge freshness platform that detects, verifies and updates outdated claims in company content.* *Mirror index: https://llms.knowledgecompany.ai/index.md - Generated 2026-09-02*