Debugging rank tracking volatility across multiple SERP tools?

Following up on the recent discussion about general SERP data inconsistencies, I'm encountering a much deeper, more technical challenge with significant rank tracking volatility across several professional SEO tools we rely on. It's not merely minor day-to-day fluctuations, but rather stark, persistent differences in reported rankings – sometimes 5-10 position discrepancies for the exact same keyword, identical locale, and specified device type – when cross-referencing data from Tool A, Tool B, and even our own manual verification attempts. This strongly points towards fundamental issues in data acquisition, parsing, or perhaps even the rendering environments these tools employ. We've already gone through the usual troubleshooting playbook: meticulously verified geo-targeting settings and the proxy IPs each tool reports using, cross-referenced user-agent strings and assessed the rendering capabilities (e.g., headless browser versus raw HTML fetching) for each, extensively compared raw SERP HTML or JSON returned by tool APIs against direct browser inspections performed under controlled environments, and even attempted to replicate these inconsistencies with our own custom scripts leveraging various public proxy networks. Despite these efforts, the SERP volatility remains a significant blocker. We're seeing specific, repeatable anomalies, like Tool A consistently showing a better rank than Tool B for certain high-value keywords, even when our manual checks align more closely with Tool B's reports. Furthermore, there are baffling mobile SERP discrepancies where one tool reports a dramatically lower position than its desktop counterpart, while another shows near parity, defying any logical explanation given the specific keyword and industry context. So, beyond these basic configuration checks and API comparisons, what highly technical methodologies or advanced debugging tools are fellow analytical experts employing to pinpoint the absolute root cause of these deep-seated rank tracking volatility issues? Are there specific network analysis techniques, perhaps involving deep packet inspection or traffic mirroring, or robust data validation pipelines you've built to normalize and verify SERP data from disparate sources? I'm genuinely eager for any insights or advanced strategies to debug these persistent data discrepancies. Waiting for an expert reply.