One loop, three beats — with an independent instrument keeping score.
Sigbase Retrieval Score (SRS) runs your client through a standardized battery of real-world queries — the questions actual customers ask AI engines in your client's niche and location. The battery runs across three AI engines in parallel, and answers are scored by consensus: an engine mentioning your client once is noise; multiple engines agreeing is signal.
The output is the Sigbase Retrieval Score (SRS): 0–100, across five dimensions of AI visibility. The score tells you — and your client — exactly where they stand in AI-generated answers today.
The gap between their score and their competitors' is the conversation. You don't have to sell anything at this stage. The number does it.
This is the white-label layer, and it's yours. Pandobix generates the fix content. You publish it. Pandobix never touches your client's site. Schema code, FAQ copy, GBP corrections, citation fixes — fully specified and ready to use.
Making the business unambiguous to machines: who it is, what it does, where it operates.
Reviews, credentials, and citations organized the way AI systems weigh them.
Content structured so engines can parse expertise, not just keywords.
The same facts about the business, everywhere the engines look.
Schema, structured data, and content depth that signals authority to retrieval systems.
Your brand is on the deliverables. Your team owns the client relationship. Pandobix is the engine behind it.
Pandobix is the white-label AI visibility partner that lets you show clients the change is real — because you're not the one saying so. You do the work; an independent score confirms it moved.
After the fixes are published, Sigbase Retrieval Score (SRS) re-runs the identical battery — same queries, same engines, same scoring math — and reports the new score alongside the baseline.
If the score moved, the report shows it, with Sigbase Retrieval Score (SRS) attribution hardcoded on the number. You never grade your own homework, and neither do we: the entity doing the optimization is never the entity certifying the score. That separation is the whole reason the score means something to your client.
HONEST NOTE, IN PLAIN SIGHT — score movement reflects changes in what third-party AI engines returned between two measured points in time. Engines evolve on their own schedules. Sigbase Retrieval Score (SRS)'s job is to hold the measurement method constant so that the comparison is fair — and to report the reading exactly as taken.