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SAG TECHNOLOGY FRONTIER
We design how search, answers and generative AI understand brands, and explain the architecture behind SAG in clear technical terms.
SAG / ARCHITECTURE NOTES
From discovery and evidence to data boundaries, reliable execution and delivery—see how each engineering choice works.
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This is the process of turning a sitemap’s address list into crawl candidates within an approved domain. A URL list is not an analysis result. Unless language-specific duplicates, excluded pages, and other hosts are cleaned up, the workload grows while comparable evidence remains scarce.
Manage document identity by distinguishing the original link from the address used for comparison. If citations with different fragments are counted as new sources each time, the number of evidence pages is inflated. Conversely, deleting important query parameters can merge different products.
These controls prevent user-provided addresses from directing requests to internal services or networks that are not allowed. Even an address that looks legitimate can reach an internal address after a redirect or name resolution. Opening network boundaries for analytical convenience undermines trust across the entire tenant.
An internal diagnostic of answer evidence that evaluates trust, evidence, location, and connection. A good page is not always selected by external AI. Reporting internal readiness as a performance rate confuses improvement work with market response.
A design for assigning field meanings, versions, and validation rules to JSON observation and reporting data. Even when new engines are easy to add, changes in field meaning can distort historical data. Flexible storage does not mean no validation.
This data contract uses the month selected in the customer workspace as the shared basis for queries, aggregation, and page navigation. If SEO reads September while GEO reads the latest data, the numbers in one report do not describe the same period. Even if the interface is fast, comparisons become unreliable.
Measure search position, appearance in answers, and recommendation meaning as separate items. A mention near the end is not the same as a first recommendation. Converting them all into a single search ranking makes it difficult to know what to improve.
A design that keeps processing resources predictable by limiting the permitted size, entries, and paths of compressed inputs. Even a small upload can require substantial memory after decompression. Using filenames directly as paths can also risk affecting files outside the analysis system.
Learn how to organize customers’ goals, situations, constraints, and product attributes as question structures. The same keyword can reflect different budgets, environments, and decision criteria. Storing only the words misses the actual selection conditions and the product evidence needed.
Parallelize independent reads and read shared configuration once for reuse. Even small queries add latency when repeated round trips accumulate. As features grow, the cost of re-reading shared configuration can become a bottleneck rather than the model.