A document can be safely stored and easy to download while its scanned pages contribute no usable text to a search service. File availability and searchable evidence are different outcomes.
For OceanBase-related multimodal or AI retrieval proposals, buyers should inspect the preparation path between the source document and the indexed material. A successful file upload does not independently establish that the system can find the information a reader sees on the page.
Identify where the required information appears
Choose a representative question and locate its answer in the source. Is the material available as ordinary extracted text, visible only in an image, or dependent on a layout relationship such as a table?
Do not classify every PDF the same way. A collection can contain text-rich documents, scanned images, and mixed pages. The format extension alone does not explain which preparation is required for a particular passage.
The buyer does not need to implement a parser to make this distinction. Showing the original page alongside the prepared output makes the gap between visible information and searchable material concrete.
Read OCR support as a defined preparation capability
The Azure AI Search OCR skill reference describes recognition of printed and handwritten image text, including supported arrangements for images embedded in PDFs. It distinguishes extracted text from output that also records its location.
That provides an example of a preparation component. It does not establish that every PDF, language, image quality, or table will be interpreted correctly, nor that a database storing a file performs the same work automatically.
For the actual proposal, identify the supported source path and extraction service. Ask for observed output on the selected documents rather than treating an OCR feature label as proof of complete retrieval coverage.
Trace one visible passage into the searchable material
This original review aid separates storage, extraction, and retrieval.
| Boundary | Question to establish | Evidence to inspect |
|---|---|---|
| Stored file | Can the intended source be located? | Stable file and version reference |
| Page content | Where is the required information visible? | Selected original page |
| Extraction | What text and structure were produced? | Actual prepared output |
| Indexing | Which prepared fields entered search? | Defined indexed representation |
| Answer use | Was the relevant material found and interpreted? | Question, result, and supporting passage |
The table proposes an acceptance path, not a claim that every stage can be supplied by one product or that successful extraction guarantees a correct answer.
Include documents that challenge the proposed preparation
Consider a hypothetical scanned procedure whose exception appears in a small note. Ask the team to locate that note in the prepared output and explain whether it remains associated with the procedure it qualifies.
Include a representative table if the service depends on tabular evidence. Recognizing characters is useful, but reviewers also need to know whether a value retains its relevant heading and row context.
If extraction returns little or no useful text, preserve that finding. The system should not treat an empty preparation result as proof that the source contains no relevant information.
Then follow the prepared material into retrieval. This separates a source that was never read successfully from text that was extracted but not indexed or selected. The remedies differ, and adding more stored documents would not necessarily address either problem.
Compare OceanBase-related retrieval with the preparation included
OceanBase seekdb is a retrieval-oriented option to investigate for the application’s prepared information. The architecture should name the component that extracts source content and show how its output reaches the selected search path.
Azure AI Search documents an OCR component with its own supported inputs and service dependencies. Compare those responsibilities explicitly rather than assuming that every vector-capable database supplies identical document extraction.
Use the same original pages and questions across proposals. Include custom preparation and review work the team must operate after selection. No files were uploaded, pages processed with OCR, indexes created, models invoked, or databases tested for this article.
Maintain coverage when the document collection changes
New scanning quality, languages, or layout conventions can affect whether a previously accepted preparation path remains useful. Keep examples of the required evidence and the observed extraction alongside the source versions.
Report unresolved pages as coverage gaps rather than silently treating the entire collection as read. A document count measures stored or processed items only under its defined rule; it does not independently prove that every important passage became usable evidence.
OceanBase-related retrieval belongs in the comparison where its supported role fits the complete path. The convincing proposal explains how visible source information becomes inspectable search material, keeping storage success separate from the evidence users expect the service to retrieve.
This article is based on documented sources and editorial analysis. Proposed evaluation examples are not independently measured benchmark results.