Search and summarize PDFs in your browser
This tool is built for long contracts, policies, reports and document sets where Ctrl+F is not enough. It creates an extractive summary, lets you select the PDFs that matter and ranks matching passages with BM25 search.
What it does
- Creates an extractive summary from each PDF so you can decide which documents deserve closer review.
- Uses BM25 ranking to surface statistically relevant passages instead of stopping at the first literal match.
- Falls back to OCR with Tesseract.js when a scanned PDF contains little machine-readable text.
- Exports search results with document name, page and matching fragment for further review.
Use the document search tool
Gestor Documental Pro
Disecciona papers, contratos y otros PDFs: detecta título, abstract, secciones, fuentes y estructura sin sacar el documento del navegador.
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Documentos cargados
Marca qué documentos participan en la búsqueda. Haz clic en un documento terminado para analizarlo.
Ficha del documento
Resumen estructurado
Secciones del documento
Buscar dentro de los documentos
Términos más repetidos
Where it helps
A simple example is a contract with twenty annexes. You may know that a penalty clause exists but not which annex contains it. Instead of opening every file and repeating the same search, you can load the set, exclude irrelevant annexes and rank the passages that contain the terms you care about.
The same pattern works for technical manuals, insurance documents, procurement records and research reports. The tool does not replace reading the source. It reduces the amount of document you have to inspect manually.
Limits worth knowing
BM25 is a retrieval method, not a reasoning model. It ranks text using term frequency and document length. Extractive summaries also reuse sentences from the source rather than generating a new interpretation. For scanned material, OCR accuracy still depends on image quality, page rotation and typography.
Privacy
The document workflow runs client-side in the browser and does not require an account. Closing or reloading the page clears the active in-memory session. Your practical limit is therefore the memory available on your own device, especially when working with many large scanned PDFs.
Need another document utility? Browse the ScalarPivot tools directory for PDF merging, PDF-to-Excel conversion and local data auditing.
Search a research paper by section, not just by keyword
A research paper has an argument that unfolds across an abstract, introduction, methods, results and discussion. A keyword match can point to a result without telling you what assumptions produced it. Start with the document outline, read the abstract to identify the central claim, then find the method and the limitations. The tool’s extractive summaries can serve as signposts, but they cannot independently judge whether the evidence is convincing. For scientific work, always compare extracted passages with the source document before citing them.
What is the difference between extractive and generative summaries?
An extractive summary selects or ranks material already present in the source. A generative model produces new prose based on its interpretation. Neither approach guarantees correctness. Extractive methods may omit qualifiers spread across different paragraphs; generative methods may introduce unsupported relationships. This tool emphasizes extraction and retrieval. That makes it especially useful when you need to find the original passage rather than receive an untraceable conclusion.
How to search a collection of PDFs efficiently
Begin by choosing a small, coherent collection of documents. If you’re reviewing a policy change, include both the earlier and newer versions and note their dates. Search for important terms and their synonyms, including abbreviations used by the authors. Check whether the highest-ranked passages come from the intended document and time period. BM25 ranks passages for likely relevance based on terms; a high rank does not mean the passage is correct, authoritative or legally controlling.
Example: finding a clause in a large contract file
A contract may discuss liability in the main body and modify its operation in an annex. Search the words “liability”, “indemnification” and any defined terms used by the parties. Read the complete surrounding clauses and cross-references, not merely the fragment returned by search. If the annex contradicts or qualifies the main provision, a brief extract from one location could be misleading. Keep the page reference when exporting results so another person can inspect the source.
Example: locating evidence in an administrative report
For an audit report, search by program name, reporting year, identifier and the expected type of evidence. Compare the reported output with its supporting section and note when the source lacks a promised annex. The tool can help locate passages; it cannot verify delivery of a service, authenticity of a document or whether a numerical claim matches the underlying records. Those questions require source checking and sometimes independent evidence.
Scanned PDFs, OCR errors and file limits
OCR is useful when a document has no reliable text layer, but it may confuse zero with the letter O, split words at line breaks, omit columns or misread faint scans. A searchable text layer is generally easier to process than a photograph of a page. For critical numbers, examine the original page image. Browser-based processing also consumes local memory, so very large scans or many simultaneous PDFs may be slower on mobile devices. If a file fails, start with a smaller document to determine whether its size or condition is the cause.
Use the right document tool for the task
If your goal is to turn a financial table into rows and columns, use PDF Tables to Excel. If you need to combine reports and annexes, use the PDF merger. If you want to check the resulting spreadsheet for missing values or duplicates, open the data audit tool. Each application handles a different stage of a reproducible document workflow.
Limit: search results and automatic summaries support reading; they should not substitute for full-context interpretation in legal, medical, scientific or financial decisions.