private AI file search for your desktop
LocalSpider helps you find files by meaning across images, PDFs, documents, spreadsheets, and presentations. It is designed for local-first search, so you can use AI-powered file discovery without uploading personal files to a cloud search index.
Why you may not want cloud AI tools indexing your files
AI search is useful because it can read across messy files and understand what they are about. The tradeoff is that many cloud AI workflows require uploading files first, then building a search index on remote servers. That may be fine for public files, but it is not always comfortable for personal archives or client work.
Your desktop can contain tax PDFs, contracts, invoices, screenshots, source notes, unpublished drafts, client research, product plans, medical paperwork, and private photos. Uploading those files can raise practical questions: who can access the account, how long data is retained, what the vendor processes, what happens when a team member leaves, and whether the upload is allowed by a client or workplace policy.
LocalSpider is built around a different assumption: many people want the usefulness of AI-powered file search, but do not want to create a cloud search index of everything sitting on their laptop. That makes LocalSpider useful for both local file search and broader desktop search workflows.
LocalSpider's local-first approach
LocalSpider is designed to index and search your files on your own computer. The goal is practical: make your files searchable by content and meaning without requiring a cloud upload workflow.
Build a local index
LocalSpider scans selected folders and creates a search index on your device. That index is what powers search results, so your files do not need to be copied into a cloud search service first.
Search by meaning
You can describe the file you need in natural language. LocalSpider compares that query with the meaning captured in your local index, not just exact filename matches.
Keep the workflow on-device
The product is designed so indexing and search happen locally. This reduces the need to move sensitive personal or work files into another cloud system just to find them later.
Semantic search, explained simply
Normal file search looks for exact words. If you type "contract", it looks for files with "contract" in the filename or text. That works when files are named clearly and use the same words you remember.
Semantic search looks for meaning. If you type "client contract about office rent", it can surface a file that says "commercial lease agreement" even if the filename is agreement_final_v3.pdf. The words are different, but the meaning is related. The semantic file search page explains this matching behavior in more depth.
For images, the same idea applies visually. Instead of searching only for IMG_2041.png, you can describe what an image appears to show: a login error, a receipt, a whiteboard diagram, or a product screenshot. Results are based on the local index and may not be perfect, but they are designed to be more useful than filenames alone. See search images by content for image-specific examples.
Supported file types
LocalSpider is built for the files that usually pile up across Downloads, Desktop, Documents, screenshots folders, and project archives.
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Images JPG, PNG, WEBP, HEIC, GIF, SVG - screenshots, photos, scans, diagrams, and reference images.
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PDFs Reports, invoices, manuals, papers, contracts, saved web pages, and exported documents.
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Documents DOCX, TXT, RTF, MD - notes, drafts, memos, transcripts, and writing projects.
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Spreadsheets XLSX, CSV, ODS, TSV - budgets, exports, datasets, trackers, and analysis files.
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Presentations PPTX, KEY, ODP - slide decks, product plans, pitches, lessons, and research presentations.
Use cases for private AI file search
Local-first AI search is useful when the files are valuable, messy, sensitive, or hard to name consistently.
Creators
Find drafts, reference images, screenshots, footage notes, scripts, and exported assets by describing the project or visual idea, even when filenames are versioned or generic.
Students
Search lecture PDFs, class notes, slides, assignment sheets, screenshots, and reading material by topic without uploading a semester of files to another service.
Researchers
Locate papers, excerpts, datasets, charts, scans, and notes by concept, author, method, or finding across a local research library.
Consultants
Find client deliverables, decks, invoices, meeting notes, discovery documents, and prior recommendations without creating a cloud index of client material.
Product managers
Search roadmaps, customer notes, research screenshots, specs, backlog exports, and stakeholder decks by product area or user problem.
Knowledge workers
Find the right file across downloads, folders, email exports, notes, presentations, PDFs, and spreadsheets when you remember the subject but not the filename.
Join the waitlist for private AI file search
LocalSpider is in early access. Join the waitlist to be notified at launch and lock in a discounted early-access price.
Frequently asked questions
Common questions about private AI file search and LocalSpider.