OpenlySearch: Privacy-First Local AI Desktop Intelligence & Project Memory

Description and use

OpenlySearch is a local desktop AI assistant that provides fast semantic search, task extraction, and calendar planning while keeping all data on the user’s machine.

Problem

Freelancers, developers, and consultants need AI assistance without violating NDAs or data residency laws, and they struggle with fragmented context across files, notes, and clipboard history.

Outcome

OpenlySearch enables privacy‑first AI assistance for professionals, providing fast local search, task extraction, and calendar planning without external data transmission.

Workflow

• 1. Scan project folders and PDFs, generating 384‑dimensional embeddings with @huggingface/transformers.
• 2. Persist embeddings in a lightweight local index (userData/index.json).
• 3. Execute hybrid semantic + lexical search in under 5 ms.
• 4. Extract TODOs, FIXMEs, deadlines, and decisions via regex and optional local LLM (Ollama).
• 5. Structure deliverables into phases and bind tasks to an interactive monthly calendar with tick marks.
• 6. Monitor clipboard, filter out sensitive tokens, and store non‑sensitive snippets.
• 7. Generate daily memory briefings with text‑to‑speech audio readout.

Evidence

OpenSearch turns passive local project folders into an active, actionable workspace

Source

Every single feature runs on the user's hardware without sending a single byte to external servers

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Hybrid Semantic + Lexical Search: Instant sub‑second search combining local MiniLM embeddings (all‑MiniLM‑L6‑v2) with keyword ranking over documents, PDFs, Markdown, and code

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Searchable Clipboard Memory: Automatically captures and categorizes copied code, commands, and notes while proactively filtering out sensitive API keys and secrets

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