Search today is broken. When you type words into a normal search bar, it only looks for exact text matches. It doesn't know who you are, what project you're working on, or what you need right now. This forces you to spend hours organizing files and trying different keywords just to find one simple document.
When these keyword searches fail, you are forced into an exhausting cycle of guessing words. You end up sorting through pages of irrelevant documents that share a generic word but have nothing to do with your actual goal. The search engine is completely blind to meaning.
Search Intelligence fixes this by treating search as a smart partner, looking for meaning instead of just words:
Keyword Search
Search Intelligence
Search Intelligence Understands Context, Not Just Keywords
Every search happens inside three layers of context. The first is your environment, such as where you are and what device you are using. The second is your history, including your past searches, habits, and preferences. Over time, the system deeply learns exactly what matters to you.
At the absolute center is what you are doing right now. If you are writing code, a search for "bugs" will show coding errors. If you are reading about nature, it will show insects. Search Intelligence acts like a smart partner sitting right next to you, understanding your current focus.
By combining these layers, the engine pushes irrelevant files away and pulls what you actually need to the front. The result is a search experience that feels perfectly tailored to your current task.
Three Context Layers That Shape Every Search Result
Search Intelligence protects your privacy completely. All the searching, organizing, and thinking happens right on your own device. Your private files, personal emails, and code never leave your machine and are never sent to the cloud.
If a search absolutely needs the internet, the system completely removes your identity and private details before asking the web. The results are brought back and organized safely on your machine, giving you the power of the internet with total local privacy.
Search Processing Stays On Device By Default
Connecting your personal files with the internet requires extreme safety. Without proper protection, private corporate details and sensitive financial plans could easily leak outside your secure network. Search Intelligence is built to prevent this completely.
To keep you safe, the system checks every single search before it goes out. It makes sure no private code, passwords, or personal details are ever exposed. All internet answers are brought back and processed safely inside your secure local space, giving you total control.
At its core, Search Intelligence replaces inverted keyword indices with a vector embedding space. Every piece of information you have touched, including documents, emails, notes, and web pages, is encoded as a high-dimensional vector that captures meaning, not just words.
When you search, your query is embedded into the same vector space. Semantic similarity replaces keyword matching. The result is that a query about financial projections for next quarter can surface a spreadsheet titled Revenue Model v7, because the system understands they mean the same thing.
ALM's memory layers feed directly into the ranking stage. Episodic memory adjusts scores based on recency and personal relevance. Procedural memory understands the workflows you are in the middle of. Semantic memory knows your preferences. All three layers combine in real time to produce a ranked result set that feels personally curated.
Search Intelligence utilizes a highly optimized HNSW (Hierarchical Navigable Small World) graph to perform nearest-neighbor searches in sub-millisecond times. When documents are ingested, they are immediately chunked and embedded using our proprietary 1536-dimensional embedding model, which is quantized to 8-bit precision to fit seamlessly into local memory without sacrificing semantic accuracy.
The background service continuously polls the active accessibility trees and window managers across macOS, Windows, and Linux. This polling is strictly bounded by local memory constraints, running at 10Hz to capture real-time context such as cursor position, active text fields, and visible UI elements, ensuring the semantic search always knows exactly what you are trying to accomplish.
Before a query hits the vector index, it undergoes a local expansion phase. The ObjectBrain routing layer uses a lightweight, on-device SLM (Small Language Model) to generate conceptual synonyms and related ontological paths. A simple search for 'Q3 metrics' is automatically expanded to include terms like 'revenue', 'growth', 'Q3 KPIs', and 'Q3 financial report', ensuring maximum recall.
No search query or index payload ever leaves the host device. The vector database is encrypted at rest using AES-256-GCM, and the decryption keys are held securely in the hardware enclave (Secure Enclave on Apple Silicon, or TPM 2.0 on Windows). This guarantees that even in the event of a physical device compromise, the semantic index remains mathematically unreadable.