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"SherlockAI is an AI-powered issue intelligence system that transforms tribal knowledge into institutional memory. When engineers face production issues, instead of asking colleagues or searching Slack, they get instant AI-generated solutions based on similar past incidents. We built this using a RAG architecture with hybrid search, achieving 85% accuracy and reducing resolution time from 60 minutes to 5 minutes."
**STATUS: ADVANCED FEATURES SUCCESSFULLY IMPLEMENTED** β
> Design document analyzing how user actions feed back into ML predictions,
Tensor factorization is a method for decomposing tensors, which are described in [Section @sec:loading-rescal], into lower-rank approximations.
Demo data: `thelook_ecommerce` from BigQuery public dataset (7 tables).
- **Plugin interface patterns**: Leveraged AI suggestions for the BasePlugin abstract class structure
This demo showcases the key capabilities of Tensorus, an agentic tensor database/data lake. We'll walk through data ingestion, storage, querying, tensor operations, and how to interact with the system via its UI and APIs.
**Project:** AI-Powered Privacy-First Study Companion
βββ package.json # Root monorepo β concurrently runs client + server
The AI Research Assistant is a powerful tool that combines knowledge graphs, semantic search, and AI agents to help researchers analyze academic papers, identify research gaps, and generate hypotheses. The system supports both local and cloud-based AI models, with a focus on privacy and flexibility.
> Based on: `architecture.md`
Repository: `WajeehAlamoudi/Smart_AI_Camera`
Build an AI-driven email onebox aggregator with real-time IMAP synchronization, intelligent categorization, and RAG-powered reply suggestions using TypeScript and Node.js.
> Build date: Saturday, 14 March 2026
A hands-on demonstration of Vectro+'s embedding optimization capabilities.
> Source of truth for what to build. Every task must be checked off before moving to the next.
- **Primary Model**: `all-MiniLM-L6-v2` base model with legal domain fine-tuning
This file provides guidance to WARP (warp.dev) when working with code in this repository.
TΓΌm local AI agent'lar (Claude Code, Cursor, Gemini, Antigravity, vb.) iΓ§in merkezi bir memory sistemi. Docker ΓΌzerinde Γ§alΔ±Εan Go MCP Server + REST API, PostgreSQL + pgvector DB, Ollama embedding, ve Web UI.
Nowadays AI provides many great features, from quick answers to smarter search and digital assistants.
> This repository contains a ready-to-use Low-Level Design (LLD) for the Intelligent Document Query Platform. It is organized so you can drop each file into a GitHub repo and iterate from there.
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In our previous session, we explored basic graph matching using spatial coordinates and the Hungarian Algorithm. While this approach provides a foundation for matching keypoints between images, it only considers geometric distances. In this session, we'll enhance our matching by incorporating topological features using node2vec and commute times embeddings.
