Search Results for "search engine optimization"
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Showing 8 open source projects for "search engine optimization"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Weaviate
Weaviate is a cloud-native, modular, real-time vector search engine
Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). -
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Vald
Vald. A Highly Scalable Distributed Vector Search Engine
Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine. Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search for neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which is made for searching from billions of feature vector data. Vald is easy to use, feature-rich and highly customizable as you needed. -
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Vearch
A distributed system for embedding-based vector retrieval
Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. -
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gse
Go efficient multilingual NLP and text segmentation
Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others. Gse is implements jieba by golang, and try add NLP support and more feature. Support common, search engine, full mode, precise mode and HMM mode multiple word segmentation modes. Support user and embed dictionary, Part-of-speech/POS tagging, analyze segment info, stop and trim words. Support multilingual: English, Chinese, Japanese and others. Support Traditional Chinese. Support HMM cut text use Viterbi algorithm. Support NLP by TensorFlow (in work). ... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also... -
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CyberStrikeAI
CyberStrikeAI is an AI-native security testing platform built in Go
...Through comprehensive lifecycle management, results are tracked, aggregated, and visualized, with support for versioned persistence, search, and risk severity scoring. -
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LLocalSearch
LLocalSearch is a completely locally running search aggregator
LLocalSearch is an open-source search engine framework designed to run entirely on local infrastructure using large language model agents to gather and synthesize information from the web. The system allows users to submit natural language questions, after which a chain of LLM-driven agents recursively searches for relevant information and compiles a response. Unlike many AI search tools, LLocalSearch operates without requiring external cloud APIs or proprietary services, making it suitable for privacy-focused or offline environments. ... -
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alvd
alvd = A Lightweight Vald. A lightweight distributed vector search
A lightweight distributed vector search engine based on Vald codebase. Vald is an awesome highly scalable distributed vector search engine works on Kubernetes. It has great features such as file-based backup, and metrics-based ordering of Agents. Also, Vald is highly configurable using YAML files. It works without Kubernetes, single binary (less than 30MB), easy to run (can be configured by command-line options), and consists of Agent and Server. alvd has almost the same features as Vald's gateway-lb + discoverer and agent-ngt. alvd depends on Vald codebase, the files came from Vald (such as internal, pkg/vald. ...
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