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What is SciPhi?

Establish your RAG system with a straightforward methodology that surpasses conventional options like LangChain, granting you the ability to choose from a vast selection of hosted and remote services for vector databases, datasets, large language models (LLMs), and application integrations. Utilize SciPhi to add version control to your system using Git, enabling deployment from virtually any location. The SciPhi platform supports the internal management and deployment of a semantic search engine that integrates more than 1 billion embedded passages. The dedicated SciPhi team is available to assist you in embedding and indexing your initial dataset within a vector database, ensuring a solid foundation for your project. Once this is accomplished, your vector database will effortlessly connect to your SciPhi workspace along with your preferred LLM provider, guaranteeing a streamlined operational process. This all-encompassing setup not only boosts performance but also offers significant flexibility in managing complex data queries, making it an ideal solution for intricate analytical needs. By adopting this approach, you can enhance both the efficiency and responsiveness of your data-driven applications.

What is Azure AI Search?

Deliver outstanding results through a sophisticated vector database tailored for advanced retrieval augmented generation (RAG) and modern search techniques. Focus on substantial expansion with an enterprise-class vector database that incorporates robust security protocols, adherence to compliance guidelines, and ethical AI practices. Elevate your applications by utilizing cutting-edge retrieval strategies backed by thorough research and demonstrated client success stories. Seamlessly initiate your generative AI application with easy integrations across multiple platforms and data sources, accommodating various AI models and frameworks. Enable the automatic import of data from a wide range of Azure services and third-party solutions. Refine the management of vector data with integrated workflows for extraction, chunking, enrichment, and vectorization, ensuring a fluid process. Provide support for multivector functionalities, hybrid methodologies, multilingual capabilities, and metadata filtering options. Move beyond simple vector searching by integrating keyword match scoring, reranking features, geospatial search capabilities, and autocomplete functions, thereby creating a more thorough search experience. This comprehensive system not only boosts retrieval effectiveness but also equips users with enhanced tools to extract deeper insights from their data, fostering a more informed decision-making process. Furthermore, the architecture encourages continual innovation, allowing organizations to stay ahead in an increasingly competitive landscape.

Media

Media

Integrations Supported

Docker
Git

Integrations Supported

Azure AI Services
Azure Machine Learning
Azure Marketplace
Azure OpenAI Service
Cognee
Microsoft Azure
Microsoft Copilot Studio
Microsoft Foundry Agent Service
Microsoft Intelligent Data Platform
Titan CMS

API Availability

API Availability

Pricing Information

$249 per month
Free Version

Pricing Information

$0.11 per hour
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

SciPhi

Company Website

www.sciphi.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/ai-services/ai-search/

Categories and Features

Categories and Features

Popular Alternatives

Popular Alternatives

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