SciPhi Description
Create your RAG system using a more straightforward approach than options such as LangChain, enabling you to select from an extensive array of hosted and remote services for vector databases, datasets, Large Language Models (LLMs), and application integrations. Leverage SciPhi to implement version control for your system through Git and deploy it from any location. SciPhi's platform is utilized internally to efficiently manage and deploy a semantic search engine that encompasses over 1 billion embedded passages. The SciPhi team will support you in the embedding and indexing process of your initial dataset within a vector database. After this, the vector database will seamlessly integrate into your SciPhi workspace alongside your chosen LLM provider, ensuring a smooth operational flow. This comprehensive setup allows for enhanced performance and flexibility in handling complex data queries.
SciPhi Alternatives
LM-Kit.NET
LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
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Vertex AI
Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case.
Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Vectorize
Vectorize is a specialized platform that converts unstructured data into efficiently optimized vector search indexes, enhancing retrieval-augmented generation workflows. Users can import documents or establish connections with external knowledge management systems, enabling the platform to extract natural language that is compatible with large language models. By evaluating various chunking and embedding strategies simultaneously, Vectorize provides tailored recommendations while also allowing users the flexibility to select their preferred methods. After a vector configuration is chosen, the platform implements it into a real-time pipeline that adapts to any changes in data, ensuring that search results remain precise and relevant. Vectorize features integrations with a wide range of knowledge repositories, collaboration tools, and customer relationship management systems, facilitating the smooth incorporation of data into generative AI frameworks. Moreover, it also aids in the creation and maintenance of vector indexes within chosen vector databases, further enhancing its utility for users. This comprehensive approach positions Vectorize as a valuable tool for organizations looking to leverage their data effectively for advanced AI applications.
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Pinecone
The AI Knowledge Platform.
The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems.
Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval.
Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters.
Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.
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Pricing
Pricing Starts At:
$249 per month
Free Version:
Yes
Integrations
Company Details
Company:
SciPhi
Website:
www.sciphi.ai/
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Product Details
Platforms
Web-Based
Customer Support
Online Support
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