SciPhi

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KI-Verzeichnis : AI Knowledge Base, Large Language Models (LLMs)

SciPhi Website screenshot

What is SciPhi?

SciPhi is a cloud platform for developers that simplifies building and deploying serverless RAG pipelines.

How to use SciPhi?

1. Sign up for an account on SciPhi. 2. Build your RAG pipeline using the intuitive framework. 3. Deploy your solution into production with just one click. 4. Monitor embeddings, RAG, and evaluation results in real-time. 5. Scale your deployment with autoscaling serverless technology.

SciPhi's Core Features

One-click RAG deployment

Intuitive framework with abstractions

Real-time monitoring

Autoscaling serverless deployment

SciPhi's Use Cases

Build retrieval for AI applications

Power sales, education, and personal assistant solutions

FAQ from SciPhi

What is SciPhi?

SciPhi is a cloud platform for developers that simplifies building and deploying serverless RAG pipelines.

How to use SciPhi?

1. Sign up for an account on SciPhi.n2. Build your RAG pipeline using the intuitive framework.n3. Deploy your solution into production with just one click.n4. Monitor embeddings, RAG, and evaluation results in real-time.n5. Scale your deployment with autoscaling serverless technology.

How does SciPhi compare to the OpenAI assistant?

SciPhi allows you to select OpenAI as an LLM completion provider, therefore SciPhi can offer the same features of the OpenAI assistant API. However, with SciPhi you have full observability into the RAG pipeline and the ability to fully customize your solution.

What are some primary use cases for SciPhi?

SciPhi allows for the seamless deployment of any LLM backend that requires Retrieval Augmented Generation (RAG). Further, the SciPhi platform makes it easy to monitor and improve your solution over time. Our users are already leveraging the platform to power sales, education, and personal assistant solutions.

What is the largest AI solution powered by SciPhi?

The platform provided by SciPhi is used internally to manage and deploy a semantic search engine with over 1 billion embedded passages.

What is included in the hands-on setup?

The team at SciPhi will assist in embedding and indexing your initial dataset in a vector database. The vector database is then integrated into your SciPhi workspace, along with your selected LLM provider. The above work forms a complete pipeline that is then deployed and transferred to your SciPhi workspace.

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