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Build and deploy serverless RAG
Effortlessly build, deploy, and scale Retrieval-Augmented Generation systems
Focus on AI innovation while SciPhi helps you with the infrastructure
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Flexible Document Ingestion

Default support for csv, docx, html, json, pdf, text and more.

Robust Document Management

Readily update or delete vectors at the user and document level.

Feature Rich

Select from many LLM and vector database providers. Customize your pipeline and let SciPhi handle the infra.

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It's easy to build a prototype RAG pipeline —
It's hard to deploy one that keeps up with your users

We spoke with literally hundreds of founders in the AI space and were surprised to find most of them solving different aspects of the same problem from scratch. Whether it was deployment or optimization, RAG was the most top of mind.

With SciPhi+R2R, building the best RAG system isn't so hard or confusing. Start with the basic RAG pipeline and use the platform's observability and deployment to iterate quickly when things start going wrong.

Owen Colegrove

Founder of SciPhi

Don't just take our word for it

Kevin Tang

Firebender (Ex-Two Sigma)

SciPhi cut our LLM costs, while also improving accuracy in responses. Support has been phenomenal especially with expert guidance on improving/iterating our RAG pipelines.

Kehinde Williams

Shepherd (Ex-NVIDIA)

We use SciPhi to power help our students find relevant study resources and are currently working with them to build out a multi-document RAG pipeline.

Andrew Wang

GoldenBasis (Ex-Citadel)

Really enjoyed using SciPhi--I was able to set up a RAG to talk to dozens of dense 100+ page PDF documents in just an hour.

Why build with SciPhi + R2R?

R2R is supported by a thriving community of open source collaborators. With more than 1,000 members in Discord and a direct line of access to the SciPhi team, you can be sure your questions will not go unaswered for long.

Read documentation

Solid foundations

R2R provides a strong, reliable foundation to build upon, with abstractions and pipelines that have been proven.

The framework is designed to enable fast iteration and deployment.

Pricing for every stage

Find the plan that works for you


Best for small projects.

Max of 10 pipelines

Single developer

10,000 embeddings per pipeline

100,000 requests per month

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For startups and small teams.



Unlimited pipelines

Team workspace

Up to 1M embeddings

Up to 1M requests per month

Premium RAG Pipeline

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For larger organizations.


Everything in Startup, plus

Prioritized feature onboarding

On-prem deployment option

RAG pipeline consultation

Managed migration

Private beta access

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Effortlessly build, deploy, and scale Retrieval-Augmented Generation.
Focus on AI innovation while SciPhi helps you with the infrastructure

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