SciPhiFocus on AI innovation while SciPhi helps you with the infrastructure
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.
Configurable Provider
Seamlessly connect with third party data retrieval sources, including Serper, Exa, and more.
Adaptable
Customize your RAG pipeline by integrating additional plug-ins or proprietary data to tackle complex scenarios.
Dynamic Scalability
Autoscale up and down available compute with user demand.
SOTA Techniques
One-click deployment of latest techniques such as HyDE, RAG-Fusion, and Agentic RAG.
Configurable & Customizeable
Specify providers, adjust settings, and optimize performance with ease to build powerful tailored RAG applications.
Intelligent Assistants
Transform conversational AI systems into intelligent assistants capable of handling complex inquiries by augmenting their responses with retrieved information.
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.
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.
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
Free
Max of 10 pipelines
Single developer
10,000 embeddings per pipeline
100,000 requests per month
Startup
$999
$499
Unlimited pipelines
Team workspace
Up to 1M embeddings
Up to 1M requests per month
Premium RAG Pipeline
Enterprise
Custom
Everything in Startup, plus
Prioritized feature onboarding
On-prem deployment option
RAG pipeline consultation
Managed migration
Private beta access
