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Building a RAG workflow

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Dataloop enables easily building scalable RAG workflows end-to-end with dedicated tools purpose-built for chat-based applications.

The Problem

Today’s RAG workflows are built from a collection of fragmented tools, that need to be integrated and maintained. Iterating and validating RAG is hard, as most tools weren’t built with chat-based iterations in mind, and new models are constantly being introduced.

The fastest path to
enterprise-grade RAG workflows

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Reduce RAG time-to-market

Dataloop speeds up application development by combining the entire RAG workflow in one toolset, including a built-in vector database.

  • Quickly find the right model by picking and iterating between models without needing to reconnect each part.
  • Improve accuracy by iterate on your workflows with dedicated RAG validation capabilities.
  • Add human feedback to your RAG workflows with scalable RLHF validation capabilities.
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Don’t start from scratch

Dataloop’s Marketplace offers pre-built RAG templates and models so you can iterate and find the right model as fast as possible.

  • Pick from a constantly updating selection of RAG templates in 
Dataloop’s Marketplace.
  • Dataloop aggregates all of the latest models so you don’t have to waste time integrating them from other sources.
  • Save or make a template out of your own RAG workflows for future use by you or your team.
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Connect any data source or vector database

Easily connect to multiple data sources and vector databases (including Dataloop’s vector store) to create versatile RAG workflows.

  • Use Dataloop dedicated vector database or connect your own external one.
  • Easily manage your data to ensure your RAG workflows are fed with the data they need.
  • Utilize data management features built with unstructured data types in mind, including PDFs, transcripts and freeform text.
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Build on a solid foundation

Develop AI applications at the speed of market demand

 

Build anything with Dataloop

These are just some of the workflows our users build using the platform

Running AI in production

Deploy a model into production seamlessly, integrating everything from model development to AI operation within a single environment. Run all your AI applications from a single, cost-effective, platform.

Building a GenAI stack

Use pre-built Reinforcement Learning workflows with human and AI feedback nodes. Facilitate RLHF for GenAI at scale by allowing human feedback to be an inherent part of your operations, without the overhead.

Multi-cloud Compute

Chain multiple cloud compute nodes together in a single pipeline. Use different types of compute and different compute vendors, including all major clouds, on-premise, NVIDIA’s DGX or Dataloop’s own compute offering.

Building AI agents

Dataloop offers all the essential components to develop robust, both task-specific and general-purpose agents. Input context during model configuration, then deploy the agents to multiple destinations from within Dataloop.

FAQ

Dataloop is an AI development platform designed to empower data practitioners to collaborate and build exceptional AI solutions. It comes pre-packed with models, functions, datasets, and integrations with popular cloud platforms, ensuring you can hit the ground running when developing your AI applications.

Dataloop is an all-in-one solution, eliminating the need for multiple tools or cloud services to deliver complete, robust AI applications. Furthermore, Dataloop prioritizes RLHF, Active Learning, and other human-in-the-loop workflows, offering dedicated, state-of-the-art annotation studios for human reviewers to excel.

Dataloop offers a large Marketplace of models, datasets, pre-built workflow templates and more, and is highly-integrated with a variety of cloud platforms, data tools and more.

Read more about why Dataloop is a great choice for you in our dedicated page for Data Engineers.

Dataloop helps automate processes crucial to AI development, such as model training, human feedback (for RLHF and Active Learning) and more, and lets you focus on training your models instead of platform setup and configuration.

Read more about why Dataloop is a great choice for you in our dedicated page for Data Scientist.

In Dataloop, every piece of the pipeline can be created, modified and deleted using an API call, and our robust Python SDK allows for complete code-level control on the data pipelines you rely on to build your AI applications.

Read more about why Dataloop is a great choice for you in our dedicated page for Software Engineers.

Dataloop allow teams to focus on building AI applications, and not platform maintenance – while still allowing for complicated, human-in-the-loop flows and without compromising on quality or the speed of delivery.

Read more about why Dataloop is a great choice for you in our dedicated page for Data & AI Leaders.

To get started with Dataloop, you can talk to one of our AI experts.

At Dataloop, privacy and security are our top priorities. We adhere to leading industry standards and are dedicated to ensuring the security of your data with comprehensive governance throughout the entire platform. More specifically, Dataloop is compliant with SOC 2 Type II, GDPR, ISO 27001 and ISO 27701, and offers RBAC, 2-factor authentication, AES-256 encryption and ongoing tracking of all system resources and actions that occur within the platform.

You can read more about our security controls in our dedicated security resource.