hero use cases

Validating GenAI with RLHF/RLAIF

hero use cases mobile

Create production-grade GenAI applications fast with Dataloop by embedding RLHF/RLAIF natively in the AI development process.

The Problem

Validating GenAI is complex and manual, with each step occurring in a different tool. True, reliable validation requires many iterations and most tools that deploy and run models aren’t built for RLHF/RLAIF feedback.

Validating GenAI with
RLHF/RLAIF made easy

shape blue 2.svg

The easiest path to GenAI

Get started with the latest models and combine them with human feedback to create amazing multi-modal GenAI pipelines.

  • Dataloop’s marketplace offers a massive selection of pipelines & the latest GenAI models.
  • Manage the entire GenAI workflow, including RLHF/RLAIF, in one place.
  • Prompts, datasets and models are unified in a single workflow.
shape mobile.svg

Ensure GenAI meets your standards

Dataloop makes it easy for project managers to validate GenAI annotations to ensure the data fed into your models meets your requirements.

  • Easily enforce annotation rules with Javascript files in the Annotation Studio.
  • Dedicated QA/QC workflows such as Consensus, Qualification, and Honeypot.
  • Enforce AI-powered restrictions to remove label duplications, require a minimum amount of labels and more.
shape 5 right.svg
shape mobile.svg
shape use cases blue.svg

Get GenAI to production faster

Unifying the validation process allows iterating much faster on applications to create production-grade GenAI solutions.

  • Communication features allow annotators, data scientists, and ML to collaborate and make faster decisions.
  • Easily scale up validation with humans with purpose-built RLHF environment for non-technical users.
  • Get started with pre-built GenAI pipelines that combine all the steps with minimal setup and overhead.
shape mobile.svg
left corner.svg
left corner.svg
left corner.svg
left corner.svg

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

Creating an active learning pipeline

Instantly install & get going with an active learning pipeline template from Marketplace. Run quick learning iterations with less human intervention, and quickly increase the quality of your AI application’s outputs.

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 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.

Bulding RAG workflows

Build Retrivial-Augmented-Anything workflows with Dataloop, combining models, data, compute and pipelines in one location – instead of scattered across multiple providers and platforms.

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.