Top 5 Dataloop Alternatives [Key Features, Use Cases]

Labelbox

Labelbox is an end-to-end AI product-building platform that helps organizations squeeze the most out of their unstructured data.

With Labelbox, you can:

• Explore and organize data through vector and AI-powered search, intelligent grouping, or few-shot learning classification for pre-labeling;

• Annotate images, videos, audio, or text across different formats, supported by workflows and granular analytics to track progress, efficiency, and accuracy;

• Develop, optimize, and ship models to support annotation workflows that you can connect with model training frameworks, cloud providers, or data lakes.

The platform also offers on-demand labeling services that you can test on a free trial basis.

Key features

• Multiple complex data management and visualization solutions

• Native annotations across multiple data formats

• Advanced model development platform

Use if

You’re an enterprise customer with a lot of unstructured data that demands rigid organization—especially if you’re in the aerospace or government sector.

Pricing

Labelbox offers a free plan for individual research and small teams with a data limit. Apart from some of the premium features, the plans vary in the amount of data available to use—the site offers a calculator to estimate your starting price. If your data needs are larger, you need to contact the sales team.

SuperAnnotate

SuperAnnotate, as the company name suggests, is a labeling-focused platform that brings together an all-in-one AI data infrastructure system and annotation services.

SuperAnnotate caters to annotators, project managers, and data scientists. It’s split into two tiers:

• Data Studio for annotation software and services as well as quality assurance;

• ML Studio focused on data management and comprehensive MLOPs pipeline creation.

With SuperAnnote’s annotation tool, you can label images, videos, audio, text, and LiDAR. The project management platform lets you build workflows that support progress monitoring, standardized review processes, and clear analytics. The toolset also includes an LLM fine-tuning solution which includes data curation and RLHF (Reinforcement Learning from Human Feedback) capabilities.

The ML Studio covers the rest of the AI product development lifecycle. It lets the users curate and monitor data, create CI/CD pipelines with the help of webhooks and integrations, as well as train, fine-tune, and deploy models.

Superannotate’s main purpose is to provide software for data annotation and organize humans in the loop. If your goal is to build robust, complex workflows and data management pipelines or train your models entirely on the platform, look for another software.

Key features

• Various data formats supported (LiDAR, PDF, or different audio formats)

• On-demand labeling services 

• High-security standards (GDPR, HIPAA-compliant)

‍Pricing

Superannotate offers a free plan for early-stage startups and researchers. To learn the prices of pro and enterprise plans, you need to request a demo.

Use if

You need a data annotation tool with a simple UI and on-demand labeling services, and you don’t need to build complex MLOps pipelines on the platform.

Kili Technology

Kili Technology is a data training platform for creating DataOps pipelines that accelerate building quality AI products.

With Kili, you can annotate images, videos, text, PDF documents, satellite imagery, and conversations in their native formats—with the help of model-assisted labeling. You can also build flexible workflows with customized interfaces, validation rules, and review stages for maximum efficiency and accuracy. To monitor dataset and annotation quality, you can enhance your labeling pipeline with consensus stage and programmatic error spotting (by running custom detection models).

Kili Technology provides an API and Python SDK for connecting the tool to any ML stack, as well as options to directly integrate with your data storage of choice. The platform also offers an on-demand labeling workforce and ML expert guidance for labeling team training.

Kili Technology focuses mostly on data management and labeling. As such, the software won’t cover the entire AI product development process—you need to integrate it into your current MLOPs pipeline.

Key features

• Customizable, use-case-based interfaces

• Robust and flexible QA system

• On-demand ML experts

Use if

You’re looking for a data management and labeling tool that lets you slice and dice your data, and you already have an existing MLOPs pipeline in place.

Pricing

Kili Technology offers a free plan for small teams. Its next subscription tier, the Grow plan, starts at $83 a month. If you’re an enterprise client, you need to contact the sales team for price estimation.

Ango Hub

Ango Hub, formerly AngoAI, is a part of the iMerit platform, which provides data annotation solutions.

Ango lets you label images, videos, text, audio, and DICOM files in native formats. You can utilize ML-assisted labeling or multiple specialized plugins to automate the labeling process partially.

The platform also lets you build simple workflows with benchmarking as well as consensus and review stages to monitor annotation accuracy. Project management is additionally supported by user role assignment, analytics panel, and real-time troubleshooting.

iMerit additionally offers on-demand labeling workforces, an issue-solving toolkit, and MLOps solutions.

Key features

• Multiple data formats support, including DICOM and audio files

• Flexible labeling services that can replace in-house team

• Plugins that automate labeling across a few specific use cases

Use if

You’re looking for a data labeling platform (and not a complete AI product development infrastructure) that can support multiple formats at once, and you’d like to hire a labeling workforce.

Pricing

You can try out Ango Hub with a free trial. You need to request a demo from the sales team for details concerning platform capabilities and pricing.

Final words

Before you pick your alternative to Labelbox, we advise you to take a good look around and make use of the demos and trials each platform offers. Always make sure that the tool of choice can cover your specific use case—try to think of all the possible corner cases before you schedule your demo call.

And if you’re ready to check out if V7 can cover all your needs, take a look at V7 case studies to see how we already helped other businesses. Or, you can schedule a chat with the V7 customer team right away!