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LayerNext Reviews & Product Details

Joe C.
JC
Enterprise(> 1000 emp.)
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Validated Reviewer
Verified Current User
Review source: Organic
What do you like best about LayerNext?

LayerNext has been great to work with and quick to address issues and add features to tailor to our needs. We use LayerNext to organize image data and record metadata as data is collected from the field. The platform gives us good flexibility to upload data from their python SDK or through their webpage UI. The user interface is helpful as it allows us to view data which makes creating annotation projects and training datasets easy. Review collected by and hosted on G2.com.

What do you dislike about LayerNext?

As it is a fairly new product, there are some aspects of that aren't as refined as they might be with a more mature product. The team is still working on improving things like the data search and reporting features which we are hoping will be improved in future releases. Review collected by and hosted on G2.com.

What problems is LayerNext solving and how is that benefiting you?

The biggest task which we use LayerNext for is for their Data Lake. We use it as a intake point for data from our data collectors in the field, the platform lets us set metadata requirements and ensure information about this data is collected. We also use it to build data collection to send in for annotation or for training datasets. Review collected by and hosted on G2.com.

LayerNext Overview

What is LayerNext?

LayerNext is the AI-powered Business Insight Generation platform. With LayerNext's proactive insights, decision-makers can move quickly and make confident, data-driven decisions. LayerNext seamlessly integrates with existing data infrastructures like cloud data warehouses (e.g., Snowflake) and DataLakes (e.g., Databricks) to distill actionable insights from both structured and unstructured data. With LayerNext, you can: Actionable Insights: - Automatically generate AI-driven insights delivered directly to end users - Insights are personalized and tailored to achieve specific goals - Deliver only impactful, actionable insights, eliminating information overload - Experience a highly intuitive UI designed for an optimal user experience Deep Dive Analysis: - Receive deep insights for highly analytical questions - Connect data points from multiple sources for a comprehensive view - Ask follow-up questions to further interrogate AI-generated insights Ask Questions: -Get answers to simple questions from any internal data source -Seamlessly generate ad hoc reports in seconds

LayerNext Details
Languages Supported
English
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Product Description

LayerNext is an AI data platform that facilitates the exploration, curation, labeling, training & analysis of large-scale Computer Vision data. Data is the heart of your computer vision model. Get insights on how your data impacts model performance using a frictionless data engine designed for rapid iteration. Build performant computer vision models faster.


Seller Details
Year Founded
2021
HQ Location
San Francisco, CA
LinkedIn® Page
www.linkedin.com
Description

LayerNext is a data infrastructure platform for connecting best-in-class computer vision tools with a powerful data lake that unifies raw data, annotations, metadata, analytics and model predictions.


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Recent LayerNext Reviews

Joe C.
JC
Joe C.Enterprise (> 1000 emp.)
5.0 out of 5
"LayerNext for data lake"
LayerNext has been great to work with and quick to address issues and add features to tailor to our needs. We use LayerNext to organize image data ...
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LayerNext Media

LayerNext Demo - LayerNext Data Lake
A Data Lake for collecting, exploring, visualizing and searching all of your computer vision data. Connect all your cloud data storage and visualize data from anywhere using your browser. Quickly find the data you need by searching and filtering on metadata, labels and tags. Use a python SDK to i...
LayerNext Demo - LayerNext Annotation Studio
A powerful annotation tool that helps teams rapidly and accurately label image and video data for ML applications. Create pixel-perfect polygons or simple boxes annotations in a few clicks and add attribute-level labels to further classify objects using LayerNext’s attribute labeling tool. Save c...
LayerNext Demo - LayerNext Dataset Manager
Manage your labeled training datasets with version controls to avoid duplication and integrity issues. Capture data provenance and lineage to ensure the quality, integrity, and reliability of your data. Find and fill data gaps in your dataset by comparing performance of training experiments and v...
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