V7 Darwin Reviews & Product Details

Video annotation is very easy and its predictive labeling tool is really easy to use. We are able to annotate massive datasets to train our ML models. Review collected by and hosted on G2.com.

Ease of use, very easy to quickly annotate images and videos Review collected by and hosted on G2.com.

Darwinbox is an excellent all-in-one HRMS that helped me manage the entire employee lifecycle seamlessly. I found it particularly useful for onboarding, performance management, time and attendance tracking, and payroll processing. The platform made it easier to centralize employee data, automate HR workflows, and ensure transparency across processes. I appreciated how it reduced manual work and improved accuracy in payroll and performance evaluations. I was using this software on a regular basis, and I found it very useful Review collected by and hosted on G2.com.

While Darwinbox is robust, it can sometimes feel slightly complex to navigate, especially when dealing with advanced features. Certain modules could be more intuitive and user-friendly, as new users may require extra time to adapt. Additionally, occasional lag in system responsiveness was noticeable during peak usage. Review collected by and hosted on G2.com.

Spreadsheet tech hasn't really changed since 1979 when VisiCalc was introduced with support for formulae in spreadshset cells. V7 has changed that - having an LLM running inside each cell and allowing cells to contain rich content like handwritten documents or scanned paperwork is a huge game changer! Review collected by and hosted on G2.com.

I only dislike that they didn't invent this 20 years ago Review collected by and hosted on G2.com.

It's easy to use as a software and navigation is easily graspable Review collected by and hosted on G2.com.

The software doesn't allow a person to retract a submission of an annotation Review collected by and hosted on G2.com.

It has automatic annotation tool like SAM, and it allows you to merge the polygons, which I find very handy. Review collected by and hosted on G2.com.

I would like to see a feature that allows me to split an existing polygon into multiple new polygons. Also, V7 does not allow file/folder manipulation on their website (like the operations supported by Google drive), which I find inconvenient. Review collected by and hosted on G2.com.

Exporting the documents and annotating and labeling them. All its functionalities and excellent and up to our requirements. The arrangement of its UI and tool is so exciting and intuitive for all users. No confusion while selecting the tool for your desired work. Its automotive features are unique, helping you make your job done more efficiently and in less time with more accuracy. Enables you to manage all your teamwork in one place. Supports multiple processes and operations. Review collected by and hosted on G2.com.

Finding or filtering the documents from the mass data is quite tricky sometimes. Its sorting or filtering feature does not provide accurate results or lags when there are more files. Review collected by and hosted on G2.com.

One of the best things about this tool is its user-friendly data annotation feature. Thanks to the auto-annotation features, I could label my dataset with ease, even for the most complex objects. The tool even allows for the annotation of polygon shapes, which was a massive help for me. Review collected by and hosted on G2.com.

I want more export options for my dataset, such that it supports a wide range of formats. I encountered this issue with the instance segmentation format for YOLO. Moreover, I would prefer the dataset hosted directly in the colab notebook, just like Roboflow datasets can be accessed. Review collected by and hosted on G2.com.

After several tries trying out various tools to annotate my data, I stumbled on V7 and immediately realised that V7 had exactly what I needed. My datasets have a lot of similar images and V7's copy annotations feature helps save a ton of time and allows me to work through my datasets swiftly. Furthermore, I never knew I needed the image manipulation options that V7 provides until I used it. It allowed me to completely isolate my items from the noise for more accurate annotations.

Also, V7's UI looks amazing and is incredibly simple to use. There's no learning curve. Review collected by and hosted on G2.com.

No complaints so far, as I haven't encountered any features that I dislike. Everything is straightforward to use, and I haven't encountered any bugs while using V7 either. Review collected by and hosted on G2.com.

I am using v7 labs AI tool for my research on Computer Vision. Especially for annotating data and training CV models. I must say that V7 is the most innovative and amazing tool in this category. I am fascinated by this platform's features, from annotating datasets to training and deploying. It's really wonderful to have all these managed wonderful features. The data annotation tool on the platform is extremely powerful, well-featured, and easy to use. I can now label my dataset in a few clicks, even the most complex objects with amazing auto-annotation features, even for polygon shapes. I also tried 3d annotation of objects in the image using a cuboid tool that it provides, and it's fantastic. I really recommend v7 labs to everyone who is Computer Vision Pro and wants to annotate and build efficient and accurate computer vision models and manage the whole pipeline/workflow. Thank you, v7 labs team for such a great platform. Review collected by and hosted on G2.com.

There is nothing that I dislike so far. All features are really amazing. Review collected by and hosted on G2.com.

Web-based annotation tools including model-assisted polygon annotation are among the best I have tried. I appreciate that they provide the option of hosting models for companies getting started with this technology. Pricing seems fair for what they are providing. Review collected by and hosted on G2.com.

In my first week using the service I have had no problems with it. I have given them a few recommendations that might streamline the navigation of datasets, and that feedback was welcome and encouraged. Review collected by and hosted on G2.com.