A software project management system used to plan, track and release great software with this lightweight and customizable system that integrates into any project management workflow. FogBugz is designed for software development teams and includes all the project management tools developers need straight out of the box. Users can: Track projects from start to finish - With tasks and subtasks for each case with required details and track them to ensure…
$62
per month
H2O.ai
Score6.4 out of 10
N/A
An open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides information retrieval on internal data, privately hosts LLMs, and secures data.
FogBugz has been a very useful tool to our organization, and much preferred over other options we reviewed, mainly JIRA. There are still some improvements needed, but with the fairly recent acquisition by DevFactory, we have a great deal of hope for what is in store given DevFactory's focus and transparency. It seems like both DevFactory and FogBugz customers are eager for substantial improvements on the front-end, but there is/was a great deal of backend housecleaning that definitely needed to take place first.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use. If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Tasks, Subtasks, and notes. All three of these areas were critical for our team. Tasks in Fogbugz were a bit easier to see than in more bug based software like Trello or JIRA
The entire screen is used to view a task or case. Clicking on a task or case will open up and take up the entire screen, aside from the sidebar nav columns. I like to see details and I think Fogbugz does this very well, using up as much digital real estate as possible.
Flowcharting in Fogbugz with Creately is nice - instead of getting an exterior flowchart software like Lucidchart, Creately works right in Fogbugz.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The simplicity of a single admin type user is not great because anyone who can create a job or client in the system, can also add and delete users. Content and User administrative rights should be separated.
There are ways to change the terminology/lexicon within the tool, but we are not able to get it to work even after reaching out to tech support. So we are forced to use the system terminology that doesn't match up to our company making training a bit difficult.
There is a subscribe function that you can opt into, there should be a way to add subscribers as you create a new task.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Saves time by quickly allowing Developers to make the necessary notes without getting bogged down in bloated UIs
Has allowed us to look back easily and see the exact code changes made for the exact Case to aid in decisions for current changes, increasing the certainty of the decided path, without regression
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
