JazzHR is an ATS and recruiting software. JazzHR aims to replace antiquated hiring processes like email and spreadsheets with an intuitive applicant tracking system that helps recruiters and hiring managers build a scalable and effective recruiting process.
$99
per month
Kortical
Score10 out of 10
Enterprise companies (1,001+ employees)
Kortical is an end to end AI as a Service (AIaaS) platform designed to accelerate the creation, iteration, explanation and deployment of world-class machine learning models. The vendor describes the key benefits of Kortical is AutoML that writes custom machine learning solutions from the ground up in code. Getting hands-on with the code is optional but being able to edit code it makes it easy to get the best of data scientists and AutoML, while also getting the benefits of full…
Since it allows you to tag candidates based on their level of talent or potential utility to the company, it is best used to identify the best prospects in large operations, such as multi-franchise oriented businesses that cover all kinds of sales. It can be used to make periodic assessments of the level of employee growth in certain departments, and based on the results let us know if certain employees would do better working in another type of area, so that the overall work operations are more uniform. JazzHR could excel in departments that use a high level of reporting, as its administrative tools provide high content reports with statistics on the performance of each employee or candidate at different levels.
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
Kortical is really widely applicable to many use cases, although it doesn't handle images or video it is great to help you build really great ML models without needing to plan ahead what you are going to try, you let the platform build you the best model. It is suited to beginner and more advanced data scientists as you can edit the code to narrow the search space which makes model creation more you build it without AutoML. Hosting the model behind an API that is ready to go is great as it saves so much time vs doing that dev work 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
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
It worked well for the majority of our needs and is still in use even though I've left the company. The Resumator was an interim solution until we found a system that integrated with all our other internal systems. However, we ended up staying with it because of ease of use
It's not a 10 due to the eTemplates. If those were less time-consuming to set up and if some common forms were available to select from already set up, then I would give it a 10.
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
Each person I've spoken to have been helpful, positive and encouraging. Once you begin using JazzHR, they have intervals in which they reach out to you to see how you're doing or if you have any questions. When you're setting up, they review what you've done and offer praise as well as suggestions on how to make it work better for you. They offer webinars and online training videos to walk you through every process.
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
Their support is great as we use Slack and we have our own channel and they always respond really quickly. Data Science support is available to help unblock you as well as dev support as we're setting up the data feeds. It would be great if there were more FAQ or self-help guides in the platform but the personal touch is also really appreciated and probably gets us there quicker anyway.
A solutions consultant walked me through each step. It was easy. As I progressed in setting things up, their support contacted me to set a time to walk through any possible issues and make suggestions on a better way to set it up. At any time, if I had a question, they were available and there are also training documents and videos available.
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 Greenhouse and Lever at least seemed to have great products and great teams; they simply weren't worth 2-5X the cost for us. Now, let's be clear - a platform that helps you hire the best people is a certainly worth 2-5X (or perhaps 10X) the cost. However, for most small and medium businesses, the three platforms are very similar. Once you have ~100s of different positions or ~100,000 applicants, then a more advanced ATS could be worth the cost. For us, Jazz is excellent. We have about 8 types of roles and 250 employees, and we see the Jazz system working very well for us even as we grow to 1,000+ employees.
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
ROI is great as what we would spend on compute we get the AutoML for essentially the same price so it is cost neutral as Kortical comes with compute built-in.
The results mean that we can automate so much more than our previous model so that is key to the positive ROI.
The platform auto trains new models and lets us know when there is a better model so it has saved a lot of time so we can focus on new business problems to solve with ML.
