AutoML without compromises
April 30, 2020
AutoML without compromises
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Kortical
We are using the AutoML to create NLP models that are used to automate customer service enquiries, where we use the models to read the email and classify it. For those emails with a high confidence it will automatically respond but for those that they are not sure we use people to classify the email and help enrich the dataset.
Pros
- The NLP models results were much better than the ones that we did outside of the platform.
- It is really easy and quick to build a good model with a lot of the manual boring tasks all done automatically like one hot encoding, etc.
- Kortical shows the features and their importance for any model type as part of the platform which is great for understanding the models.
Cons
- It would be ideal to have Jupyter built into the platform, they say it is coming.
- Also while it is easy to use, at the start it would have been helpful to have more help guides.
- 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.
Do you think Kortical delivers good value for the price?
Yes
Are you happy with Kortical's feature set?
Yes
Did Kortical live up to sales and marketing promises?
Yes
Did implementation of Kortical go as expected?
Yes
Would you buy Kortical again?
Yes
Comments
Please log in to join the conversation