What is our primary use case?
From May or June this year, we've been using its API to automate translations.
The main use case at work was managing a team of translators. To speed up their work, they would input text into DeepL for a quick check and fix. Now, with the API, our systems are connected, and translations are done automatically. We still proofread them afterward.
How has it helped my organization?
It makes our work faster and more efficient, freeing up time for more complex tasks. The basic translation is done by DeepL, allowing us to focus on other details. The main improvement is in speed and efficiency.
What is most valuable?
The quality of the translation is high, understanding nuances and context well. Another feature I like, available in the pro version, is the glossary. It allows for storing specific word translations, ensuring consistency.
DeepL Translator has a good option, which is also good. When you have the app on your phone, you can scan a text, and it automatically translates the text, which I find pretty cool.
What needs improvement?
We translate a lot of content into Spanish. DeepL is set up for other languages like English and maybe others with different country variations, like British English or American English. With Spanish, there's only a general Spanish. However, Spanish can be very different depending on the country.
My impression of DeepL is that they try to have standard, plain Spanish. But I would like the option of choosing different Spanish because Spanish from Spain, especially, is quite different from Latin American Spanish.
In future releases, I would like to see an option for saving previous translations. For example, other translators, like Google Translate, save your past searches, and that might be something useful.
For how long have I used the solution?
I've used it privately for a few years. I live in Germany, but I'm Colombian. So, for tasks like writing emails in German or ensuring correct communication, I use it a lot.
Professionally, I've used it with my teams of translators since around July or June last year.
What do I think about the stability of the solution?
It has been a stable solution so far.
What do I think about the scalability of the solution?
There are only a couple of users using this solution because the organization went through a restructuring process. So, previously it used to be around 30 end-users using this solution.
How was the initial setup?
The initial setup was simple enough.
What about the implementation team?
The tech team of the company deployed the solution.
What was our ROI?
We calculate ROI, like how much time it would save later. So it would cut the work, like the amount of time they needed to produce the translation. It would cut it from maybe four or five hours to maybe half, so 50% cut in the time of the translation.
What's my experience with pricing, setup cost, and licensing?
The solution offers a fair price. If you're a casual user, you might not want to pay for it, so it's good to have the free version. The free version is good enough for what a casual user would need. But definitely, the prices are fair for this tool.
Which other solutions did I evaluate?
The glossary is very, very useful for a translator. In general, there's a paid version, but the free version is quite good.
The translations tend to be very, very accurate. So, those are the main pros. You do really notice the quality of the work. You can't trust it 100% because you're not giving it enough context sometimes.
But in general, you can trust that it will always do an okay translation.
In terms of cons, the fact that you can't really personalize it that much or give it as much input. So you can choose between a formal and an informal tone, but that's it. You don't have as many options for a tone or the sort of translation you want done.
If I'm thinking of more professional translation tools because DeepL is kind of in the middle. Like, it's for an everyday user. It can also be used via a translator.
But if I compare it with more professional translation tools, it doesn't have a few features like the options of storing more specific sentences or storing certain fragments and comparing the original text with the translation and just making subtle changes, that you can store in memory to then use again in a different document.
What other advice do I have?
It's a great tool. I would recommend implementing it for many cases, but also do not always trust a hundred percent of the translation and just keep an eye on things, like double-checking certain translations. The human eye is always important.
I like this solution. I would recommend it. Overall, I would rate the solution an eight out of ten.
Which deployment model are you using for this solution?
Public Cloud