At TrollWall, we didn’t just stumble upon the idea of social media content moderation; we were drawn to it, each of us armed with unique experiences and skills that made us capable and compelled to act.

We're a team of tech-savvy enthusiasts dedicated to driving change in social communication. Our expertise lies in harnessing cutting-edge AI technologies for a purpose—to revolutionize content moderation and empower brands in the digital sphere.

The Challenge

ATL is a trusted partner I worked with in the past, and I know I can rely on them to deliver the best possible quality. Also, since we are a startup company, we need a partner that can understand our dynamically changing needs and help us be able to quickly scale up. The main challenge we were facing was how to scale up, how to include the languages nobody in the company speaks into our portfolio, and how to ensure that the product we offer in each language is of good quality. Also, we wanted to save some time on recruiting and managing groups of annotators for various languages, since we know how cumbersome of a process this can be.

It feels great to see that both ATL and ourselves seem to learn something from the cooperation and I feel confident that even if neither of us is sure how to solve a particular problem, we will discuss it in a very friendly and supportive manner, and we’ll find a way to make it work. That’s what I call a true partnership!

The Solution

ATL provided us with teams of annotators and linguists to support our language model creation and training. ATL turned out to be very flexible, coming up with solutions that matched our (initially very limited) budget, our quality requirements and were able to turn things around faster when we needed that. The contact I have with the Project Managers at ATL is excellent, I feel confident reaching out to them with any piece of feedback, any concern, and any word of appreciation. I feel I can openly admit that I am not sure about something, and I won’t be criticized for that – just the opposite, the team at ATL will do their best to support us.

The Result

Thanks to the cooperation with ATL, TrollWall was able to build and launch entirely new language models. These models have been built on the data delivered exclusively by ATL, so I can safely say that they wouldn’t exist if it wasn’t for ATL work. Additionally, ATL has significantly contributed to the creation and optimization of our existing language models, by delivering several datasets that have been used for the re-training of existing models.

Currently, ATL supports us with training and optimization of 5 language models: Czech, German, English, Polish and Romanian.

This allows TrollWall to expand internationally and to meet our internal KPIs. We have ambitious goals for this year, and I see ATL as a key partner in making these plans reality for us. That will certainly include: continued work on the language data for the existing models, providing complete datasets for the purpose of the implementation of new languages, as well as supporting TrollWall AI with any other linguistic tasks we may need.

Building a new language model is a complex effort from several different teams, and scaling up quickly would be much more difficult. Using high-quality annotated linguistic data is crucial in the process and ATL takes over a big part of our work on it. Instead of managing the freelance annotation teams for all languages internally, we can free up our hands by outsourcing this effort to ATL. Without ATL’s support, we’d probably need to employ 1-2 coordinators who could deal with workload management, hiring, training, and managing the annotation teams – that would be quite a significant cost for a startup company like TrollWall. So far, ATL has delivered over 200 000 labels which we use in the process of language model training. We see good accuracy ratio for the newly created models and the good performance of the model proves that the data annotated by ATL was of high quality.

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