A vision of the future of the translation industry, based on SmartCAT CEO Ivan Smolnikov’s award-winning speech at TAUS Innovation Contest 2016 in Portland, OR.
Our vision of the future of the translation industry is based on three principles:
- Advanced collaboration is the key to effectively manage large-scale and urgent projects,
- Technology should help translators and project managers simplify time-consuming routines and increase productivity, with artificial intelligence playing a large part in setting up teams and managing their performance,
- High-value and SLA-compliant linguists are the strongest success drivers in translation projects, and technology must facilitate identifying and reinforcing the choice of such professionals.
It all starts with our key belief that selling licenses for CAT software is an atavism of our industry. We believe that no one should have to continuously count licenses in a business where almost all key value producers are freelancers and teams are highly dynamic and dependent on the projects you will have tomorrow.
Relying on the number of licenses limits the efficiency of translation processes in a company and restricts its growth potential and scalability. Finally, the low technology penetration and the need to sew together multiple tools to have a more or less seamless and efficient workflow are the major factors slowing down the evolution of individual companies and the industry as a whole.
Then, what is the true value that a tech vendor should bring to a customer? We believe that it lies in technologies for building and managing the supply chain. Moving towards this goal, we introduced what we call “advanced collaboration.” The following video shows how it simplifies the management of large-scale and urgent projects.
You can see several people working on the same document at the same time. They can understand the context, communicate right on the platform and see each other’s contributions in real time. But they can’t erase one another’s work thanks to a smart locking mechanism. The same is true for the editor, who can start working almost simultaneously with the translator, but can’t start editing before the translator completes a segment.
Similarly, the editor and the translator can work together and communicate within the same user interface. The editor can correct and consult the translator along the way and not after the project is completed. Thus they are able to finish their respective assignments almost at once. Both the speed and the quality go up.
The big difference between this and what you have probably tried so far is that there is no need to split the text into parts. You can invite as many translators and editors as you need to work on one document, and everyone will see the whole of it. (And, of course, they can reuse TMs and terminology in real time.)
The experience is somewhat similar to Google Docs, except that they can’t interfere with each other’s work accidentally. This is a unique feature for the market, and it is very useful for projects involving the work of many linguists.
In order to meet the needs of tomorrow we are bringing collaboration to new heights.
By introducing chatbots, we aim to boost project managers’ productivity even further and provide them with full control over their projects from a smartphone and their usual messenger.
Chatbots allow PMs to chat with anyone in a project and get automatic reports on its status. Here is a video demonstrating this user experience:
This is a simple case of how this technology helps improve project managers’ work. Sometimes (pretty often, actually), managers need to check the project status on the go and make some actions afterwards. Usually this takes getting back to the computer. Instead, now the manager can just send a query to the SmartCAT bot. The bot displays the list of recent projects. The manager chooses the one of interest, and the bot returns its progress data.
Now, let’s say the manager sees a possible issue with an editor’s performance. She can then write him a private message using the same bot. The editor is sitting by his desktop and receives this message within the SmartCAT interface. He answers through the desktop chat, and the manager reads the answer on her mobile device.
We have many surprises in the future development of SmartCAT. Bots will be getting smarter, powered by artificial intelligence. Besides mere reporting shown above, they will learn to actually think for the project manager. By analyzing real-time performance of translators, they will make actionable suggestions to add or remove project contributors. They will also analyze quality in real time and recommend a replacement if someone performs below expectations. In doing so, they will choose among those with relevant domain knowledge (e.g., based on analyzing the source content).
This will bring project managers’ productivity to a new level — after all, they are one of the most valuable forces in translation, along with translators.
Let’s take a look at the future:
Here’s how it goes: The bot sends an alert notifying the project manager that translator Jessica is working too slowly or that the quality of her work is below expectations. It asks if the manager wants to chat with Jessica or bring another translator to the project.
The manager clicks Add, and gets top three candidates for the job. All of them specialize in the domain, and two of them have successfully worked for this particular customer. She looks through their brief profiles and selects one. Done — the translator has just been assigned.
Now, the bot not only tells you about an issue, but also suggests a solution.
Our ongoing and never-ending pursuit is building a platform that enables effective cooperation between customers, project managers, and translators. Today, all of them spend far too much time struggling with the routine.
While technologies should help, they often complicate things even more. We are here to make a change and turn technology into an assistant, not burden, for all market participants.
We trust that the future of translation lies in human talent — empowered by the right technology.
Selling CAT licenses is boring — we’re up to something much more exciting.
Ivan Smolnikov is the CEO and founder of SmartCAT.ai. He has a solid track record in the translation industry with a strong focus on linguistic technology development. He started his first translation business in 2004 and built it into one of the top 50 global LSPs, known today as ABBYY LS, where he worked as the CEO until 2015.
In 2013 Ivan co-founded SmartCAT, now a completely independent, venture-backed, and fast-growing business with headquarters in California, 2 operational offices in Europe, and a team of 80+ people.