The chatbot that gathers all your company’s knowledge
In the face of employee turnover and geographical dispersion, the CEO of Zapiens, Daniel Suárez, has developed a robot that stores all of a company’s internal knowledge so that it is not lost and workers can learn from it.
Over recent years, whenever we want to find something out the first thing we do is ask our great friend Google, that search engine that always seems to have the answer for everything. But what happens when it’s a work-related question that only your colleagues could know? To go round asking people one by one doesn’t seem very efficient. What if the colleague who might know works from China and you don’t know them? And if they’ve already left the company?
After having worked for several retail companies, this start-up identified similar problems which came as a result of employee and product turnover and geographical dispersion. The CEO of Asturias start-up Zapiens, Daniel Suárez, decided to create a “corporate brain” that would gather internal knowledge at every company. “In one single work session, we noticed that 20 people could come up with 400 different questions. We realised we could gather all that information through an app so that the entire corporation could access it”, explains Suárez.
They didn’t pick their company name randomly: Zapiens comes from sapiens, and so does the name of the machine learning robot that they have created: Zap. “The chatbot learns from the employees, who get Q&A or video training on their mobile. Their answers allow the system to learn about who they are, what they know and what their areas of expertise are”, says Suárez. In case altruism and love of learning aren’t enough, the app uses gamification techniques for incentivising its use.
Once training is complete and the robot has gained all that knowledge and learnt about all the employees, it can be used as a regular search engine: workers can ask questions and the machine predicts who in the company might have the answer. “Zap is different from other robots because he can answer ‘I don’t know’ and take the question to the relevant expert”, points out Suárez.
Behind Zap, the robot that wants to become just another employee you can reach out to in case of emergency, there is artificial intelligence, machine learning and semantic analysis. There are more than enough data that prove how much companies improve through this system: according to Suárez, data transfers have increased by 80% when compared to training programmes, which have also become more frequent, with a 70% frequency rate that used to be just 10%.
Knowledge is value. That is why Zapiens’s ultimate goal, besides preserving existing knowledge within companies, is to become part of something bigger: some kind of global encyclopaedia to keep all the knowledge there is in the world. So far, Zap is already doing his bit.