We create human-like
natural language, AI - assisted Chatbots
Thanks to the Panel you'll be able to train the Chatbot in order to obtain data necessary for comprehensive customer service.
Chatbot training phases:
We work with companies from various industries, as well as with local government institutions.
What benefits can a chatbot bring to your business?
Chatbots work as a part of your Team. They automate sales and customer service processes, work tirelessly around the clock and bring tremendous savings to businesses that utilize them.
per month cost of owning a fully- functional chatbot
once set up, chatbots work 24/7 around the clock, giving you 100% uptime.
Teach it once, it will remember forever. Chatbots retain 100% of the knowledge learned.
Our chatbots don’t have a limit on how many customers they can handle, even simultanetously. Custmer service operations never stop
What makes us different?
Our customers need innovative solutions, which is why we create Chatbots for various companies and institutions.
AIForce1 is a Team of engineers, managers and experts in the field of artificial intelligence, natural language processing and artificial neural networks.
Developer and AI project leader.
Builds knowledge base structures that provide the basis for the analysis of Chatbot's behavior
Responsible for NLP processing and neural network classifiers.
Manages contact with our Clients and Business Partners.
Front-end Trainer’s Panel developer
Builds training models with the use of AI
Responsible for UX and UI of the Trainer’s Panel application.
Coordinates projects related to finances and deployments.
Frequently Asked Questions
Aritificial Intelligence (AI) is a term coined in 1956 by John McCarthy to distinguish the then fledgling computer science projects focused on creating systems that simulate the behavior of intelligent organisms. Probably John didn’t even imagine that his term would grow to become
one of the greatest buzzwords at the beginning of the 21st century.
Why artificial? Isn’t intelligence just intelligence? We use the term ‘artificial’, because it was created in an engineering process, rather than through a natural one.
In turn, why a buzzword? Because, as a field of science, it is such a broad concept that it contains hundreds, if not thousands of specializations, which ultimately led to the use of the term ‘artificial intelligence’ as the default when defining even questionable ‘intelligent’ products.
Unfortunately, marketers love to use „A.I.” on just about any project.
Since the beginning of the 80’s, for more than twenty years there has been the so-called „AI
Winter” – which can be described as a lack of momentum in AI development and utilization. This
„winter” was caused by relatively primitive and weak hardware at the time, combined with a
general lack of valuable data to be processed.
It wasn’t until the turn of the century that fast graphics cards, multi-terabyte drives, multi-core
processors and, of course, the Internet brought tremendous changes to the AI landscape. Huge
amounts of data coming from social media, massive distributed systems, online shops, thematic
portals, combined with the progress not only of the hardware but also of the software, led to an
unprecedented situation: the emergence of the Big Data movement.
For the first time in history, we have a huge amount of data that we can process and analyze
almost in real time. This breakthrough led to the gradual melting of the glacier surrounding
artificial intelligence topics, especially in the context of natural text, image, sound recognition
and, of course, the stock market behavior. Thanks to this thaw, we are now able to use all these
sets of data in machine learning.
Overall, machine learning is a process of preparing large amounts of training data, which will
then be fed to our learning system. The most popular and also one of the most effective
machine learning processes is ‘deep learning’ based on neural networks. This process is
responsible, among other things, for the AlphaGo machine defeating the 50 best players in
Go, including the master of all time, Lee Sedol. At the moment, we are able to successfully
use deep learning for most of the statistical decision-making tasks.
Of course, machine learning is not only deep learning. There are at least several dozen, if not
several hundred types of neural networks suitably adapted to specific tasks, such as face
recognition, cancer cell detection, optimal vehicle route planning and so on. Regardless of the
software used, most of the solutions focus on training processes or behaviors, rather than on
Information, usually flowing from large databases through the learning systems goes to
isolated knowledge bases.
Natural Language Processing (NLP) and Natural Language Understanding (NLU) is quite a challenge. Nonetheless, it’s at the core of our interests and a founding pillar of our business. Using proprietary solutions, external tools and free software, we work hard to make sure that you will be able to train our systems intelligently, using natural, human-like language. Of course, this includes figuring out the complexity and fully supporting Polish language as well!It is worth mentioning that in order to recognize and understand natural language, we have toovercome a whole spectrum of problems: from grammatical and linguistic, to technological andpsychological. But don’t worry – we take care of all of that for you. When using our solutions youcan relax and work with our systems in natural language – just as you would with a human being.
The last technological challenge when implementing smart solutions, especially those with high (national or global) availability, is the infrastructure autonomy. From a business perspective, regardless of whether there are 10 or 100,000 queries at any given moment, the systems should always be able to handle all of them, without delay.
This is why our services scale automatically according to demand. By using cloud technology, especially serverless technology, our systems and robots will always remain online, regardless of how many customers they serve.
As a direct result of our extensive work on knowledge bases, machine learning, natural text recognition and autonomous infrastructure, our chatbots are incredibly friendly and life-like in
Our virtual assistants and salesbots communicate with your clients in natural language, learn under your supervision and let you directly control their autonomy in handling cases.
The Training Panel allows you to have a full insight into the learning process and information processing tasks. Moreover, you can integrate our assistants with popular communicators, such
as Facebook Messenger, LiveChat, Slack or E-mail.
Would you like our virtual assistants to help you run your business? In a few sentences let us know about your needs and we will surely find the perfect solution for you.