Objective
In the digital age the online channel is very important for lead generation: that is why chat-bots and Virtual Digital Assistants can become one of the most important channels. Chat-bots and VDAs are platforms that simulate a real conversation with users in written or spoken form by using artificial intelligence. Most of the available chat-bot platforms are limited in text, written and voice recognition. If they are not supported by AI, they are not able to identify the context and to remember conversations. Additionally, most platforms support a limited number of conversation domains. Platforms supporting custom domains, coming with high additional costs, require a lot of training data like chat logs, which are often not present or not sufficient. OmniBot is an Artificial Intelligence and Natural Language Processing Bot platform for designing and integrating Virtual Assistants. Through the use of the OmniBot platform components, OEMs and end customers can quickly start with simple limited task bots for initial functional deployments and evolve to more complex, conversational, voice enabled multi-task bots and virtual assistance. OmniBot provides a complete SDK providing all documentation, tools, templates and libraries for multiple platforms required for building and integrating scalable enterprise ready virtual assistants: this speeds up the bot integration process and reduces costs and complexity while increasing productivity and quality.
OmniBot seeks funding to conduct a feasibility study to prove technical and commercial viability, conducting an analytical exercise to position the product. The objective is to test the economic viability of the platform among a larger pool of potential clients (user -acceptance), and to assess if the chosen commercialization approach will be conducive of the projected growth on the European level.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesdata sciencenatural language processing
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
26129 OLDENBURG
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.