Real-time context and insight
Have you ever sat in a meeting and someone makes a reference to something you have no idea about? We have and we've felt the pain of the awkward smile and head nod while jotting a note down to Google "CPM" when you left the meeting. Every day, we encounter in meetings and conversations references to emails, upcoming meetings, documents, past conversations, and general topics and sometimes we either can't remember or just don't know the reference. We built a tool to help people gain more context and intelligence around a conversation in an unobtrusive and seamless manner.
ListeningPost is a real-time engine that listens via your computer or tablet (Android) microphone and then picks out terms, phrases, and topics that you may want more context around. When you are logged in, ListeningPost can find matching emails, past conversations, and documents that you might want to reference and delivers them into a stream that is updated live. Dig deeper and get more information on a topic by simply selecting the captured phrase. ListeningPost also goes beyond your personal accounts to search the web so you never get caught off guard not knowing what "YOLO" means.
The Target Audience
ListeningPost is a great tool for people who attend meetings and helps keep attendees focused on the conversation without the need to constantly type and search which creates a distraction. It's also a great tool for people who may not be as familiar with cultural references or the latest news/topics and want to better understand what other people are trying to communicate when they speak. Whether in a business meeting or when you're watching Family Guy, ListeningPost is a great tool to have as a companion.
What We're Proud Of
We spent a lot of time refining our method for figuring out what phrases/words are important and what's not and we think we've gotten the engine to a place we are excited about. There is opportunity to further improve the engine through more NLP techniques and we can expect the technology to improve as speech-to-text engines become more accurate in the future.