Our Approach

Off-the-shelf deep learning models require millions of documents to be manually annotated - a slow approach that’s impossible in today's workplace. Corporate documentation is simply too sparse for big data techniques. That’s why we’ve employed a blended method. We leverage the depth of free text retrieval and the accuracy of deep natural language understanding to provide real-time, succinct, and accurate responses.

Kiite Natural Language Processing, How Kiite uses NLP

Natural Language Processing

Thanks to search engines, online chat, and social media, we’ve grown accustomed to accessing critical information at lightning-speeds. Yet, in the workplace, internal software systems and the processes they support are often outdated and kludgy, which can slow your people down. That’s why we’ve developed Kiite, the world’s first Intelligent Sales Coach, using Machine Learning (ML) and Natural Language Processing (NLP) technologies. With Kiite’s intelligence, turn stale processes and locked knowledge into automatic coaching.

Our Technology

AI Training

We take a supervised learning approach. That’s why Kiite learns from your real data sources. Over time, Kiite continues to learn by analyzing real-time user inputs through chat. Because Kiite’s using your data to learn, it’s your company’s knowledgeable expert from Day One.

AI Technology

Using AI components, Kiite takes complex real-time data -user history and behaviour, real-time questions, confidence score rankings, user feedback- to train its models in real-time.

Security and Data Portability

We abide by the highest security standards for data management and have no risk of cross-contamination between customer accounts. We uphold our commitment to customers that data entered into Kiite is theirs to take with them.


Answers to questions are friendly, on-point, and delivered in bite-size chunks of text. By analyzing user behaviour and identifying trends, Kiite recommends helpful information to individuals, when those individuals might need it.


Kiite’s accuracy is always improving. Responses and proactive recommendations become more tailored and more helpful as the software adapts to individual user inputs.