North Side develops a full-coverage semantic frame system. We consider syntax and arguments to extract meaning - not just the probability of a lemma occurring, as in ML. See FrameNet for basic semantic frame concepts. Semantic frames are used to formalize our large database of knowledge about everyday life, and power high-precision search


A knowledge-based conversation pipeline, able to converse on any topic of everyday life. (Click Show More for details)

Situated language understanding (resolve references to 3D objects and spatial relations), used in our Say it, See it!™ solution and videogames.

Our Jimmy’s World videogame leverages our pipeline and a vast database of knowledge about everyday life.

In 2015, our Bot Colony videogame pioneered text-based 3D animation – the ability to control virtual character actions in English. Our 3D capable NLU powers our Say It, See It!™ product.

The robustness of our NLU enabled us to support speech-based, transactional financial applications with the same pipeline used for videogames.

The best of both worlds: Coverage and Precision

Nowadays, everyone relies on Machine Learning (ML) to ensure coverage. Our knowledge-based approach increases precision, giving deterministic answers when possible.

  • ‣ Makes sense of more user utterances. Deals better with UMM (unsupported, misunderstood, mismatched utterances).

  • ‣ Extracts ALL the entities and relations, modality and negation from utterances.

  • ‣ Handles more out of turn utterances.

  • ‣ Handles more dialogue acts including user clarification requests when answering.

  • ‣ Co-references resolves pronouns, nouns, adverbials.

  • ‣ Uses context to resolve ellipsis (missing verbs, nouns, etc) and to do co-reference resolution.

  • ‣ Handles complex dialogue graphs, where the next prompt depends on the user's answer to a previous question.

North Side Natural Language Understanding (NLU) pipeline

Go Conversational!
Add conversation using voice or typing to your current applications. We'll handle the conversation and call your API's from our Conversation Server.

Existing Interface

This is what your application looks like today.

Conversational Interface

Here's how you can support conversational access in addition to GUI based access.


1. A Virtual Robot-Human Development framework