Parent page for the articles detailing the modules and services in Qwiery.


Highlights and features Workflows Asking Qwiery to send mail will trigger a workflow which captures the info necessary to send a mail. The workflow can be interrupted and will be saved as a task. The continue the workflow you can simply click on the task and Qwiery will pick up where you stopped. Workflows are […]

jQwiery: the JavaScript client library

The Qwiery JavaScript client library is an ajax wrapper to easily call the Qwiery API. Besides giving access to all of the public facing Qwiery methods it also contains various utilities to help you build JavaScript applications on top of Qwiery. The documentation below divides the API in broad sections which combine related methods. You […]

Scaling up Qwiery

Qwiery was not build with scalability and tight security in mind. It was build for simplicity and ease of use. If you wish to go hyperbolic then the following notes will be helpful. File based. The way QTL and other data is stored in flat JSON files is obviously not ideal. Take MongoDB, DocumentDB, CouchDB or any […]

Psychological profile

The psychological profile of a user is a service in Qwiery which allows: to tune the answers returned in function of a psychological vector (psy-vector) to find similarities between users and through this to create broad categories of users with similar brains (i.e. semantic networks with similar characteristics) . The psychological profile really is just a vector which […]

Constructive vs. learned

If you consider creating a conversational agent there are mainly two options: a constructive approach where the agent builds up an answer based on rules, hard-coded switches and domain-specific input. a learned approach where the agent is taught to talk (much like a child) based on a massive amount of data and repetitive fine-tuning. This […]

Qwiery Template Language

Qwiery Template Language When the Qwiery messaging pipeline has found one or more answers matching a request it processes a template which contains the answer. The answer is usually not just a simple line of text but can be any combination of the following: requests to fetch data stored in the knowledge graphs; personal data […]


Cognitive appraisal theories assume that an emotion is the result of a cognitive process. A person assesses at all times what is happening in the world around him or her. These events are evaluated in terms of how relevant and conducive these are to that person’s and other persons’ “goals”. Emotions emerges from this process and it’s clear from the […]

The oracle module

The oracle module deals with mapping the input to a parametrized sentence and executing the instructions (the QTL template) upon finding a match. It’s loosely based on AIML and similar constructive approaches to natural language interpretations. Its amazingly simple yet effective, especially in a NodeJS implementation. The speed with which one can alter templates and template […]

Language Manual

You can ask Qwiery anything you like but there are also specific commands which instruct Qwiery to handle a question in a particular way. Below is a summary of these commands. There are in general multiple ways to get the same result and Qwiery knows quite a bit about synonyms and equivalent formulations, so the […]

The semantic network

The jQwiery library is a JavaScript client library which wraps the graph API. Input creates knowledge and knowledge creates answers. This interaction is embodied in the interplay between the oracle module (the NLP if you prefer) and the semantic network (aka graph database or graphdb). This semantic network is a labelled directed graph which in […]