Frequently Asked Questions

What, exactly, does Jaxon do?

Jaxon is a machine learning platform that autonomously labels text for training predictive models and classifiers.

How do we deploy/host data?

Jaxon is deployed in the form of a Docker stack and can be deployed on premises or in the cloud.

Does Jaxon support other languages?

Jaxon is generally language agnostic and learns from statistical patterns discovered in a corpus rather than from the actual language(s) contained in the corpus. Jaxon has not yet been certified for languages that use non-Roman characters or different morphology to English such as Arabic, Hebrew, or Chinese.

The most common languages Jaxon uses are the NLTK set of Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Portuguese, Russian, Spanish, Swedish, and Turkish.

How does Jaxon handle domain-specific phrases/terminology?

This is one of the main advantages of using Jaxon: all words are incorporated easily and efficiently. During the training phase, Jaxon ingests every word found in the training corpus, including any domain-specific language, slang, or common abbreviations and misspellings, and incorporates them into its label-generation model(s).

What’s Jaxon’s accuracy?

Training sets and their inherent accuracy are determined by the amount, quality, and breadth of data imported into Jaxon as it relates to the downstream model and use case. In general, for machine learning applications, more data leads to higher accuracy for model predictions.

So what do I use Jaxon labels for?

Machine Learning models, and Deep Learning models in particular, require training sets that contain millions to billions of examples, and it takes months and massive amounts of manpower to get them labeled. Jaxon replaces these costly, slow, error-prone, inconsistent human labelers by automating the data labeling process. Jaxon’s output feed into predictive models and classifiers as training data.

With Jaxon, machine learning applications make more accurate classifications and predictions.

What are some specific use cases for Jaxon?

Some use cases that have seen great success are:

  • Monitoring social media, news, and other sources in order to assess trends

  • Training natural language understanding (NLU) models to support chatbots and conversational AI systems

  • Triaging trouble tickets for IT and customer support

  • Real-time bidding and programmatic marketing

  • Document classification for governance and compliance