datajoi is a browser-based data analytics and narrative tool that lets users query, visualize, and interpret data without needing to write SQL. It aims to make data more accessible by turning raw tables into interactive “stories” you can explore directly in a browser.

• As described on their Medium page, datajoi acts in part as a Chrome extension SQL client, redefining how you “experience data” in your browser. Medium

• It supports creating data products, embedding generative-AI, and layering context + governance on top of your datasets. Medium

• On the “Support” page, datajoi describes itself as helping with “technical and non-technical help,” handling payments & subscriptions, etc. datajoi.com

A DataStory (or “DataStory™” in your branding) is datajoi’s way of packaging an insight as a narrative. Unlike static dashboards or charts, a DataStory:

• Combines visuals and explanations to tell what is happening in your data

• Adds context and interpretation — not only showing numbers but helping you understand the “why”

• Is interactive — users can often dig deeper, ask follow-ups, or explore related segments

In short: a DataStory is your insight translated into a narrative that people (technical or nontechnical) can understand and act on.

The DataEngine is the analytical “brain” under the hood:

• You ask questions in natural language; the engine interprets them and generates queries (e.g. SQL) behind the scenes.

• It chooses appropriate visualizations (charts, tables, etc.) automatically, mapping data to forms that best reveal patterns.

• It manages data lineage, versioning, dependencies, and governance — tracking how data flows, who owns what, and maintaining integrity.

• It supports workflows: once you set metrics or views, the engine can continuously monitor, alert, share, or act on changes.

• It is designed to use “small AI models on small data” (i.e. contextually tailored models) rather than generic large models.

So, the DataEngine transforms your data + questions into stories, while retaining traceability and governance.

DataAgents are autonomous or semi-autonomous helpers embedded in datajoi’s platform. Their role is to help scale analytics by handling routine tasks, anticipating insights, and executing workflows.

Practically speaking, a DataAgent might:

• Monitor data changes and trigger relevant analyses

• Generate suggested views or metrics

• Automate pipelines, transform data, or issue alerts

• Act as “AI assistants” to your data team, proactively surfacing value

They are the active layer in the system — not just showing insights, but helping do them.

Here are all the available support and contact channels for datajoi (as of current public info): support@datajoi.com.