Key concepts

Conversation data and business data

Dimension Labs works with two kinds of data, and treats them differently.

	Conversation data	Business data
What it is	Chats, calls, tickets, reviews, survey answers, social posts: anything a person wrote or said	Revenue, orders, renewals, accounts, locations, usage: rows and columns
Where it goes	Data Sources > Unstructured data	Data Sources > Structured data
How it gets in	An integration, the universal API, or a file upload	File upload only today. An API is on the roadmap.
What happens to it	Read in full and enriched into Dimensions	Stored as a table you and the agent can query. Never enriched.
When you can use it	Queryable after a short sync. Dimensions arrive as described in When enrichment runs.	Queryable within about a minute

Each item in Data Sources is a source: an integration or an upload under Unstructured data, or a table under Structured data.

The value comes from joining the two: what customers said, next to what they spent, renewed or returned. See Join business data.

The meaning layer

The meaning layer is the name for the whole structure the agent works on: your original conversations, the Dimensions extracted from each one, and your business data, in one schema you can query together. You don’t build it by hand. It is built from the data you connect.

Every source, whether a file upload, the API or an integration, is first put into the same conversation format, so a chat, a review and a survey answer can be read the same way. From there, data moves through the four steps on What Dimension Labs does: enrich, join, prove, repeat.

Dimensions and prompts

A Dimension is one typed field the platform extracts from each conversation: a category, a yes or no, a score, or a short verbatim quote. A prompt is the configuration that defines a set of Dimensions, and each prompt writes its own table. Enrichment is running prompts over conversations.

Every workspace has the standard Dimensions available, called System Prompts in the app. Prompts you design yourself are custom prompts, and the Prompts tab lists all of them. See What a Dimension is.

Because the labels are stored, they act as a ground truth: everyone who asks the same question of the same data gets the same counts, every label can be checked against its conversation, and the results can be counted and tested. Enrichment is a recognition task (finding whether something is present in text that already exists), which is the kind of task language models do most consistently. See How reliable the labels are.

Conversations

The unit Dimension Labs reads is a conversation: one chat, ticket, call, review or survey response, with every message in it in time order. Messages are grouped into a conversation by their sessionId. The model reads the whole conversation at once, customer and agent or bot turns together, and writes one set of Dimensions for it. That’s why the sessionId in your data matters. See Sessions and conversations.

When enrichment runs

Enrichment doesn’t happen the moment data lands.

Data	When it gets Dimensions
A live integration (a one-click integration, or a universal API job sending to /track)	Automatically, every day
A file upload, or anything sent to /trackhistorical	When you run a backfill from the Backfill tab. A backfill typically shows up within the hour, depending on how much data is being enriched.
Standard Dimensions	Every day only when Dimension Labs turns on daily enrichment for your workspace (ask [email protected]). Otherwise, run a backfill.
Business data	Never. It’s queryable within about a minute of upload.

See When enrichment runs and Backfill history.

Drivers, not volume

The most-mentioned issue isn’t always the one that costs you. Dimension Labs ranks drivers by their effect on an outcome you choose (a renewal, a refund, a predicted CSAT score), after accounting for other differences between customers. See How we prove a driver.

Projects and chats

A conversation with the agent is a chat. A project holds the files, standing instructions and chats for a piece of work. Anything in the project’s AGENTS.md file is read as a standing instruction in every chat of that project. See Projects and standing instructions.