Delights

Philosophy

The bet behind Delights is simple: AI is changing our relationship with data.

The dashboard era treated data as something you went and read at a moment in time. The agent era treats data as something you can talk to, shape, and act on as it moves. We can finally ask the questions we want to ask, in real time, and get the answers in the form we need.

We do not want Delights to be a chatbot pasted on top of a dashboard. We want to make customers’ data legible to the models and ecosystems they already work in. We want to ship products that show what good looks like, and prove that data can be delightful.

The AI landscape is changing quickly. Delights is where we become the trusted partner in continuous exploration.

What is Delights?

Delights is curiosity unlocked by AI. It is a place where Density and our customers experiment side by side, with us as the guide.

It has two parts. First, Delights is the set of ephemeral tools we build for customers to show what is possible. Second, it is the home for bring-your-own-agent work: the resources customers need to enable their own agents and make the most of them.

Delights is built for a wide range of users, from people just starting to dabble with AI to organizations with robust AI teams building agents of their own.

Customers find it as a Delights tab in Atlas, with sample delights to play with and a clear path to request one of their own.

How customers engage

Customers engage through ongoing conversations with their account leads, where we act as their guide.

We can help with the basics: getting an agent pointed at Density data, understanding which models and patterns are worth paying attention to right now, and seeing what is actually working in the wild.

Delights is not a set of finished products. It is a place for dialogue: a back and forth with tools that keep changing as the space changes.

The way in is either to ask things of us directly, or to use the resources here: the Sensor CLI, agent-ready markdown, and improved API documentation, all built to fit inside an organization’s AI and data policies.