Analytics Engine

Agents don't read data the way people do. They analyse by writing code: firing off queries to explore a dataset, test a hypothesis, and check their own working. It's also how they stay accurate. Running a query to look at the data is far more reliable than holding it all in context. That makes good analysis compute-heavy by nature: the deeper an agent digs, the more it needs to run.

Count has been built for this:

• Cells to analyse and visualise
• Python environments to run any code
• Sub-agents that take on work without clogging up the main agent's context
• A fast in-memory database that handles most queries itself. Agents can run thousands of them without touching your warehouse, cutting warehouse costs from agents by up to 80%.