Why this exists

The newest AI should not mean learning everything again.

Atlas puts advanced agents, routing, memory, and control behind an interface that stays simple.

Evan Uster in a navy suit, standing beneath a garden pergola

Meet the builder

Hi, I’m Evan.

I’m a 13-year-old builder in Toronto. I build AI tools I use every day, then write down what held up and what did not.

Atlas started with one annoyance: running one agent was easy, but running several meant five windows, repeated context, and no overview.

More about Evan
Video The public beta from first launch to first result Video: use the real beta to show that starting with Atlas feels simple, even when the work behind it is not.

Product screens use staged sample data.

Routing

The newest model should not reset your workflow.

Atlas treats the AI products you already use as available capacity. You describe the outcome once; Atlas chooses the right agent and provider without making you compare every option first.

Staged Atlas activity log showing task routing across local and cloud AI providers
Structure

Complex systems belong behind the interface.

Defined roles, reporting lines, project memory, and connected tools give serious work the structure it needs. You should feel the clarity, not the configuration.

Staged Atlas constellation view showing agent roles and reporting relationships
Control

Control should remain obvious.

More autonomy should not mean less control. Sensitive actions stop where your sign-off matters, and the next step stays visible. Atlas works ahead without working around you.

Staged Atlas activity screen showing a sensitive action paused for approval

The Atlas principle

Advanced underneath. Simple from your side.

Atlas can keep a hierarchy of agents, route work, preserve project context, and enforce permissions without asking you to wire every step together. The complexity earns its place behind the interface, not in front of you.

Spend less time moving work around.

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