The Live Agent Company

Every research company eventually has to answer the same question: whose opinion is this, really? Panels answer it with recruitment criteria. Synthetic personas answer it with a prompt. We think both answers are increasingly insufficient for the decisions enterprise teams are making with the results.

Why we started here

We started Sayge because we kept seeing the same failure pattern: a team makes a high-stakes decision — a launch, a price change, a campaign — based on research that was either too slow to matter or too synthetic to trust. The gap between “directionally interesting” and “something I'd defend in front of the board” was almost never closed.

Live AI Agents close it by refusing to be anonymous. Every agent in the network traces back to one real, identifiable person, starting from public behavior and gaining fidelity only as that person claims their agent, verifies it, and chooses — explicitly, revocably — to contribute more. Nothing in a baseline agent is private data. Nothing gets added without permission.

The Quality Ladder

Not every answer deserves the same confidence, so we don't present one. Each Live AI Agent sits somewhere on a five-step ladder, from Baseline — public signal only, good for an early directional read — up through Claimed, Verified, Learning, and High-fidelity, where accuracy is measured directly against real outcomes. A result built on Level 5 agents and a result built on Level 1 agents are both useful; they are not the same thing, and we never let them look like it.

What we're building toward

The long-run goal isn't a bigger panel. It's a network specific and current enough that asking it a question feels less like commissioning a study and more like asking a person you trust — except it's thousands of them, each accountable, each real, all at once. That's the frontier we think is actually in front of the industry, and it's the only one we're building for.