Exa Agent Ultra is built for research that must run to exhaustion—think massive list building, deep entity enrichment, or questions that demand thousands of sources. Teams often hit walls when they need exhaustive coverage but lack the time or compute to manually scrape, verify, and merge data from countless web pages. Manual efforts are slow, error‑prone, and quickly become unsustainable as the scale grows. Existing AI agents stop after a few steps, leaving gaps that force analysts to patch results together, delaying decisions and inflating costs.
Exa Agent Ultra solves this by splitting a task into many subtasks and dispatching parallel subagents. It routes the most powerful frontier models to the steps that need deep reasoning while using faster, cheaper models where they suffice. The result is a single API call that continues until the agent exhausts its allocated budget or time, returning the most complete set of rows possible. Users simply set the parameter effort: “ultra” when calling the hosted Exa Agent API. No open‑weights model is required, and there is no need to manage infrastructure—Exa handles hosting, scaling, and model routing.
Typical runs finish complex tasks in about thirty minutes, with very hard cases extending up to three hours. Cost and duration can be capped via maxCostDollars and maxDurationSeconds, giving teams predictable spend and runtime controls. When a limit is reached, the agent stops launching new work and returns whatever it has gathered, ensuring you always get a usable output rather than a timeout error.
For researchers, product managers, and data teams that need exhaustive, source‑backed lists without weeks of manual labor, Exa Agent Ultra offers a turnkey, scalable way to achieve thorough research in a single, manageable API call.
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