SERP Explorer

Inspect live web and news search results with recency filters and a dedicated frontend around the TrendAnalysis.ai search backend.

Run a live SERP query

Test the browser-safe `/api/serp` flow directly on this page, then move into the terminal only when you need evidence extraction and clustering.

Live GETBrowser playground

Try the live SERP endpoint

This playground hits the same read-only SERP route described below, including vertical, recency, and response-format controls.

SERP Search

Normalized Bright Data-backed web or news search results.

Request URL
/api/serp?q=NVDA+earnings&vertical=news&recency=d&format=light
Reference example: /api/serp?q=NVDA%20earnings&vertical=news&recency=d
Open raw
Response
Formatted JSON or text body from the selected public route.
Run a request to inspect the live response payload.

Normalized SERP payloads

Use the same backend search layer that powers the research pipeline, with normalized result lists suitable for debugging or external use.

Web and news verticals

Switch between broad web discovery and news-specific search surfaces without rebuilding the query path.

Recency-aware search

Filter by recent hour, day, week, month, or year to focus on moving narratives rather than stale search results.

Upstream debugging surface

Turn the internal search stage into a public-facing inspection layer so the product shows where evidence collection starts.

Best-Fit Use Cases

Validate whether a topic has enough fresh news coverage before triggering a full run.
Inspect how web versus news search changes the evidence pool for the same market query.
Show prospects and partners that the search layer itself is a reusable product surface.

Exposes the same search-stage capability that seeds TrendAnalysis.ai evidence collection.

API Surface

GET/api/serp

Run a read-only search query against the backend SERP layer. Supports `q`, `vertical`, `format`, and `recency`.

GET /api/serp?q=NVDA%20earnings&vertical=news&recency=d&format=light

Want the full workflow after search?

Use the terminal to turn raw search discovery into evidence extraction, clustering, and graph analysis.