evidence-firsttraceableBright Data docs

TrendAnalysis.ai 如何工作

查看实时搜索、证据提取、图谱构建和回放快照如何组成当前的 TrendAnalysis.ai 产品结构。

ARCHITECTURE

Evidence-first pipeline

plan -> search -> scrape -> extract -> link -> cluster -> render

User question

Ask about an asset, a move, and a horizon (today / 24h / week).

AI planner (OpenRouter)

Generates search angles and coverage constraints (recency, macro, catalysts).

Bright Data SERP

Gets fresh sources across news and web with consistent parsing.

Web Unlocker

Fetches the pages that matter (and that usually block bots).

AI extraction + linking

Summaries, entities/actors, catalysts, edges, spillover hypotheses.

Supabase

Stores sessions, pipeline events, and evidence so the UI can replay the trace.

Dashboard

Breaking Tape, Sources, Narratives, Evidence Map (Graph/Mind/Flow), Price, Video Pulse, Chat.

Bright Data is used as the evidence acquisition layer; the model uses that evidence to reason and produce artifacts.

架构说明

当前产品壳的生产形态说明

数据层

Bright Data 提供 SERP 与页面提取；AI 推理只基于已收集的证据。

工件层

每次运行都会生成证据、时间带、图谱连接和叙事聚类，并保存可回放的快照。

界面层

以地图为中心的工作区把图谱、时间线、检查器和仪表盘回放整合到同一个研究界面中。