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ProResearch5 nodes
Score 73

Market Research Automation

Define a market topic — Agent Reach sweeps news, reports, and analyst content, Trafilatura cleans sources, LLM synthesises findings into a structured research report with market sizing, trends, and competitor profiles.

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What does this workflow do?

Drop your topic — the pipeline runs 5 automated steps: Agent Reach (topic→json) → Trafilatura (URLs→text) → LLM Reasoning (text→json) → LLM Reasoning (json→markdown) → Python-DOCX (markdown→docx) — and delivers docx. Every node is visible, auditable, and replaceable.

System flow

1. Agent Reach — Multi-source retrieval agent that sweeps public platforms and news 2. Trafilatura — Boilerplate-free main-content extraction from any web page 3. LLM Reasoning — Large-language-model step that extracts, classifies, validates or writes structured output 4. LLM Reasoning — Large-language-model step that extracts, classifies, validates or writes structured output 5. Python-DOCX — Renders the final Word document with headings, tables and styling

Pipeline breakdown

Agent Reach topic Trafilatura URLs LLM Reasoning text LLM Reasoning json Python-DOCX markdown
  1. Agent Reach agent-reach — Multi-source retrieval agent that sweeps public platforms and news topic → json
  2. Trafilatura trafilatura — Boilerplate-free main-content extraction from any web page URLs → text
  3. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output text → json
  4. LLM Reasoning llm — Large-language-model step that extracts, classifies, validates or writes structured output json → markdown
  5. Python-DOCX python-docx — Renders the final Word document with headings, tables and styling markdown → docx

Workflow Reputation Score

Based on executions, success rate, update frequency, component quality, and user rating.

73Overall
★★★★★ 4.4
▶Executions
30
✓Success rate
100
↻Update frequency
70
⚙Component quality
90
★User rating
88

Based on executions, success rate, update frequency, component quality, and user rating.

Components used

Agent Reachagent-reach

Multi-source retrieval agent that sweeps public platforms and news

FlowSync proprietary
Trafilaturatrafilatura

Boilerplate-free main-content extraction from any web page

adbar/trafilatura ↗
LLM Reasoningllm

Large-language-model step that extracts, classifies, validates or writes structured output

FlowSync proprietary
Python-DOCXpython-docx

Renders the final Word document with headings, tables and styling

python-openxml/python-docx ↗

How is this different from n8n or Zapier?

Unlike generic workflow builders, FlowSync workflows ship pre-configured with AI skills baked into every node — OCR, LLM reasoning, transcription, super-resolution — not just webhook triggers. Each node is white-box auditable: you see input, output, and config. Deployment is instant — no self-hosting, no API-key per node.

Use cases

  • New market entry research
  • Industry landscape analysis
  • Competitive positioning study
  • Investment due diligence research

Author & Source

This workflow is maintained by the FlowSync team. All components are open-source or commercially licensed. Source code for each component is linked in the Components section above.

Pricing: Free tier available · PRO tier · Official

Data handling

Data is processed in-memory during pipeline execution only. No files are stored permanently unless you choose to save outputs to your account.

FlowSync Workflow Marketplace · 73 reputation score · 30% execution · 100% success · 5-node white-box pipeline · maintained by FlowSync Official

Ready to run?

Define a market topic — Agent Reach sweeps news, reports, and analyst content, Trafilatura cleans sources, LLM synthesises findings into a structured research report with market sizing, trends, and competitor profiles.

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