Block 1 - When chat message received
- Type / Role
- @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
- Config choices
- Version 1.3
This workflow is provided as-is. Please review and test before using in production.
Why skim 10 K/10 Q by hand when AI can extract what matters in minutes? Who is this for? Sales engineers, solution architects, founders, product/...
@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenrouter, n8n-nodes-base.perplexitytool, n8n-nodes-base.markdown, n8n-nodes-base.set, n8n-nodes-base.stickynote, n8n-nodes-base.httprequest
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Ashish Kumar Swain.
Original n8n.io sourceWhy skim 10-K/10-Q by hand when AI can extract what matters in minutes?
Sales engineers, solution architects, founders, product/strategy teams, analysts, and BD reps who need fast, consistent briefs on public companies—plus a mapping to a chosen vendor’s solutions.
Trigger: “When chat message received” (or webhook) accepts name / URL / ticker + target vendor.
AI Agent:
Chat Model (OpenRouter) orchestrates the prompt and formatting.
Tool: Perplexity Deep Research performs retrieval over the latest 10-K/10-Q and recent references.
Output: Creates a Google Drive document from the generated text (title, summary, initiatives, vendor-solution matches, suggested contacts).
n8n (Cloud or self-hosted).
Credentials in n8n:
OpenRouter API key (with access to Perplexity’s Deep Research model).
Google Drive (and Google Sheets, if you add the sheet step).
Import the workflow JSON into n8n.
Open Credentials → connect OpenRouter and Google Drive.
In the AI Agent node:
Set Chat Model to your OpenRouter model.
Set Tool to Perplexity’s Deep Research endpoint.
Paste the provided prompt that(example):
Ticker/Name disambiguation: Add a guardrail step that confirms the exchange + CIK before analysis.
EDGAR fetch (advanced): Pull the exact 10-K/10-Q document/link and pass it to the model for grounded citations.
Multi-vendor mapping: Loop over a list (e.g., Microsoft, Google Cloud, AWS) and produce a comparison table.
Contact enrichment: Add your preferred enrichment step to suggest roles (IT, Network, Data, Finance).
Scoring: Compute initiative ↔ solution fit scores and prioritize must-explore actions.
Alerts: Send the brief to Slack/Telegram/Email for your team.
Wrong company matched? Add a pre-check that resolves ticker → legal name and require confirmation.
Generic web summary? Tighten the prompt: “Use the latest 10-Q/10-K; cite sections; list initiatives with evidence.”
Empty Drive file? Verify the AI Agent’s {{$json}} mappings flow into the Drive node’s content.
No citations? Require bullet-level references; if missing, loop once with a “citations-only” follow-up prompt.
Turn hours of filing review into a repeatable, shareable brief. You’ll get:
A clean financial snapshot,
The company’s top initiatives,
A vendor-aligned solution map you can act on immediately—great for prospecting, QBRs, and strategic planning.
For setup guidance, customization, or business inquiries, Email: [email protected]
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Financial reporting AI: concise SEC 10-K/10-Q briefs via OpenRouter + Perplexity |
|---|---|
| Complexity | advanced |
| Nodes | 17 |
| Categories | Document Extraction, AI RAG |
| Author | Ashish Kumar Swain |
| Published | 05 Sept 2025 |
Use the JSON export at /data/workflows/8313/8313.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Why skim 10 K/10 Q by hand when AI can extract what matters in minutes? Who is this for? Sales engineers, solution architects, founders, product/...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI RAG use case.