Lead qualifying from any data source.

1. This val is a webhook
2. You can POST arbitrary lead data to it from anywhere
3. An AI agent sorts the good leads from the bad leads
4. Leads are stored and arranged in a dashboard

1. Click Remix
2. Click here to save your OPENAI_API_KEY as an environment variable
3. Customize PROMPT.txt (Don't remove any fields from the structured response)
4. Get the val's HTTP endpoint from main.ts:
5. Forward leads to this webhook as a POST request.
6. That's it! Watch them drop into your dashboard at main.ts

• The HTTP endpoint at main.ts ingests all inbound POST request data and passes it to the OpenAI agent in agent.ts.

• The agent uses the lead data from your POST request and its web search tool to determine if the lead is a match for the criteria in PROMPT.txt.
• By default, the AI returns {name, match, reasoning}. This is the output_data.

• Every lead is added to the leads SQLite table: id, timestamp, input_data, output_data.
• The main.ts dashboard shows a history of all lead assessments, successful matches first. Clicking any lead shows the full inbound and output data from the assessment.

• Add fields to the AI's output instructions in PROMPT.txt to:
• enhance AI's assessment
• enrich your leads
• normalize lead data from different sources.

• add query parameters to your POST
  • (ex: your-val-endpoint.val.run?source=signup-page`)
  • The parameters will be bundled in the _query object of input_data.