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. Everything is stored and sorted 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.

• You can add any number of fields to the AI's output instructions in PROMPT.txt and they'll be added to output_data. You can use this to expand the AI's assessment, enrich your leads, or even just normalize lead data coming from different sources.
• You can also add query parameters when you POST to the val endpoint. (ex: your-val-endpoint.val.run?source=signup-page). The parameters will be bundled in the _query object of input_data. This can be useful for tracking where a lead was forwarded from.