Sales & marketing
Lead Qualification & Follow-up
Scores inbound leads, spots the ready-to-buy ones, and drafts a personal follow-up - no more leads sitting in your inbox.
How the data flows
Requests move between your backend and the AI workflows automatically. Here's the exact path a request takes.
AI workflow
lead_qualification_workflow
Scores the lead and starts the follow-up pipeline
Backend event
lead_captured
Backend event
follow_up_queued
AI workflow
lead_follow_up_workflow
Drafts a personal follow-up email
What you get
Every template is built from two kinds of pieces: Workflows and Response Formats.
Workflow
lead_qualification_workflow
Scores the lead and starts the follow-up pipeline
Workflow
lead_follow_up_workflow
Drafts a personal follow-up email
Response format
lead_qualification_response
Lead score, intent, and next action
Response format
lead_follow_up_response
Personal follow-up email for the lead
Details
The full specification of each workflow, with plain-English explanations. Everything below is set in the downloaded file and can be changed after import.
lead_qualification_workflow
Scores the lead and starts the follow-up pipeline
The primary model plus automatic fallback models if the primary is unavailable.
The structured JSON this workflow returns. Fields are defined by you and enforced by ModelRiver.
Fields you include in each request so the workflow can personalise its answer.
Identical requests are answered from memory within this window, which is faster and cheaper.
Steps that run automatically around this workflow, in order.
Runs live against your connected AI provider.
lead_follow_up_workflow
Drafts a personal follow-up email
The primary model plus automatic fallback models if the primary is unavailable.
The structured JSON this workflow returns. Fields are defined by you and enforced by ModelRiver.
Fields you include in each request so the workflow can personalise its answer.
Runs live against your connected AI provider.
How to use it
- 1
Download the template
The file is a portable JSON bundle - safe to share and easy to read.
- 2
Open a project in ModelRiver
Sign in, pick a project, and make sure the AI providers used by this template are connected. You can connect them from the Providers section.
- 3
Import it
Open the Import button in your project, paste or upload the file, review the preview, and confirm. Everything is created atomically, so nothing is overwritten. How import & export works
Template file
Technical users can inspect the raw bundle below.
View full template JSON
{
"version": 1,
"structures": [
{
"name": "lead_qualification_response",
"description": "Lead score, intent, and next action",
"example": {
"fit_score": 82,
"intent": "ready_to_buy",
"lead_category": "high_value",
"next_action": "book a demo call"
},
"schema": {
"type": "object",
"properties": {
"fit_score": {
"type": "number"
},
"intent": {
"type": "string",
"enum": [
"ready_to_buy",
"researching",
"not_interested",
"unknown"
]
},
"lead_category": {
"type": "string",
"enum": [
"high_value",
"medium",
"low"
]
},
"next_action": {
"type": "string"
}
},
"required": [
"fit_score",
"intent",
"lead_category",
"next_action"
],
"additionalProperties": false
}
},
{
"name": "lead_follow_up_response",
"description": "Personal follow-up email for the lead",
"example": {
"email_subject": "Re: your inquiry about ModelRiver",
"email_body": "Hi Alex, thanks for reaching out - happy to answer your questions.",
"send_follow_up": true
},
"schema": {
"type": "object",
"properties": {
"email_subject": {
"type": "string"
},
"email_body": {
"type": "string"
},
"send_follow_up": {
"type": "boolean"
}
},
"required": [
"email_subject",
"email_body",
"send_follow_up"
],
"additionalProperties": false
}
}
],
"workflows": [
{
"name": "lead_qualification_workflow",
"description": "Scores the lead and starts the follow-up pipeline",
"provider": "openai",
"model": "gpt-5.6-terra",
"backups": [
{
"provider": "anthropic",
"model": "claude-haiku-4-5-20251001"
}
],
"request_type": "chat",
"system_instructions": "Score the inbound lead from 0 to 100 based on fit and intent. Choose the lead category, identify what they want next, and flag the best next action for the sales team.",
"structure": "lead_qualification_response",
"customer_fields": [
"lead_name",
"lead_email",
"company",
"lead_message"
],
"test_mode": false,
"cache_window_seconds": 600,
"backend_pipeline": {
"enabled": true,
"events": [
{
"name": "lead_captured"
},
{
"name": "draft_follow_up",
"target_workflow": "lead_follow_up_workflow"
},
{
"name": "follow_up_queued"
}
]
}
},
{
"name": "lead_follow_up_workflow",
"description": "Drafts a personal follow-up email",
"provider": "openai",
"model": "gpt-5.6-terra",
"backups": [
{
"provider": "anthropic",
"model": "claude-haiku-4-5-20251001"
}
],
"request_type": "chat",
"system_instructions": "Write a short, personal follow-up email for the lead based on their message and company. Keep it warm, specific, and easy to reply to.",
"structure": "lead_follow_up_response",
"customer_fields": [
"lead_name",
"lead_email",
"company",
"lead_message"
],
"test_mode": false
}
]
}Looking for something else?
More templates are on the way. In the meantime, you can build your own workflows from scratch in the ModelRiver console.