Score and qualify inbound leads automatically with AI and BANT

Scores every new lead against the BANT framework with AI and stores the results so sales can focus on the best prospects.

How the work actually flows

It branches. Every path runs.

Pattern: Parallel Split (2)

flowchart TD trig>"new lead via webhook"]:::trig s0["score lead against BANT"]:::task s1["assign score and label"]:::task s2["recommend next step"]:::task trig --> s0 s0 --> s1 s1 --> s2 gx{"+ where to send result"}:::gate s2 --> gx p00["save to database"]:::task gx -->|"save record"| p00 p10["post to Slack"]:::task gx -->|"alert team"| p10 p00 --> out p10 --> out out[/"qualified lead record created"/]:::out pay{{"sales focuses on best leads"}}:::pay out --> pay classDef task fill:#e7f6fe,stroke:#34b8f0,color:#2c2a29 classDef svc fill:#f6f8fa,stroke:#7c8795,color:#2c2a29 classDef mi fill:#e7f6fe,stroke:#0079a8,color:#2c2a29,stroke-width:2px classDef human fill:#fff,stroke:#0079a8,color:#0079a8 classDef store fill:#f6f8fa,stroke:#0079a8,color:#2c2a29 classDef trig fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigtime fill:#00a4eb,stroke:#0079a8,color:#fff,font-weight:bold classDef trigdata fill:#8ad4f5,stroke:#0079a8,color:#06314c,font-weight:bold classDef gate fill:#fff,stroke:#e8a23d,color:#6b4708,font-weight:bold classDef out fill:#1f9d6b,stroke:#167a53,color:#fff,font-weight:bold classDef pay fill:#06314c,stroke:#021f33,color:#fff
Starts itA stepEvery pathResultPayoff
Build size
Advanced

A larger build with multiple systems, AI reasoning, and custom rules.

Business functions
Knowledge Base & RAGLead Generation & ProspectingEmail AutomationMessaging & NotificationsSpreadsheet & Database OpsAPI & Webhook Integration
Connects
OpenAISupabaseSlack
Featured in

The problem it solves

Your team wastes time chasing leads that were never going to buy, while promising prospects sit in the queue too long. Without a consistent way to score budget, need, and timeline, every rep judges leads differently, and good opportunities slip through the cracks.

Who it fits

B2B sales teams, SaaS companies, or marketing departments that need to separate hot leads from tire-kickers before handing them to sales.

How it works

  1. Triggers when a new lead comes in through a webhook
  2. AI scores the lead against Budget, Authority, Need, and Timeline, plus company fit and engagement
  3. Assigns a 0-100 score and labels the lead Hot, Warm, or Cold
  4. Recommends the next step for the sales rep
  5. Saves the score and details to Supabase and alerts the team in Slack
What you get

Leads ranked by how ready they are

You get every inbound lead scored against Budget, Authority, Need, and Timeline, so your sales team knows exactly who to call first.

What you get

A qualified lead record with a score, priority level, and recommended next action, stored for tracking over time.

What you need

An OpenAI account, a Supabase account, and a way to send leads in, such as a web form or CRM webhook.

We can build this. But should you?

The hard question is not how to build it. It is whether this is the right thing to build first.

That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.

Let's Talk Strategy

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