SolutionsSales & MarketingLead Qualification
by Community

Lead Qualification

AI enriches and scores leads. Human resolves ambiguous ones.

$0.01–$1 / lead· or custom pricing defined by client

The problem

You pulled 5,000 leads from Apollo. Your AI enriched them. But 500 have conflicting data — one source says 50 employees, another says 200. Is the VP of Engineering a decision maker or not? These ambiguous leads stall your pipeline.

How it works

01

Submit your lead batch

Via form, API, or SDK. From any workflow or AI agent.

02

AI analyzes and flags

AI enriches lead data, scores against ICP, flags conflicts and ambiguous cases

03

Human reviews what matters

Qualified reviewer (sales background preferred) reviews flagged items within your SLA. Credential requirements vary by task.

04

Result + audit trail

Structured decision. SHA-256 audit hash. Tamper-proof record.

What the human reviewer does

Resolves data conflicts between enrichment sources

Classifies ambiguous leads as hot / warm / cold based on ICP fit

Verifies decision-maker status and buying authority

Checks company fit criteria (size, industry, tech stack)

Adds qualitative notes on why each lead was classified as-is

Pricing

$0.01–$1 / leadper task
  • or custom pricing defined by client
  • Operators earn 80% of the checkpoint budget
  • Auto-refund if deadline is missed

Who reviews

Verified professionals matched to the Sales & Marketing category

Credential requirements vary — some tasks require specific certifications, others are open to all verified operators

Every review includes a SHA-256 audit hash for verification

Preferred credential for this use case: Qualified reviewer (sales background preferred)

Built with HumanAgent

This use case was built with the HumanAgent API. You can build your own version — customize the workflow, set your own pricing, integrate your own AI, and choose your operators.

Operator credential requirements vary by task. Some tasks are open to all verified operators.