Demos/Sales · GTM

ICP Qualifier

Score any company against your Ideal Customer Profile and get a sourced rationale in one call.

company-intelligencescoringsyncapi

Try it

Input

Website domain — no protocol or path.

Natural language rubric. The agent uses it as the scoring criterion.

Output

cached sample
{
  "company_name": "Sixtyfour AI, Inc.",
  "industry": "Data enrichment / AI",
  "headquarters": "San Francisco, CA, United States",
  "employee_count": "15",
  "employee_count_range": "10-50",
  "annual_revenue_estimate": "Not publicly disclosed — early-stage startup",
  "funding_stage": "Series A",
  "last_funding_round": "Series A — $4.1M total raised, per Crunchbase and press reports",
  "last_funding_date": "2024",
  "primary_buyer_persona": "VP Engineering / Head of Developer Growth / RevOps",
  "tech_stack_signals": "TypeScript, Python, Next.js, AWS, LLM orchestration, REST APIs",
  "key_products_or_services": "People and company intelligence APIs — find_email, find_phone, and an in-house Waterfall enrichment API for developers",
  "target_market": "B2B SaaS, GTM, recruiting, and compliance teams that need structured people and company data via API",
  "notable_signals": "Launched open-source demo hub and skills for AI agents; replaced third-party enrichment dependency with in-house Waterfall API; active PLG motion on docs and app",
  "icp_fit_score": "62",
  "icp_verdict": "moderate",
  "icp_reasoning": "Sixtyfour is a US-headquartered B2B SaaS company with a clear technical buyer in engineering and developer-facing GTM — matching the product profile and HQ criteria. Headcount (~15) sits below the 50–500 floor, and reported funding is Series A rather than Series B+, so the account is a strong product fit but undersized on scale and maturity relative to the rubric.",
  "icp_key_facts": [
    "US HQ (San Francisco)",
    "B2B SaaS / API-first data enrichment",
    "Series A stage (~$4.1M raised)",
    "~15 employees",
    "Developer and engineering buyer persona",
    "find_email / find_phone / Waterfall API product suite",
    "Active open-source and PLG developer motion"
  ],
  "icp_mismatches": [
    "Headcount ~15 is below the 50–500 employee minimum",
    "Funding stage is Series A, not Series B+ as specified in the rubric"
  ]
}

Copy code

// ICP Qualifier — score one company against your ICP rubric.
// Single API call. No workflow setup needed.
// Run: SIXTYFOUR_API_KEY=... node icp.mjs

const API_KEY = process.env.SIXTYFOUR_API_KEY;
const BASE = "https://api.sixtyfour.ai";

const domain = "ramp.com";
const icp = "B2B SaaS, 50-500 employees, US HQ, Series B+ funded, technical buyer in eng or finance.";

const res = await fetch(`${BASE}/company-intelligence`, {
  method: "POST",
  headers: { "x-api-key": API_KEY, "Content-Type": "application/json" },
  body: JSON.stringify({
    target_company: { website: domain },
    struct: {
      company_name: "Official company name",
      industry: "Primary industry (1-3 words)",
      headquarters: "City, state, country",
      employee_count: "Estimated total employees",
      funding_stage: "Latest funding stage",
      last_funding_round: "Most recent round: name, amount, lead investor",
      annual_revenue_estimate: "Most recent known ARR with source",
      tech_stack_signals: "Notable technologies (3-6 items)",
      primary_buyer_persona: "Primary buyer role (CTO, VP Eng, CFO, etc.)",
      icp_fit_score: `Integer 0-100 scoring against: "${icp}"`,
      icp_verdict: "One of: strong | moderate | weak | unfit",
      icp_reasoning: "2-4 sentences explaining score with specific facts",
      icp_key_facts: "5-8 bullet strings of relevant facts",
      icp_mismatches: "ICP criteria the company fails. 'none' if perfect."
    },
    tier: "low"
  }),
});

if (!res.ok) throw new Error(`Failed: ${res.status} ${await res.text()}`);
const { structured_data, confidence_score, references } = await res.json();

console.log(JSON.stringify(structured_data, null, 2));
console.log(`Confidence: ${confidence_score}/10`);

Response data

A score (0–100), a fit verdict (strong / moderate / weak / unfit), the company facts that drove the score, and a list of source URLs the agent referenced.

Run locally

  1. 1

    Clone the repo

    bash
    git clone https://github.com/sixtyfour-ai/sixtyfour-demos.git
    cd sixtyfour-demos/demos/sales-gtm/icp-qualifier
  2. 2

    Add your API key

    Get your key from app.sixtyfour.ai, then:

    bash
    cp .env.example .env
    # Open .env and set SIXTYFOUR_API_KEY=your_key_here
  3. 3

    Install dependencies

    bash
    pnpm install
  4. 4

    Run the demo

    Executes the enrichment and prints the structured output to your terminal.

    bash
    pnpm start