Funding Round Tracker

Drop in a list of company URLs. Get back: latest funding round (stage, amount, lead investor, year), full funding history, recency rating, and an AI-generated buying window assessment.

Just-funded companies have a 60 to 90 day aggressive procurement window. This actor tells you who is in it right now.

What this solves

Timing is the biggest variable in B2B sales. The same pitch that fails at Month 13 (after the procurement window has closed) closes instantly at Month 2 (when they just raised and are buying aggressively). This actor tells you where each prospect sits in that cycle.

What you get per URL

{
  "input_url": "https://linear.app",
  "company_name": "Linear",
  "mode": "ai",
  "has_funding_signal": true,
  "latest_stage": "series-c",
  "latest_amount_usd_m": 82,
  "latest_lead_investor": "Accel",
  "latest_year_hint": 2024,
  "latest_evidence_quote": "Linear closed an $82M Series C led by Accel...",
  "latest_confidence": "high",
  "recency": "recent",
  "funding_history": [
    { "stage": "series-c", "amount_usd_m": 82, "lead_investor": "Accel", "year_hint": 2024, "confidence": "high" },
    { "stage": "series-b", "amount_usd_m": 35, "lead_investor": "Sequoia", "year_hint": 2022, "confidence": "high" }
  ],
  "total_raised_usd_m": 117,
  "stage_proxies": { "founded_year": 2019, "customer_count_signal": 25000 },
  "ai_insights": {
    "estimated_stage": "series-c",
    "runway_assessment": "Strong, ~24-36 months on current burn",
    "buying_window": "active, 12 months from last round so aggressive procurement window is past but still spending",
    "sales_pitch_angle": "Pitch tools that scale with multi-region distributed engineering team",
    "key_investor_signals": "Accel + Sequoia signal sustained product-led growth trajectory"
  }
}

The buying window model

Round recency	recency value	Buying behavior
Under 3 months	very_recent	Aggressive: buying fast and broadly
3 to 12 months	recent	Active: most procurement underway
12 to 24 months	moderate	Selective: tighter evaluation
Over 24 months	older	Cautious: ROI focus, likely approaching next raise
No signal	none	Bootstrapped or signal not found

Modes

Preview (free)

1 URL only, no charge. Use to test the output before running a paid batch.

Regex ($0.20 per result, recommended for bulk)

• Fetches homepage plus 11 common press / about / investors / news paths
• Sentence-level pattern matching for funding signals: stage + amount/investor/verb combinations
• Extracts evidence quote (the exact sentence the signal was found in)
• Computes recency from year hint
• Extracts soft stage proxies: founded year, customer count signal, team size signal, revenue signals

Honest limitation: Regex detects signals in static text only. Companies that haven't published a press release or don't mention funding publicly will return has_funding_signal: false even if they have raised. AI mode uses inference to fill some of these gaps.

AI-enhanced ($0.40 per result)

Runs regex, then Claude reads up to 5 pages (homepage, about, press, investors, news/blog) to:

• Find non-obvious funding signals (investor logos, portfolio pages, "backed by" mentions)
• Infer funding stage from proxies when direct signal is absent
• Generate runway assessment and buying window classification
• Identify the best sales pitch angle given the company's stage and growth trajectory

AI deep ($0.60 per result)

Same as AI-enhanced but also reads the latest 2 blog posts or press releases for the freshest signals.

Input format

{
  "urls": ["https://linear.app", "https://notion.so"],
  "mode": "regex"
}

• urls: array of company URLs (homepage preferred)
• mode: "preview" | "regex" | "ai" | "ai_deep" (default: "regex")

Who uses this

• SDRs and AEs who want to prioritise just-funded companies in their outreach queue
• VCs and angels tracking portfolio company growth trajectories
• BD and partnerships teams finding well-funded strategic partners
• Investors doing preliminary diligence on private companies
• Competitive intelligence teams monitoring funded competitors

FAQ

Q: What if a company is bootstrapped and never raised? The actor returns has_funding_signal: false and recency: "none". The stage_proxies block still returns available signals (founded year, customer count). AI mode can infer approximate stage from these proxies.

Q: How do you know the year of the round? From the evidence text. If the year is not explicit, the actor returns year_hint: null and recency: "unknown".

Q: Can I filter results by recency? Yes. Use Apify's dataset filtering in the UI, or pipe the dataset into your own code and filter on the recency field.

Q: What's the typical hit rate? In regex mode: approximately 45% of companies have detectable funding signals on their site. AI mode raises this to approximately 70% (by reading investor pages and inferring from proxies).

The B2B Sales Intelligence Suite

This actor is part of a 4-actor suite by Emily Ward that turns a raw TAM list into a ranked, personalised outreach queue:

1. Hiring Signal Detector: who's expanding?
2. Funding Round Tracker (you are here): who has fresh capital?
3. SaaS Spend Scanner: what do they pay for?
4. AI Sales Personalizer: write the opener.

Used together, they 3x outbound conversion vs working from a raw TAM list. What used to take a 5-person SDR team a week takes 1 person 2 hours and ~$95 AUD in Apify credits.

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Tags: funding venture-capital crunchbase b2b sales-intelligence startup investment lead-enrichment

Made by Emily Ward, Founder of Cancel Costs. Questions: emily@cancelcosts.com