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Find companies that recently raised funding and identify decision-makers for timely, signal-based outreach.
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Based on SOC occupation classification
Helps sales reps break into target accounts via Amplemarket. Runs deep research on the company and key people, identifies the buying committee, surfaces possible engagement angles, recommends who to reach out to and why, and creates personalized multi-channel sequences. Use when a rep wants to research, plan, or execute outreach against a target account — net-new or re-engagement.
Interactively refine your Ideal Customer Profile through guided questions, web research, and iterative Amplemarket searches until your targeting criteria are dialed in.
Build a visual, interactive org chart for any target account using Amplemarket and HubSpot MCP data. Combines contact discovery, enrichment, outreach history, CRM deal context, and relationship signals into a single React-based visual. Use this skill whenever the user asks to map an org structure, visualize contacts at a company, understand outreach status across an account, build a stakeholder map, do account-based research, cross-reference with CRM, see account penetration with CRM data, or map a specific team. Trigger phrases include: "show me the org chart for [company]", "who do we know at [company]", "map the buying committee", "show me outreach status for [account]", "pull all contacts at [domain]", "account map", "stakeholder map", "account penetration", "engineering org chart for [company]", "map the product team at [company]", "deal context for [account]".
Map untapped departments and roles within existing accounts to surface expansion opportunities, then find contacts in whitespace areas with personalization that references your existing relationship.
Analyze existing HubSpot customer accounts to find untapped departments and personas, map whitespace against the full organizational structure from Amplemarket, and generate expansion outreach referencing the existing customer relationship.
Help AEs get a status check on their accounts with open deals -- where things stand, where to focus, and what next steps to take.
| name | funding-event-prospector |
| description | Find companies that recently raised funding and identify decision-makers for timely, signal-based outreach. |
| metadata | {"author":"amplemarket","version":"1.0.4","category":"Signal Monitoring"} |
| compatibility | Requires Amplemarket MCP server |
Find companies that recently raised funding and identify decision-makers for timely, signal-based outreach.
When a user wants to prospect into companies that have recently raised funding, execute this multi-step research and enrichment workflow.
Gather targeting criteria from the user. Ask these five questions:
If the user provides a broad request, infer reasonable defaults and confirm: "I'll search for Series A-C rounds in the last 30 days across all industries. Want me to narrow this down?"
Construct WebSearch queries targeting funding news sources. Run multiple searches to maximize coverage:
"Series [A/B/C]" "raised" [timeframe] site:techcrunch.com"funding round" "[amount range]" [industry] site:crunchbase.com"raised" "million" [industry] [geography] [timeframe]Vary the queries based on user criteria. For example, if the user wants Series B in fintech:
"Series B" "raised" "fintech" site:techcrunch.com 2026"Series B" "funding" "fintech" site:crunchbase.com"raised" "Series B" "million" "fintech" 2026Run 3-5 searches to ensure broad coverage across sources.
WebFetch top results to extract structured funding details from each article. For each result, capture:
Prioritize the 10-15 most relevant results. Skip duplicates where the same company appears in multiple articles.
Enrich each funded company by calling mcp__claude_ai_Amplemarket__enrich_company with the company domain extracted from the funding articles. Key data points to capture:
If the domain is unclear from the article, search for it using the company name + "website" via WebSearch.
Filter against user's ICP criteria. Compare enriched company data against the user's requirements:
Remove companies that do not fit and note why they were excluded. Present the filtered list to the user before proceeding.
Search for decision-makers at each matching company by calling mcp__claude_ai_Amplemarket__search_people with:
company_domains: [company domain]person_titles: based on user's target rolesperson_seniorities: mapped from target roles (e.g., ["VP", "Head", "Director", "C-Suite"])full_output: truepage_size: 10Focus on roles most likely to be involved in post-funding initiatives (hiring, procurement, expansion).
Enrich top prospects by calling mcp__claude_ai_Amplemarket__enrich_person for the highest-priority contacts at each company. Set reveal_email to true for contact details. Credit note: Each person enrichment with email and phone reveal consumes Amplemarket credits. Warn the user before enriching: "I found [N] prospects across [M] companies. Enriching all of them will use [N] credits. Want me to proceed with all, or select the top prospects?"
Present results grouped by funding recency. Organize the output into three tiers:
For each company, display:
Include dynamic fields (see Dynamic Fields Generated below) that can be used in outreach templates.
Offer lead list creation with funding context. Ask: "Would you like me to create a lead list from these prospects? I can name it something like '[Funding Stage] - [Industry] - [Month Year]'." If the user agrees, pivot to creating a lead list via mcp__claude_ai_Amplemarket__create_lead_list using the discovered prospects' LinkedIn URLs.
The following dynamic fields are produced for each funded company and can be used in outreach templates:
| Field | Description | Example Value |
|---|---|---|
{{funding_round}} | Type of funding round | "Series B" |
{{funding_amount}} | Amount raised in the round | "$45M" |
{{funding_date}} | Date of the funding announcement | "2026-02-28" |
{{funding_lead_investor}} | Lead investor in the round | "Andreessen Horowitz" |
{{funding_all_investors}} | All participating investors | "a16z, Sequoia Capital, Tiger Global" |
{{funding_use_of_funds}} | Stated use of the new capital | "Expanding engineering team and entering European markets" |
{{funding_company_name}} | Company name | "CloudMetrics" |
{{funding_company_domain}} | Company website domain | "cloudmetrics.io" |
{{funding_company_size}} | Employee count range | "201-500 employees" |
{{funding_company_industry}} | Company industry vertical | "Cloud Computing / SaaS" |
{{funding_growth_signal}} | Inferred growth signal from the funding | "Hiring 50+ engineers, opening London office" |
{{funding_source_url}} | URL of the funding announcement article | "https://techcrunch.com/2026/02/28/cloudmetrics-series-b" |
{{funding_suggested_opener}} | Ready-to-use opening line referencing the funding event | "Congrats on CloudMetrics' $45M Series B. With plans to scale the engineering team, I imagine tooling decisions are top of mind right now." |
User prompt: "Find companies that raised a Series B in fintech in the last 30 days. I want to reach VPs of Engineering."
What the skill does:
"Series B" "raised" "fintech" site:techcrunch.com 2026"Series B" "funding" "fintech" site:crunchbase.com 2026"raised" "Series B" "million" "fintech" February 2026mcp__claude_ai_Amplemarket__enrich_company for each company found.mcp__claude_ai_Amplemarket__search_people at each company with person_titles: ["VP of Engineering", "Vice President of Engineering"], person_seniorities: ["VP"].Example output:
FUNDING EVENT PROSPECTS: Series B Fintech - Last 30 Days
This Week (3 companies)
1. PayFlow - $38M Series B (March 5, 2026)
| Field | Detail |
|---|---|
| Domain | payflow.io |
| Industry | Fintech / Payments |
| Size | 120 employees |
| Lead Investor | Accel |
| Use of Funds | Scaling engineering team, launching in LATAM |
| Source | techcrunch.com/2026/03/05/payflow-series-b |
Decision Makers Found:
| Name | Title | ||
|---|---|---|---|
| James Liu | VP of Engineering | j.liu@payflow.io | linkedin.com/in/jamesliu |
| Nina Patel | Head of Platform Engineering | n.patel@payflow.io | linkedin.com/in/ninapatel |
{{funding_suggested_opener}}: "James, congrats on PayFlow's $38M Series B. With plans to scale engineering and launch in LATAM, I imagine you are making some key infrastructure decisions right now."
2. LendStack - $52M Series B (March 3, 2026)
| Field | Detail |
|---|---|
| Domain | lendstack.com |
| Industry | Fintech / Lending |
| Size | 200 employees |
| Lead Investor | Sequoia Capital |
| Use of Funds | Product expansion, doubling engineering headcount |
| Source | crunchbase.com/funding_round/lendstack-series-b |
Decision Makers Found:
| Name | Title | ||
|---|---|---|---|
| Sarah Kim | VP of Engineering | sarah.k@lendstack.com | linkedin.com/in/sarahkim-eng |
{{funding_suggested_opener}}: "Sarah, saw LendStack just closed a $52M Series B led by Sequoia. Doubling the engineering team is a big undertaking, and getting the right tooling in place early can save months of rework."
This Month (5 companies)
(Same format continues for companies that raised 8-30 days ago)
Summary
Would you like me to create a lead list from these 14 prospects? I'd suggest naming it "Series B - Fintech - Mar 2026".
User prompt: "Who just raised Seed or Series A in healthtech on the US West Coast? I want to reach founders and CTOs."
What the skill does:
"Seed" OR "Series A" "raised" "healthtech" OR "health tech" OR "digital health" site:techcrunch.com 2026"Seed round" OR "Series A" "healthcare" "California" OR "Oregon" OR "Washington" site:crunchbase.com"raised" "million" "digital health" "San Francisco" OR "Los Angeles" OR "Seattle" OR "Portland" 2026mcp__claude_ai_Amplemarket__enrich_company for each company found.mcp__claude_ai_Amplemarket__search_people with person_seniorities: ["Founder", "C-Suite"], person_titles: ["Founder", "Co-Founder", "CTO", "Chief Technology Officer"], company_domains: [each matching company domain].Example output (abbreviated):
FUNDING EVENT PROSPECTS: Seed/Series A Healthtech - US West Coast
This Week (2 companies)
1. MedSync - $8M Seed (March 6, 2026)
| Field | Detail |
|---|---|
| Domain | medsync.health |
| Industry | Digital Health / Telemedicine |
| Size | 15 employees |
| Lead Investor | Khosla Ventures |
| Use of Funds | Building initial product team, FDA pathway |
| Source | techcrunch.com/2026/03/06/medsync-seed |
Decision Makers Found:
| Name | Title | ||
|---|---|---|---|
| Dr. Anika Rao | Co-Founder & CEO | a.rao@medsync.health | linkedin.com/in/anikarao |
| Marcus Chen | Co-Founder & CTO | m.chen@medsync.health | linkedin.com/in/marcuschen |
{{funding_suggested_opener}}: "Anika, congrats on MedSync's $8M Seed led by Khosla. Navigating the FDA pathway while building a product team is no small feat. Would love to share how we help early-stage health tech teams move faster."
User prompt: "Find companies that raised $50 million or more in the last 60 days. Any industry. Target Heads of Sales and CROs."
What the skill does:
"raised" "$50 million" OR "$60 million" OR "$75 million" OR "$100 million" 2026 site:techcrunch.com"funding" "50M" OR "75M" OR "100M" site:crunchbase.com 2026"raised" "million" "Series" 2026 (then filters to $50M+ during extraction)mcp__claude_ai_Amplemarket__enrich_company for all companies regardless of industry.mcp__claude_ai_Amplemarket__search_people with person_titles: ["Head of Sales", "CRO", "Chief Revenue Officer", "VP of Sales"], person_seniorities: ["Head", "C-Suite", "VP"], company_domains: [each company domain].Example output (abbreviated):
FUNDING EVENT PROSPECTS: $50M+ Rounds - All Industries - Last 60 Days
Found 12 companies that raised $50M or more. Showing top results by round size:
| Company | Round | Amount | Industry | Lead Investor | Date |
|---|---|---|---|---|---|
| DataForge | Series C | $120M | Cloud Infrastructure | Tiger Global | Mar 2, 2026 |
| ClimateTech Co | Series B | $85M | Clean Energy | Breakthrough Energy | Feb 25, 2026 |
| SecureNet | Series C | $72M | Cybersecurity | Insight Partners | Feb 18, 2026 |
| ShipFast | Series B | $55M | Logistics / Supply Chain | a16z | Feb 10, 2026 |
Total CROs/Heads of Sales found: 22 Enriched with contact details: 12
Would you like me to create a lead list? I can segment by industry or create one unified list named "$50M+ Rounds - Q1 2026".
| Problem | Solution |
|---|---|
| WebSearch returns few or no funding articles | Broaden the search: 1) Remove the site: restriction to search across all sources. 2) Extend the timeframe (e.g., 30 days to 90 days). 3) Use broader terms like "raised" or "funding" instead of specific round names. 4) Try alternative sources like Bloomberg, Reuters, or industry-specific publications. |
| Company domain cannot be determined from the article | Fallback chain: 1) WebSearch for "[company name] website" to find the domain. 2) Try common domain patterns (companyname.com, companyname.io). 3) Search for the company on LinkedIn and use the LinkedIn URL for enrichment. 4) If still not found, note the company with available data and skip enrichment. |
enrich_company returns no data for a funded company | This is common for very early-stage startups not yet indexed. Use the data extracted from the funding article (company name, funding details, investors) and flag: "Company not found in Amplemarket. Details sourced from funding announcement only." |
| No decision-makers found at a funded company | Fallback chain: 1) Broaden seniority to include "Manager" and "Senior". 2) Try searching by company name instead of domain. 3) For companies with fewer than 50 employees, search for "Founder" and "C-Suite" only. 4) Check the funding article for named executives and try enrich_person with name + company. |
| Duplicate companies across search results | Deduplicate by company domain before enriching. If two articles reference the same company's round, merge the details and keep the most recent or most detailed article as the source URL. |
| Funding article is about a company update, not an actual round | Verify each article by checking for specific funding indicators: round type, dollar amount, investor names, and funding date. Discard articles that mention funding only in passing or reference historical rounds. |
| Too many results consuming excessive credits | Prioritize by: 1) Recency (most recent funding first). 2) ICP fit (filter companies before enriching people). 3) Offer tiered enrichment: "I found 40 prospects. Want me to enrich the top 10 first, then continue if the quality looks good?" |