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Goal: Get a complete picture of any company or person before outreach. This skill always works with web search, memory and gets significantly better with enrichment and CRM data.

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How It Works

ALWAYS (works standalone via web search and memory)
  • Company overview: what they do, size, industry
  • Recent news: funding, leadership changes, announcements
  • Hiring signals: open roles, growth indicators
  • Key people: leadership team from LinkedIn
  • Product/service: what they sell, who they serve
  • Past context stored in memory about this person/company (email id, any discussion happened or anything)
SUPERCHARGED (when you connect other apps)
  • Enrichment: verified emails, phone, tech stack, org chart
  • CRM: prior relationship, past opportunities, contacts
Connectors (Optional) Connect your tools to supercharge this skill:
ConnectorWhat It Adds
EnrichmentVerified emails, phone numbers, tech stack, org chart, funding details
CRMPrior relationship history, past opportunities, existing contacts, notes
No connectors? No problem. Web search provides solid research for any company or person.

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Output Format

### Research: [Company or Person Name]

**Generated:** [Date]
**Sources:** Web Search + Memory [+ Enrichment] [+ CRM]

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#### Quick Take

[2-3 sentences: Who they are, why they might need you, best angle for outreach]

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#### From CORE Memory

[2-3 sentences: Whatever context is available in CORE memory about the company or the person]

### Company Profile

| Field            | Value                     |
| ---------------- | ------------------------- |
| **Company**      | [Name]                    |
| **Website**      | [URL]                     |
| **Industry**     | [Industry]                |
| **Size**         | [Employee count]          |
| **Headquarters** | [Location]                |
| **Founded**      | [Year]                    |
| **Funding**      | [Stage + amount if known] |
| **Revenue**      | [Estimate if available]   |

#### What They Do

[1-2 sentence description of their business, product, and customers]

#### Recent News

- **[Headline]** — [Date] — [Why it matters for your outreach]
- **[Headline]** — [Date] — [Why it matters]

#### Hiring Signals

- [x] open roles in [Department]
- Notable: [Relevant roles like Engineering, Sales, AI/ML]
- Growth indicator: [Hiring velocity interpretation]

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### Key People

#### [Name] — [Title]

| Field          | Detail                       |
| -------------- | ---------------------------- |
| **LinkedIn**   | [URL]                        |
| **Background** | [Prior companies, education] |
| **Tenure**     | [Time at company]            |
| **Email**      | [If enrichment connected]    |

**Talking Points:**

- [Personal hook based on background]
- [Professional hook based on role]

[Repeat for relevant contacts]

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### Tech Stack [If Enrichment Connected]

| Category  | Tools                         |
| --------- | ----------------------------- |
| **Cloud** | [AWS, GCP, Azure, etc.]       |
| **Data**  | [Snowflake, Databricks, etc.] |
| **CRM**   | [e.g. Salesforce, HubSpot]    |
| **Other** | [Relevant tools]              |

**Integration Opportunity:** [How your product fits with their stack]

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### Prior Relationship [If CRM Connected]

| Field              | Detail                                      |
| ------------------ | ------------------------------------------- |
| **Status**         | [New / Prior prospect / Customer / Churned] |
| **Last Contact**   | [Date and type]                             |
| **Previous Opps**  | [Won/Lost and why]                          |
| **Known Contacts** | [Names already in CRM]                      |

**History:** [Summary of past relationship]

---

### Sources

- [Source 1](URL)
- [Source 2](URL)

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Execution Flow

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Step 1: Parse Request

Identify what to research:
- "Research Stripe" → Company research
- "Look up John Smith at Acme" → Person + company
- "Who is the CTO at Notion" → Role-based search
- "Intel on acme.com" → Domain-based lookup

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Step 2: Web Search (Always)

Run these searches:
1. "[Company name]" → Homepage, about page
2. "[Company name] news" → Recent announcements
3. "[Company name] funding" → Investment history
4. "[Company name] careers" → Hiring signals
5. "[Person name] [Company] LinkedIn" → Profile info
6. "[Company name] product" → What they sell
7. "[Company name] customers" → Who they serve
Extract:
  • Company description and positioning
  • Recent news (last 90 days)
  • Leadership team
  • Open job postings
  • Technology mentions
  • Customer base

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Step 3: Enrichment (If Connected)

If enrichment tools available:
1. Enrich company → Firmographics, funding, tech stack
2. Search people → Org chart, contact list
3. Enrich person → Email, phone, background
4. Get signals → Intent data, hiring velocity
Enrichment adds:
  • Verified contact info
  • Complete org chart
  • Precise employee count
  • Detailed tech stack
  • Funding history with investors

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Step 4: CRM Check (If Connected)

If CRM available:
1. Search for account by domain
2. Get related contacts
3. Get opportunity history
4. Get activity timeline
CRM adds:
  • Prior relationship context
  • What happened before (won/lost deals)
  • Who we’ve talked to
  • Notes and history

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Step 5: Synthesize

1. Combine all sources
2. Prioritize enrichment data over web (more accurate)
3. Add CRM context if exists
4. Identify qualification signals
5. Generate talking points
6. Recommend approach

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Tips for Better Research

  1. Include the domain — “research acme.com” is more precise
  2. Specify the person — “look up Jane Smith, VP Sales at Acme”
  3. State your goal — “research Stripe before my demo call”
  4. Ask for specifics — “what’s their tech stack?” after initial research