CRM for Venture Capital: Deal Flow Management

Venture capital firms need a CRM that tracks deal flow from first intro to investment, manages portfolio company relationships, handles LP communications, and keeps sensitive deal data private. DenchClaw is a local-first, open-source AI CRM built on DuckDB that runs on your machine — no third-party cloud access to your deal flow. Here's how to configure it for a VC firm.

What VCs Actually Need from a CRM#

Most VC firms are running deal flow tracking in Airtable, Notion, or a spreadsheet. These tools work to a point, then break down at scale — usually around 500+ inbound deals per year or when you need to query across portfolio, pipeline, and LP relationships simultaneously.

What a VC CRM actually needs:

• Deal flow management from first contact to pass/invest decision
• Sector and stage tagging for portfolio analysis
• Founder relationship tracking (which is different from company tracking)
• LP relationship management with capital call and distribution history
• Network intelligence: who knows whom, who introduced whom

DenchClaw handles all of this with a flexible schema that you define. And because it runs locally, your proprietary deal flow data never touches a vendor's servers.

Setting Up DenchClaw for Venture Capital#

1. Install DenchClaw

npx denchclaw

Opens at http://localhost:3000. All data is in a local DuckDB file.

2. Create a Companies object

Both pipeline and portfolio companies in one place:

• Name (text)
• Website (text)
• Sector (select: SaaS, Fintech, Healthcare, Consumer, Deep Tech, Infrastructure, etc.)
• Stage at First Contact (select: Pre-Seed, Seed, Series A, Series B, Growth)
• Geography (text)
• Status (select: Tracking → Meeting Scheduled → In Diligence → Term Sheet → Portfolio → Passed → Dead)
• Lead Partner (text)
• Source (select: Inbound, Partner Network, Conference, Cold Outreach, Co-Investor)
• Introduced By (text)
• First Contact Date (date)
• Last Activity Date (date)
• Investment Date (date)
• Check Size (number)
• Ownership % (number)
• Notes (text)

3. Create a Founders object

Track founders separately from companies — they often start multiple companies:

• Name (text)
• Current Company (linked to Companies)
• Past Companies (text)
• LinkedIn (text)
• Email (text)
• Relationship Owner (text — which partner manages this relationship)
• Relationship Strength (select: Strong, Warm, Cold, Unknown)
• Background (text — university, prior employers, notable experience)
• Notes (text)

4. Create an LPs object

Your limited partners are long-term relationships requiring active management:

• Name (text)
• Type (select: Family Office, Fund of Funds, Endowment, Pension, Corporate, HNWI, Other)
• Primary Contact (text)
• Commitment Amount (number)
• Fund (text — if multi-fund)
• Capital Called % (number)
• Status (select: Active, Prospective, Former)
• Last Contact Date (date)
• Next Reporting Date (date)
• Notes (text)

5. Create a Meetings/Interactions object

Log all meaningful touchpoints:

• Company or Person (linked)
• Date (date)
• Type (select: Intro Call, Partner Meeting, Diligence Call, Portfolio Check-In, LP Meeting, Conference)
• Attendees (text)
• Summary (text)
• Next Steps (text)
• Follow-Up Date (date)

Managing Deal Flow at Scale#

A typical seed fund sees 1,000-3,000 deals per year. Without a structured process, things fall through the cracks — a promising company gets lost in email, a founder you said you'd reconnect with in 6 months never gets the follow-up.

Use the kanban view for your deal pipeline:

Tracking → Meeting Scheduled → In Diligence → IC Review → Term Sheet → Closed / Passed

Weekly deal review queries:

"Show all companies in 'Meeting Scheduled' or 'In Diligence' status sorted by last activity date" "Which companies have had no activity in over 30 days?" "Show all companies with follow-up date this week"

Thesis alignment queries:

"Show all inbound deals in healthcare sector in Seed stage in the past 90 days" "How many Series A deals in fintech have we evaluated this year vs. last year?"

Pass quality analysis:

"Show all companies we passed on in Q1 sorted by sector" — review passes periodically to assess whether your thesis filters are calibrated correctly.

For more on using AI queries for pipeline analysis, see DenchClaw's natural language query interface.

Portfolio Company Relationship Management#

Once a company is in portfolio, the CRM role shifts from pipeline management to relationship management. You're tracking:

• Key milestones (fundraising, revenue targets, hiring goals)
• Board meeting dates and prep
• Help requests (intros, recruiting, press)
• Red flags that require attention

Update the Status field in your Companies object post-investment:

• Portfolio - Active
• Portfolio - Pivoting
• Portfolio - Struggling
• Portfolio - Exited

Log all portfolio company interactions in your Meetings object. Query: "Show all portfolio companies with no logged interaction in the past 60 days" — these are the relationships that need attention.

Network and Sourcing Intelligence#

One of the most valuable things a VC CRM can do is help you understand your network and how deals are coming in.

Source attribution: "What percentage of our investments came from warm intros vs. inbound vs. conference meetings?"

Network mapping: The Introduced By field on Companies lets you track who in your network is sending the best deal flow. Query: "Show all companies introduced by [person X] sorted by investment status"

Co-investor relationships: Create a Co-Investors object to track other VCs you work with regularly:

• Firm (text)
• Partner (text)
• Stage Focus (text)
• Sectors (text)
• Co-Investments Together (number)
• Relationship Quality (select: Close, Active, Occasional)
• Notes (text)

Strong co-investor relationships are a deal flow source in themselves. Query: "Which co-investors have sent us the most deals in the past 12 months?"

LP Relationship Management#

LP relationships are often underserved in VC CRMs — most tools focus on deal flow and ignore the capital formation side. DenchClaw handles both.

Regular LP touchpoints:

"Show all LPs with no contact in the past 90 days" "Which LPs have their next reporting date this month?" "Show all prospective LPs sorted by last contact date"

Capital tracking:

Track commitment amounts, capital called, and distributions in your LPs object. Use the app builder to create a fund-level dashboard showing total commitments, called capital, and remaining dry powder. See how to build custom apps in DenchClaw.

New fund raises:

When you're raising a new fund, convert the kanban view to an LP pipeline:

Identified → Introductory Meeting → Diligence → Committed → Closed

Track every prospective LP through the raise process with structured follow-ups.

Frequently Asked Questions#

Can DenchClaw replace Affinity, Salesforce Ventures, or 4Degrees? DenchClaw can replace any of these for firms willing to build their own schema. It lacks the automatic email/calendar sync that relationship intelligence platforms like Affinity offer, but it's fully flexible, local, and free to run. Many firms use it as the source of truth and log interactions manually.

How do we handle deal flow for multiple funds? Add a Fund field to your Companies and LPs objects to tag records by fund. Filter views by fund to see each portfolio separately while keeping everything in one queryable database.

Can the team collaborate in real time? Yes. Run DenchClaw on a shared server and all partners and analysts can access it via browser simultaneously.

Can I import our existing Airtable or Notion database? Yes. Export your Airtable base as CSV and import into DenchClaw. The schema migration takes some setup but it's straightforward for anyone comfortable with CSV field mapping.

Is our deal flow data private? Yes. DenchClaw runs locally by default. Your proprietary deal flow, founder relationships, and LP information are stored in a DuckDB file on your machine — not on any vendor's servers.

Ready to try DenchClaw? Install in one command: npx denchclaw. Full setup guide →