Case study · Venture capital

Screening thousands of startups for a venture team

Flowhive VC screens deal flow for Red Bull's venture team: pre-configured agents for company due diligence, competitive analysis and market mapping, with portfolio tracking around them. It has analysed thousands of startups and is still running.

Client engagement · via Jaden Data Production

Mandate

Own the product: the agents for due diligence and competitive analysis, the portfolio and deal-flow tracking around them, and its continued operation for the venture team.

Key decisions

  1. Pre-configure an agent per recurring job — due diligence, competitive analysis, market mapping — instead of handing the team a general chat window.
  2. Put screening, portfolio intelligence and deal-flow automation in one workspace, so a screen feeds the decision it was made for.
  3. Keep the investment judgement with the team: the system narrows and maps, the investors decide.

Outcome — qualitative

Thousands of startups analysed for the venture team
Ongoing in production and still run by me
Stakeholders
  • Investment team members screening deal flow
  • Portfolio management
  • Me as product owner and operator
Constraints
  • Deal flow arrives faster than a small team can read it
  • Screening output has to be defensible to investors, not just plausible
  • Continuous operation rather than a delivered project
Reuse
  • Agent templates for due diligence and competitive analysis
  • Market mapping workflow
  • Portfolio intelligence tracking

Context

Red Bull’s venture team sees far more companies than it can study. Flowhive VC was built for that team as an AI workspace for portfolio management and deal flow, and it is still in use.

Business problem

Screening is where a venture team’s attention leaks. Reading every inbound company, checking who else is in the space and keeping a picture of the portfolio all compete for the same hours, and none of it is the actual job, which is deciding where to invest.

My mandate

I own the product: the agents, the workspace around them and its continued operation for the venture team.

Decisions

  • Pre-configured agents for the jobs that recur — company due diligence, competitive analysis, market mapping — rather than a general assistant the team has to prompt from scratch each time.
  • One workspace holding screening, portfolio intelligence tracking and deal-flow automation, so a company analysis lands next to the portfolio picture it affects.
  • The system narrows the field and maps the market; the investment decision stays with the team.

Delivery

The product runs continuously for the venture team and has analysed thousands of startups. I run it.

Outcome

The team screens a volume of companies it could not read by hand, and uses the output to decide where to invest.

Reuse

The agent templates for due diligence and competitive analysis, the market-mapping workflow and the portfolio tracking are product capabilities rather than one-off configurations.

Evidence

The outcome here is qualitative: the volume analysed is described as thousands of startups, and the engagement is ongoing. No investment performance or deal numbers are published.

Want the same thing done in your environment?

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