A queue of investors: ~25 calls for each of 7 startups
The fundraiser was raising capital for startups by hand: thousands of investor contacts are physically impossible to work through personally. We built a pipeline — database segmentation, smart outreach and AI replies — and within the first weeks each of the 7 projects landed roughly 25 investor calls.
| Sheet | 3.5 · “Cases” series |
| Project | Fundraising pipeline |
| Industry | Investment |
| Author | EDEMIUM |
| Status | Live |
What the client came with
Where deals hit the ceiling
Fundraising ran on personalization: an investor only replies to an email written for them — for their sector, their check size, their past deals. But an email like that takes time, and working through thousands of investor contacts by hand is physically impossible.
So the business lived off one-off deals: close a round for one project, start from scratch on the next. The contact base sat idle, and every new startup in the portfolio multiplied the volume of manual correspondence.
The fork was brutal: either lose personalization and turn into spam, or stay manual and hit the ceiling of your own hours. What was needed was a pipeline that keeps a personal tone at scale.
What we built
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01 · SEGMENTATION
Parsing and segmenting the investor base
The investor base is parsed and sorted into segments: sectors, check sizes, preferences. Each startup in the portfolio reaches the investors it is relevant to.
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02 · OUTREACH
Smart personalized emails
The pipeline sends 200–300 emails a day, each assembled for a specific investor and segment. A personal tone holds at a scale that was unreachable by hand.
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03 · AI REPLIES
Auto-answers from the startup decks
The AI reads the startup decks and answers investors’ standard questions on its own. Complex requests go to the fundraiser — who steps in where the deal is won.
Results in numbers
- Investor calls
- ~25 for each of 7 startups
- Startups in progress
- 7 in parallel in one pipeline
- Emails a day
- 200–300 personalized outreach
- Routine correspondence
- −61% of the fundraiser’s time
| Metric | Before | After |
|---|---|---|
| Investor calls | one-off deals | ~25 for each of 7 startups |
| Emails to investors a day | — | 200–300 |
| Time on routine correspondence | by hand | −61% |
| Base segmentation | — | sectors · checks · preferences |
| Investors’ standard questions | answered by the fundraiser | AI from the startup decks |
| Complex requests | in the general flow | fundraiser handles by hand |
Timeline and status
The system is live: within the first weeks each of the seven portfolio startups landed roughly 25 investor calls. The pipeline holds a pace of 200–300 personalized emails a day.
Routine correspondence dropped by 61%: the AI closes investors’ standard questions from the startup decks, while the fundraiser only steps in on complex requests — where the deal is won.
| Status | Live |
| Capacity | 200–300 emails a day |
| Portfolio | 7 startups in progress |
| Exit point | KPI measured on the pilot: metric hit → scale |
I want the same in fundraising
Start with an automation map: in 14 days we’ll show where your deal flow hits manual correspondence and what can be put on a pipeline.