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How Fundraising Teams Use IR Automation 👥

Different roles, same system, better investor relationships

August 6, 2025
13 min read
💼 Fundraising👥 4 Roles⚡ Real Workflows

Same automation. Four different workflows.

Tuesday you saw the code. Today you see how real team members actually use it. Each role has different needs, different views, different wins.

Team Workflows

See how different roles use the same system to transform their daily work.Click each role below

Before Automation

Manually track 150+ investor conversations across email, calls, meetings (12 hours/week)
Compile weekly update emails by copying/pasting from 6 different sources (6 hours)
Prepare board decks by hunting down metrics and formatting slides (8 hours)
Answer 'what did we tell Sequoia?' questions by searching old emails (4 hours)
Create investor segmentation lists in spreadsheets (3 hours)
Draft personalized follow-ups one by one (7 hours)

With Automation

Review AI-generated conversation summaries in dashboard (1 hour/week)
Approve auto-drafted investor updates with one-click edits (30 min)
Export board-ready slides from live data dashboard (45 min)
Ask AI 'What did we tell Sequoia about ARR?' - instant answer with sources (2 min)
AI auto-segments investors by stage, interest, engagement (automatic)
Personalize AI-drafted follow-ups in bulk editor (2 hours)

Workflow Process

💬Conversations LoggedAuto🤖AI Summarizes5 min👀Manager Reviews1 hour✉️Updates Sent30 min

Impact By The Numbers

Volume
150 active investor relationships
Saved
32 hours/week → 8 hours/week (24 hours saved)
Quality
100% conversation tracking vs 40% before
Outcome
Handle 3x investor volume without burning out

"I went from drowning in updates to actually building relationships."

— IR Manager, Series B SaaS, 6 years fundraising

How Roles Work Together Through the System

Sequoia partner hasn't responded to last 2 updates. System detects pattern, team collaborates to re-engage.

🚨

High-Priority Investor Follow-Up

✨ Scroll here to watch the workflow

🚨
AI Agent
Automatic
Flags Sequoia as 'stale' (no response in 45 days, historically engaged)
📊
Operations Lead
+2 min
Sees alert on dashboard, assigns to IR Manager with priority tag
🔬
IR Analyst
+3 min
Pulls Sequoia interaction history: last 6 calls, topics discussed, questions asked
✍️
AI Agent
+2 min
Generates personalized re-engagement email referencing their last question about enterprise pipeline
✉️
IR Manager
+5 min
Reviews draft, adds personal note about recent enterprise win, sends
📈
AI Agent
Automatic
Tracks open rate, schedules follow-up reminder if no response in 7 days

Team-Wide Impact

MetricBeforeAfterImprovement
Weekly Team Hours on IR75 hours (Manager 40 + Analyst 20 + Ops 15)14 hours (Manager 8 + Analyst 4 + Ops 2)
81% reduction
Investor Relationships Managed50 active (capacity limit)150 active (3x scale)
200% increase
Update Response Rate22% (investors ignore generic updates)38% (personalized, relevant content)
+73% engagement
Time to Answer 'What Did We Say?'10-15 min (search old emails)5 seconds (AI semantic search)
99% faster

Getting Your Team On Board

⚠️
Fear

IR Manager: 'AI can't write like me, investors will know it's automated'

💡
Response

Show side-by-side: AI draft vs their draft. AI uses their past emails as style guide. 90% of the time, they can't tell which is which. Plus, they edit every draft before sending - it's a starting point, not a replacement.

Result

After 2 weeks: 'I spend 5 minutes editing instead of 20 minutes writing from scratch. My voice is still there.'

⚠️
Fear

IR Analyst: 'I'll lose my job if AI does the data work'

💡
Response

Reframe: 'You're getting promoted from data entry to strategic analysis.' Show them time saved (16 hours/week) can be spent on competitive intelligence, investor mapping, deal sourcing - the work that gets you promoted.

Result

Analyst becomes investor intelligence specialist, gets raise after 6 months.

⚠️
Fear

Operations Lead: 'What if the system makes a mistake and sends wrong info to investors?'

💡
Response

Show approval workflow: AI drafts, humans review, nothing sends without explicit approval. Plus audit log tracks every change. More control than current process where anyone can send anything.

Result

After 30 days: 'I trust this more than our old process. I can see exactly what went out and when.'

⚠️
Fear

CEO: 'This costs too much for a 'nice to have' tool'

💡
Response

Show ROI: Team saves 61 hours/week = $4,880/month at $80/hour blended rate. System costs $2,000/month. Net savings: $2,880/month = $34,560/year. Pays for itself in 2 weeks.

Result

CEO approves pilot: 'If we save even half that, it's worth it.'

⚠️
Fear

Team: 'We're too busy to learn a new system right now'

💡
Response

Run parallel for 2 weeks: Keep doing current process, AI runs in background. Compare results. Team sees AI-generated summaries match their manual notes in 5 minutes vs 2 hours. Adoption becomes obvious.

Result

After parallel run: 'Why are we still doing this manually?' Team self-adopts.

💰

Investment & ROI

Typical payback in 2-3 weeks through time savings

Pricing

Team
Perfect for small IR teams (1-3 people)
$2,000/month
Saves ~$4,880/month in team time = 2-week payback
Department
For growing IR teams (3-8 people)
$5,000/month
Saves ~$15,600/month = 10-day payback
Enterprise
For public companies & large private (8+ people)
Custom pricing
Typical 3-5x ROI within 90 days

ROI Calculator

Current Cost
Net Savings
Payback Period
3.5 days

Proven Results

Series B SaaS120 employees, $15M ARR
225% more investors with 80% less time
Growth-stage Fintech250 employees, Series C
3 new investor intros led to $8M follow-on round
Late-stage Healthtech500+ employees, pre-IPO
Passed SEC review with complete investor communication records
🚀

From Demo to Live in 3 Weeks

From demo to production in just 3 weeks

1
Week 1
Setup & Integration
Key Activities:
  • Connect email (Gmail/Outlook), calendar, CRM
  • Import historical investor data & interactions
  • Configure team roles & permissions
  • Set up custom email templates
  • Train AI on your past communications (style learning)
Owner: Our implementation team (you review & approve)
2
Week 2
Training & Pilot
Key Activities:
  • Role-specific training: Manager (1hr), Analyst (1hr), Ops (30min)
  • Run parallel: AI drafts alongside manual process
  • Team tests AI summaries, drafts, dashboards
  • Gather feedback, adjust AI parameters
  • Refine workflows based on real usage
Owner: Joint (your team + our trainers)
3
Week 3
Full Deployment
Key Activities:
  • Switch from parallel to primary workflow
  • AI handles all new interactions automatically
  • Daily check-ins for first week (30 min)
  • Measure baseline: time saved, quality, team satisfaction
  • Optimize based on week 1 metrics
Owner: Your team (we provide support)

Enterprise deployments take 4-6 weeks for custom integrations, compliance reviews, and multi-team rollout.

Ready to Transform Your Team?

Start with a 30-day pilot or try the live demo.

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2026 Randeep Bhatia. All Rights Reserved.

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