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AI Automation Workflow

1 Automation Workflow: Slay Manual Work Execute Now

For Founders/CTOs Bleeding $5k+/Month on Manual Work to Automation Workflow


Automation Workflow

Automation Workflow

Automation Workflow

Automation Workflow

Automation Workflow

Automation Workflow

Automation Workflow

Automation Workflow

 

 

 

 

🛑 Step 0: Stop Automating Chaos

“Automating broken processes is like putting lipstick on a pig. Fix the workflow FIRST.”

The 3 Non-Negotiables with the Automation Workflow

  1. >50 repetitions/month (volume is king)
  2. Clear rules (think “if X → then Y”)
  3. Low emotional IQ neededQuick test: “Could an intern handle this with a checklist?”
The 3 Non-Negotiables
The 3 Non-Negotiables

 

💸 Step 1: Find Your Cash Bleed

1.1 Low-Hanging Fruit (We Always Start With These)

  • Customer ticket triage (tagging urgency/topics)
  • Invoice data entry → QuickBooks
  • Social media repurposing (long-form → snippets)

1.2 Calculate the Bleed

(Time per task ⨉ Frequency ⨉ $150/hr) + (Error rate ⨉ Cost per error)

Real example:

15 min/invoice ⨉ 80x/mo ⨉ $150/hr

  • (10% errors ⨉ $200) = $1,300/month wasted
Find Your Cash Bleed
Find Your Cash Bleed

🔥 Want our free Task Audit Template? → Download Here: Task Audit Template


 

🔍 Step 2: Diagnose with the Automation Workflow

Diagnose with the Automation Workflow
Diagnose with the Automation Workflow

 

🎯 Step 3: Prioritize Like a Pro

Effort vs. Impact Matrix

Only automate tasks where:

  • Impact Score (Time Saved ⨉ Strategic Value) ≥ 7/10
  • Effort Score (Dev Hours + Maintenance) ≤ 4/10
Effort vs. Impact Matrix
Effort vs. Impact Matrix

 

Crawl-Walk-Run Framework

Phase Timeline Goals
Crawl Weeks 1-2 1 workflow, <5k tasks
Walk Month 2-3 Add error handling
Run Month 4+ Predictive features

 

⚡ Step 4: Build Without Blowups

Tool Stack Cheat Sheet for Automation Workflow

Scenario Tools
<100 tasks/mo Zapier/Make
Scaling + complex logic Python/LangChain

72-Hour Validation Sprint

Ecom client example:

  1. Day 1: Built GPT-4 parser for return reasons
  2. Day 2: Auto-tagged fraud risk (89% accuracy)
  3. Day 3: Zendesk integration → 70% fewer manual reviews

⚡ Need a custom solution? → Book Technical Blueprint Session


📈 Step 5: Scale Smart

KPIs That Matter

  • ↓ Team handoffs
  • ↓ Customer resolution time
  • ↓ Compliance fines

Maintenance Reality Check

“AI models decay like bananas. Budget 20% dev time for monitoring.”

TCO Formula

[Dev cost + (Infra ⨉ 36) + (Maintenance ⨉ $150 ⨉ 3)] / (Savings ⨉ 36) > 1.5x


 

🏆 Reckap’s Battle-Tested Wins

Case Study: SaaS Onboarding

  • Automated personalized demo scheduling
  • Sales cycle 14 → 7 days
  • Result: 22% more trial → paid conversions

Security Must-Haves

  • 🔐 Zero third-party data retention
  • 🎭 PII masking before processing
  • 📝 Audit logs for all AI-human handoffs

 

🚀 Your Execution Path

3 Ways to Implement

  1. DIY: Use our stack (Python/LangChain/React)
  2. Hybrid: We build → your team maintains
  3. Done-For-You: We handle everything

Choose #3 if:

  • Errors cost $$$ or compliance headaches
  • Your dev team is overwhelmed
  • You’re tired of playing whack-a-mole with scaling issues

🎁 Free Technical Blueprint

“In 10 minutes, we’ll:

  1. Identify your top 3 cash-bleeding tasks*
  2. Map your automation roadmap—no sales pitch, just actionable insights.”

For Founders/CTOs Only (3 Spots Weekly)

Ready to automate? Book a Technical Blueprint Session or Want to tell us about business first?

“We onboard 1-2 clients/month. If you’re losing >$5k/mo to manual work, let’s talk.”


 

📚 Appendix: Reckap’s IP

Tech Stack

ROI Calculator Template

INPUTS: [Time saved/wk], [Hourly cost], [Error reduction], [Dev cost]  
OUTPUT: Monthly $ saved, Break-even point, 12-month ROI  

Failure Case Study

Legal doc review bot:

  • Mistake: Didn’t account for regional law variations
  • Result: 40% inaccuracy
  • Fix: Added jurisdiction-specific fine-tuning

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