venture/recommended-approach.md

Recommended Approach: 3-Phase Bootstrap Plan

Overview

Motto: "Slow is smooth, smooth is fast"

Philosophy: Bootstrap with minimal capital, use customer revenue to fund platform development, transition to recurring revenue model.

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Phase 1: Integration Consulting (Months 1-3)

Objective

Generate cash flow, validate market demand, build network of relationships.

Timeline

Week 1-2: Setup
Week 3-4: Outreach
Week 5-8: First pilot project
Week 9-12: Complete pilot, land second project

Services Offered

• OT/IT integration consulting
• PLC programming for data export
• Edge gateway setup (on customer hardware)
• MQTT/OPC UA configuration
• Grafana dashboard deployment
• Training and documentation

Revenue Model

• Hourly: $150-200/hour
• Project: $15k-40k (100-200 hours)
• Retainer: $2k-5k/month (optional support)

Infrastructure

NONE - Deploy on customer hardware:

• Raspberry Pi 4 or old industrial PC (customer buys)
• Ubuntu Server + Docker/LXC (free)
• Mosquitto MQTT + InfluxDB + Grafana (free, open source)
• Node-RED for PLC integration (free)

Capital Requirements

Total: $500

• LLC filing: $100-300
• Basic website (Carrd/WordPress): $0-200
• Business cards: $50
• LinkedIn Premium: $0 (optional)

Activities

Week 1-2: Foundation

• Register LLC (1-2 hours, $100-300)
• Set up website (4-6 hours, $0-200)
  • Service description
  • Case study section (empty initially)
  • Contact form
  • Bio highlighting OT + cloud expertise
• Update LinkedIn profile (1 hour)
  • "OT/IT Integration Consultant"
  • Headline: "I help manufacturers bridge PLC data to dashboards"
• Create contact list (20+ from controls engineering days)

Week 3-4: Outreach

• Email/call 20 contacts (5 per week)
• Message template:

  "Hey [Name], after 13 years programming PLCs, I spent the last 4 years learning cloud engineering. Now I'm helping manufacturers get visibility into production data without expensive cloud platforms. Know anyone struggling with this?"

• Target: 3-5 discovery calls
• Join local ISA chapter (optional)

Week 5-8: First Pilot

• Land pilot project: $5k-10k (discounted)
• Scope: Single production line, basic monitoring
  • PLC data collection (Modbus/OPC UA)
  • MQTT broker on Raspberry Pi
  • Grafana dashboards (3-5 views)
  • Alert configuration
• Document EVERYTHING
  • Before/after metrics
  • Technical architecture
  • Customer testimonial
• Deliverables:
  • Working edge gateway
  • 3-5 Grafana dashboards
  • Alert rules configured
  • 2-4 hours of training
  • Documentation for maintenance

Week 9-12: Validate & Scale

• Complete pilot project
• Get written testimonial
• Take photos/screenshots
• Write case study
• Publish to LinkedIn + website
• Ask pilot customer for 2-3 referrals
• Land second project at full price ($20k-40k)
• Begin prospecting for Phase 2 recurring customers

Success Metrics (Phase 1)

• 2-3 completed consulting projects
• $20k-45k revenue generated
• 5+ discovery calls completed
• 1-2 case studies published
• 10+ new LinkedIn connections
• 3-5 warm prospects for Phase 2

Expected Outcomes

• Revenue: $20k-45k in 90 days
• Profit: ~$19k-43k (95% margin)
• Network: 20+ new manufacturing contacts
• Validation: Proven demand for services
• Foundation: Customer base for Phase 2 transition

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Phase 2: Edge Monitoring Platform (Months 4-9)

Objective

Transition from project-based to recurring revenue, deploy multi-tenant infrastructure.

Timeline

Month 4-6: Build platform, convert 2-3 consulting clients
Month 7-9: Add 3-5 new monitoring customers, refine product

Services Offered

Consulting (continued, reduced):

• 1-2 projects/month for cash flow
• Integration work for monitoring customers

New - Monitoring Platform:

• Edge monitoring as a service
• Setup + monthly subscription
• Remote management
• Alert management
• Data backup and retention

Revenue Model

Hybrid:

• Consulting: $10k-20k/month (declining)
• Monitoring setup fees: $5k-10k per customer
• Monitoring recurring: $0 → $10k/month (growing)

Infrastructure

GTHost Dedicated Server #1:

Configuration:
├── 8 cores, 32GB RAM, 1TB SSD
├── Estimated cost: $100-150/month
├── Capacity: 8-10 customers
└── Revenue potential: $12k-30k/month

Tech Stack:

• Ubuntu Server 24 LTS
• LXC for container isolation (per customer)
• MQTT broker per container
• InfluxDB per container (or shared with DB per customer)
• Grafana (shared with customer-specific dashboards)
• Automated backup system
• Monitoring and alerting (UptimeRobot, Prometheus)

Capital Requirements

Total: ~$1,000

• GTHost server: $100-150/month × 2 months
• Development time: Nights/weekends (sweat equity)
• Funded from Phase 1 consulting revenue

Activities

Month 4-5: Platform Development

• Provision GTHost server ($5/day trial first)
• Build LXC container template
  • MQTT broker (Mosquitto)
  • InfluxDB instance
  • Grafana user + dashboards
  • Backup scripts
• Create provisioning automation
  • New customer onboarding script
  • Container creation
  • Credential generation
  • DNS/subdomain setup
• Build simple web portal
  • Customer login
  • Dashboard links
  • Support ticket system
  • Billing integration (Stripe)
• Set up monitoring
  • Server health monitoring
  • Customer container monitoring
  • Alert system for failures
• Documentation
  • Customer onboarding guide
  • Internal runbook
  • Support procedures

Month 5-6: First Customers

• Approach 2-3 existing consulting clients
• Pitch: "I've built a monitoring platform. Want to be a pilot customer for $1k/month?"
• Deploy for first 2 customers
• Gather feedback, iterate
• Test backup/restore procedures
• Validate multi-tenant isolation
• Begin marketing monitoring service

Month 7-9: Growth & Refinement

• Add 3-5 new monitoring customers
• Continue 1-2 consulting projects/month (cash flow)
• Refine platform based on feedback
• Build case studies (monitoring-specific)
• Automate more operations
• Document standard procedures
• Plan for second server (if needed)

Success Metrics (Phase 2)

• GTHost server deployed and stable
• 5-8 monitoring customers live
• $10k-15k MRR achieved
• Multi-tenant architecture proven
• 99.5%+ uptime maintained
• Customer churn <10%
• 3+ new case studies published

Expected Outcomes

• Month 6 Revenue: $17k ($15k consulting + $2k MRR)
• Month 9 Revenue: $20k ($10k consulting + $10k MRR)
• Infrastructure Cost: $150/month
• Profit Margin: 85-90%
• Platform: Production-ready, scalable
• Foundation: Ready for Phase 3 premium features

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Phase 3: GPU-Powered AI Features (Months 10-18)

Objective

Add premium AI-powered features for differentiation and margin expansion.

Timeline

Month 10-12: Build AI infrastructure, launch premium tier
Month 13-18: Convert customers, add new premium customers

Services Offered

Basic Tier (existing):

• Edge monitoring
• Dashboards and alerts
• $1.5k-2k/month

Premium AI Tier (new):

• Predictive maintenance
• Anomaly detection
• Computer vision quality inspection
• Advanced analytics
• $4k-8k/month

Revenue Model

Fully Recurring:

• Basic customers: $1.5k × 8-10 = $12k-15k/month
• Premium customers: $5k × 4-5 = $20k-25k/month
• Consulting (occasional): $5k/month
• Total: $37k-45k/month

Infrastructure

Server #1 (Basic tier):

• 8 cores, 32GB, 1TB
• 8-10 customers
• $100-150/month

Server #2 (Premium AI tier):

Configuration:
├── 16 cores, 64GB RAM
├── NVIDIA Tesla P4 8GB GPU
├── 2TB NVMe SSD
├── Estimated cost: $350-450/month
├── Capacity: 3-5 premium customers
└── Revenue potential: $15k-40k/month

Capital Requirements

Total: ~$3,000

• GPU server: $400/month × 3 months
• ML model development time
• Funded from Phase 2 profits

Activities

Month 10-11: AI Infrastructure

• Provision GTHost server with Tesla P4 GPU
• Install ML frameworks
  • TensorFlow or PyTorch
  • Scikit-learn
  • ONNX Runtime (optimized inference)
• Build predictive maintenance models
  • Anomaly detection (vibration, temperature)
  • Failure prediction
  • Remaining useful life (RUL)
• Computer vision setup (if pursued)
  • Object detection
  • Quality inspection
  • Defect classification
• Test GPU inference performance
• Create premium tier documentation

Month 12: Premium Launch

• Select 2 customers to upgrade (beta pricing)
• Deploy AI features
• Gather data for model training
• Refine models based on customer data
• Measure ROI for customers
• Create case studies showing value

Month 13-18: Scale Premium

• Convert 2-3 more customers to premium
• Market premium tier to prospects
• Hire first contractor ($3k-5k/month)
  • Customer support
  • Deployment assistance
  • Basic troubleshooting
• Formalize processes
• Build sales pipeline
• Plan for additional servers if needed

Success Metrics (Phase 3)

• GPU server operational
• 4-6 premium tier customers
• $35k+ MRR total
• First employee/contractor hired
• 95%+ customer satisfaction
• 3+ AI-specific case studies
• ROI demonstrated for customers

Expected Outcomes

• Month 18 Revenue: $40k-50k/month
• Infrastructure Cost: $500-600/month (2 servers)
• Contractor Cost: $5k/month
• Net Profit: $34k-44k/month
• Annual Run Rate: $480k-600k
• Positioning: Premium AI-powered industrial IoT platform

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Transition Strategy Between Phases

Phase 1 → Phase 2

Trigger: When you have:

• 2-3 completed consulting projects
• $20k+ in the bank
• 2-3 customers willing to pilot monitoring

Transition:

• Reduce consulting to 50% time
• Invest 50% time in platform development
• Use consulting cash to fund infrastructure
• Convert consulting customers to monitoring

Phase 2 → Phase 3

Trigger: When you have:

• 5+ monitoring customers ($10k+ MRR)
• Consistent $20k+/month total revenue
• Stable platform with <5% churn
• Cash reserves to fund GPU server for 3 months

Transition:

• Add GPU server (funded from Phase 2 profits)
• Build AI features
• Beta test with 2 willing customers
• Launch premium tier
• Hire first contractor to handle growth

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Risk Mitigation

Phase 1 Risks

Risk: Can't find customers
Mitigation: 13 years of network, LinkedIn outreach, local ISA chapter

Risk: Projects take too long
Mitigation: Scope small (40-80 hours max), resist feature creep

Risk: Customers don't pay
Mitigation: 50% deposit upfront, milestone payments

Phase 2 Risks

Risk: Platform technical failures
Mitigation: Start with 2-3 customers, test thoroughly, backup systems

Risk: Can't transition consulting customers
Mitigation: Offer discounted pilot pricing, add value not available before

Risk: Infrastructure costs escalate
Mitigation: Multi-tenant architecture, start with basic GTHost config

Phase 3 Risks

Risk: AI features don't deliver value
Mitigation: Beta test with willing customers, measure ROI, iterate

Risk: GPU costs too high
Mitigation: Start with 2-3 premium customers to fund server

Risk: Can't hire good contractor
Mitigation: Use Upwork/Fiverr first, hire part-time before full-time

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Key Success Factors

1. Start Small: $500 capital, basic consulting
2. Customer-Funded: Use their money to build platform
3. Validate First: Consulting proves demand before platform build
4. Recurring Focus: Always transition to subscriptions when possible
5. Edge-First: Maintains AWS non-compete compliance
6. Iterative: Build → Test → Refine, don't try to be perfect
7. Network Effects: Each customer = 2-3 referrals
8. Documentation: Case studies critical for next phase

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Timeline Summary

Month	Phase	Focus	Revenue	Profit
1-2	1	Setup, first project	$5k	$4.5k
3	1	Second project	$20k	$19k
4-5	2	Platform dev	$17k	$16k
6	2	First monitoring customers	$20k	$19k
9	2	Growing MRR	$20k	$19k
12	3	Premium launch	$25k	$23k
18	3	Full premium	$40k	$34k

Cumulative 18 months: ~$350k revenue, ~$300k profit

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Next Steps

See go-to-market.md for detailed 90-day action plan.

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Last Updated: December 2025