## 28. Detailed Project Roadmap & Milestones

*For strategic prototype roadmap with high-level phases, see [24_prototype_roadmap.md](24_prototype_roadmap.md)*

### Executive Summary
18-month roadmap from concept to market validation with €2.5M seed funding. Focus on de-risking core assumptions while building scalable platform based on Go 1.25 stack, graph-based matching engine, and progressive value delivery through resource matching + service marketplace.

**Financial Projections (Revised)**: Initial projections were overly optimistic. Revised targets align with industry benchmarks for seed-stage B2B SaaS:
- **Month 6**: €8k-€12k MRR (vs. optimistic €25k)
- **Month 12**: €25k-€40k MRR (vs. optimistic €150k)
- **Month 18**: €50k-€80k MRR (€600k-€960k ARR) for Series A readiness
- **Conversion Rate**: 5-8% free-to-paid (industry average: 2-5%, exceptional: 10-15%)
- **Target**: Series A readiness (€3M+ ARR typically required) vs. IPO-readiness in original projections

### Phase 1: Foundation & MVP (Months 1-3) - €400k Budget
**Goal**: Validate core assumptions, build heat-matching MVP with manual entry

#### Month 1: Core Setup & Technical Foundation
**Deliverables:**
- Team assembly (8 engineers: 4 backend, 2 frontend, 1 DevOps, 1 data; 2 domain experts, 1 BD)
- Development environment setup (Docker Compose, local Neo4j/PostgreSQL)
- Infrastructure provisioning (AWS EKS/GCP GKE, managed Neo4j/PostgreSQL)
- Legal entity formation and seed documents
- **ADR Framework**: Architecture Decision Records setup and initial decisions
- **Go 1.25 Stack Setup**: Gin/Fiber selection, Neo4j driver, PostgreSQL/PostGIS with pgx
- **Open Standards Foundation**: NGSI-LD API integration (2-3 weeks) for smart city interoperability
- **Message Queue**: NATS or Redis Streams selection (not Kafka for MVP)
- **Security Foundation**: JWT, OAuth2, RBAC implementation
- Basic CI/CD pipeline (GitHub Actions)

**Technical Decisions (ADRs):**
- Graph database: Neo4j (migration path to TigerGraph if >10B nodes)
- HTTP framework: Gin (consider Fiber if low latency critical)
- Message queue (MVP): NATS or Redis Streams
- Go 1.25 experimental features: Build with feature flags, fallback to Go 1.23 if not production-ready

**Success Metrics:**
- Team fully onboarded and productive
- All core infrastructure deployed
- Basic CI/CD pipeline operational
- Development environment documented and replicable

**Risks:** Team hiring delays, infrastructure complexity, Go 1.25 experimental feature availability
**Mitigation:** Pre-hire key technical roles, use managed services, feature flags for experimental features

#### Month 2: Data Architecture & Matching Engine Core
**Deliverables:**
- **Graph Database Setup**: Neo4j cluster with APOC library
- **Spatial Database Setup**: PostgreSQL + PostGIS for geospatial queries
- **Hybrid Architecture**: Neo4j (relationships) + PostGIS (spatial queries) synchronization
- **Data Ingestion Pipelines**: Manual entry API, CSV upload, basic validation
- **Seed Data Collection**: Berlin industrial park data (public registries, building footprints)
- **Matching Engine Prototype**: 
  - Spatial pre-filtering (PostGIS 5km radius)
  - Quality matching (temperature compatibility)
  - Temporal overlap calculation
  - Economic scoring (basic cost-benefit)
- **Resource Plugin Architecture**: Heat exchange plugin (MVP resource type)
- **Caching Layer**: Redis for match results (15-minute TTL)

**Success Metrics:**
- 50 businesses with resource flow data (seed data + manual entry)
- Basic matching engine finds 10+ viable heat matches
- Data ingestion reliability >95%
- Matching query latency <2s (p95)

**Technical Milestones:**
- Graph database schemas deployed (Business, Site, ResourceFlow nodes)
- Spatial indexes created and tested
- Basic REST API endpoints functional
- Seed data quality validation completed

#### Month 3: MVP Core Features & Pilot Launch
**Deliverables:**
- **Heat Flow Matching**: Manual entry only, heat resource type focus
- **Map Visualization**: React + Mapbox GL, resource flows as colored dots, match connections
- **Business Registration**: Simple onboarding flow (15 minutes to complete)
- **Match Notification System**: Basic email notifications (WebSocket in Phase 2)
- **Service Marketplace Foundation**: Basic structure for future expansion
- **Privacy-First Design**: Public/network-only/private data tiers
- **Free Tier**: See + Match functionality (drive network effects)

**Success Metrics:**
- 20 businesses registered in pilot (Berlin industrial + hospitality)
- 15 heat matches identified and contacted
- 3 expressions of interest for implementation
- ≥60% data completion rate
- ≥5 actionable matches per business

**User Testing:**
- Pilot user feedback sessions (10-15 businesses)
- UI/UX validation with target users
- Feature prioritization based on user input
- Cold start problem validation

**Pilot Selection:**
- Vertical focus: "Heat reuse in Berlin industrial + hospitality sector"
- "Cheap-to-act" resources focus: Low-capex matches (shared services, waste pickup)
- Manual data seeding from public sources

### Phase 2: MVP Expansion & Revenue (Months 4-6) - €500k Budget
**Goal**: Expand to multi-resource, automated ingestion, service marketplace, initial revenue

#### Month 4: Multi-Resource Support & Service Marketplace
**Deliverables:**
- **Water Resource Plugin**: Wastewater reuse, water quality matching
- **Waste Resource Plugin**: Material exchange, by-product reuse
- **Economic Calculation Engine**: 
  - NPV, IRR, payback period calculations
  - Sensitivity analysis
  - Scenario modeling
- **Enhanced Matching Algorithms**:
  - Multi-criteria scoring (quality, temporal, economic, distance, trust)
  - Ranking engine with diversity consideration
  - Fallback matching (relaxed constraints)
- **Service Marketplace MVP**: 
  - Maintenance services matching
  - Shared service opportunities
  - Group buying foundation
- **Privacy-Preserving Matching**: Anonymized discovery, network-only visibility

**Success Metrics:**
- 3 resource types fully supported (heat, water, waste)
- Economic calculations accurate to ±10%
- 50% increase in match quality
- Service marketplace: 5-10 service providers registered

**Technical Milestones:**
- Resource plugin architecture proven (3 plugins working)
- Economic calculator validated against manual calculations
- Matching algorithm performance maintained (<2s p95 latency)

#### Month 5: Automated Data Ingestion & Event-Driven Architecture
**Deliverables:**
- **Event-Driven Architecture**: 
  - NATS/Redis Streams for event processing
  - Event handlers for ResourceFlow changes
  - Incremental matching (only affected subgraphs)
- **ERP/SCADA API Integrations**: 
  - SAP, Oracle basic integration (REST API)
  - OPC UA protocol support
- **IoT Device Connectivity**: 
  - Modbus RTU/TCP support
  - MQTT broker integration
  - OGC SensorThings API (Phase 2 priority from prototype roadmap)
- **Data Quality Validation Pipeline**: 
  - Precision levels (rough/estimated/measured)
  - Device-signed validation
  - Data quality scoring
- **Background Processing**: Go workers with channel-based processing

**Success Metrics:**
- 80% reduction in manual data entry (for early adopters with integrations)
- Data freshness <24 hours
- Ingestion success rate >98%
- Event processing latency <100ms (p95)

**Migration Strategy:**
- Document Kafka migration path (trigger: 1000+ businesses)
- Monitor NATS/Redis Streams performance
- Prepare migration plan for scale phase

#### Month 6: Revenue Generation & Performance Optimization
**Deliverables:**
- **Subscription Billing System**: 
  - Stripe integration
  - Free/Basic/Business/Enterprise tiers
  - Usage-based billing foundation
- **Lead Fee Collection**: Commission tracking for facilitated introductions
- **Basic Analytics Dashboard**: 
  - Business resource flow analytics
  - Match success metrics
  - Environmental impact (CO₂ savings)
- **Performance Optimization**:
  - Query result caching (Redis)
  - Graph query optimization (Cypher profiling)
  - Materialized views for common match patterns
- **Go 1.25 Features Evaluation**: 
  - JSON v2 performance testing (if production-ready)
  - GreenTea GC evaluation (if production-ready)
  - Fallback to Go 1.23 stable features if needed

**Success Metrics:**
- 30-50 paying customers (free + paid tiers) - realistic for B2B industrial SaaS
- €8k-€12k monthly recurring revenue (MRR) - conservative estimate
- Platform performance: <2s response times (p95)
- Customer satisfaction >4/5 stars
- Cache hit rate >70%
- **Conversion Rate**: 5-8% free-to-paid (industry average: 2-5%, exceptional: 10-15%)

**Go-to-Market:**
- Launch in Berlin industrial ecosystem
- Partnership agreements with utilities (data + distribution)
- Initial marketing campaign (content marketing, LinkedIn)
- Municipal dashboard pilot (1-2 cities, free for businesses, paid for cities)

### Phase 3: Enterprise Features & Scale (Months 7-12) - €900k Budget
**Goal**: Enterprise readiness, knowledge graph integration, international expansion

#### Months 7-8: Advanced Platform Features & Knowledge Graph
**Deliverables:**
- **Real-Time WebSocket Notifications**: 
  - Match updates, new opportunities
  - Live resource flow changes
  - Go WebSocket server (gorilla/websocket or nhooyr.io/websocket)
- **Advanced Analytics and Reporting**: 
  - Predictive matching recommendations
  - Scenario analysis tools
  - ESG impact reporting (CSRD compliance)
- **API Ecosystem Foundation**: 
  - REST API v1 stable
  - API documentation (OpenAPI/Swagger)
  - Webhook system for third-party integrations
  - Rate limiting and API key management
- **Mobile PWA Launch**: 
  - Progressive Web App with offline support
  - Push notifications
  - Mobile-optimized map interface
- **Knowledge Graph Integration** (Phase 2 priority from architecture):
  - Semantic matching enhancement
  - Taxonomy integration (EWC, NACE codes)
  - Process compatibility matrices
  - Expected: 30-40% match quality improvement

**Success Metrics:**
- 150-200 active businesses (realistic growth from 30-50 paying to ~150 total)
- €25k-€40k monthly revenue (MRR) - conservative but achievable
- API adoption by 5-10 enterprises (early adopters)
- Mobile usage >20% of sessions
- Knowledge graph: 10-15% improvement in match quality (initial)

#### Months 9-10: Enterprise Integrations & Multi-Tenancy
**Deliverables:**
- **GraphQL API Implementation**: 
  - gqlgen schema-first approach
  - Flexible querying for enterprise clients
  - Subscriptions for real-time updates
- **Advanced ERP Integrations**: 
  - SAP (RFC, OData)
  - Oracle (REST, SOAP)
  - Microsoft Dynamics
  - Integration marketplace
- **Multi-Tenancy Architecture**: 
  - Data isolation (schema-per-tenant or row-level security)
  - Tenant management dashboard
  - Resource usage tracking per tenant
- **Advanced Security Features**: 
  - SOC2 compliance preparation
  - Advanced audit logging
  - Data encryption at rest and in transit
  - RBAC enhancements
- **Message Queue Migration**: 
  - Evaluate Kafka migration if scale requires (>1000 businesses)
  - NATS → Kafka migration plan execution if triggered

**Success Metrics:**
- 15-25 enterprise customers (realistic for enterprise sales cycle)
- €80k-€120k monthly revenue (MRR) - B2B enterprise SaaS typically slower to scale
- Integration success rate >95%
- SOC2 Type I compliance preparation (certification takes 6-12 months)
- Multi-tenant architecture validated

#### Months 11-12: International Expansion & Regional Features
**Deliverables:**
- **Multi-Language Support**: 
  - i18n framework (English, German, Dutch, Swedish)
  - Localized UI and content
  - Regional data formats
- **Regional Data Residency**: 
  - EU data residency options (GDPR compliance)
  - Cross-border data transfer controls
  - Data localization settings
- **International Utility Partnerships**: 
  - Netherlands (regional utilities)
  - Nordics (district heating networks)
  - Partnership revenue sharing model
- **Market Expansion**: 
  - Netherlands market entry
  - Nordics pilot (Sweden, Denmark)
  - Regional regulatory compliance (country-specific)

**Success Metrics:**
- 300-400 total businesses across 3 countries (realistic for international expansion)
- €150k-€200k monthly revenue (MRR) - conservative growth trajectory
- 100-150% YoY growth rate (more realistic for seed stage)
- 2-3 new market entries validated (Netherlands + 1-2 Nordics)
- Regional partnerships: 3-5 utility agreements (partnerships take time to develop)

### Phase 4: Scale & Optimization (Months 13-18) - €700k Budget
**Goal**: Full scale operations, AI-enhanced matching, profitability

#### Months 13-15: Advanced AI & Automation
**Deliverables:**
- **ML-Powered Match Recommendations**: 
  - GraphRAG integration (Neo4j GraphRAG) for natural language queries
  - Predictive matching (anticipate resource needs)
  - Pattern recognition (recurring opportunities)
- **Automated Lead Qualification**: 
  - Match quality scoring automation
  - Lead conversion probability prediction
  - Automated prioritization
- **Predictive Analytics**: 
  - Resource availability forecasting
  - Demand prediction
  - Scenario analysis with Monte Carlo simulation
- **Advanced Matching Algorithms**: 
  - Multi-party matching (3+ businesses)
  - Network optimization algorithms
  - Agent-based modeling for network simulation

**Success Metrics:**
- 70% improvement in match quality (vs. baseline)
- Automated lead conversion rate >40%
- Customer lifetime value increased by 25%
- GraphRAG: Natural language query support operational

#### Months 16-18: Full Market Penetration & Platform Maturity
**Deliverables:**
- **Complete API Ecosystem**: 
  - GraphQL + REST API
  - WebSocket real-time APIs
  - White-label API access
  - Third-party developer portal
- **White-Label Platform**: 
  - Customizable branding per tenant
  - Co-branded municipal dashboards
  - Utility partner white-label solutions
- **Advanced Analytics Platform**: 
  - Business intelligence dashboards
  - Custom report builder
  - Data export (GDPR compliant)
  - API for analytics integration
- **Strategic Partnerships**: 
  - Municipal partnerships (10+ cities)
  - Utility partnerships (5+ major utilities)
  - Facilitator marketplace expansion (50+ facilitators)
  - Technology partnerships (ERP vendors)

**Success Metrics:**
- 800-1,200 businesses registered (realistic for 18-month seed stage)
- €300k-€400k monthly revenue (MRR) - €3.6M-€4.8M ARR
- 75-80% gross margins (realistic after infrastructure costs)
- 5-8 strategic partnerships (partnerships develop slowly)
- Path to Series A validated (€3M+ ARR typically needed for Series A)

### Critical Path Dependencies

#### Technical Dependencies
1. **Data Quality** → Matching Accuracy → User Adoption
2. **Performance** → Scalability → Enterprise Adoption
3. **Security** → Trust → Large Customer Acquisition
4. **Graph Database Setup** → Matching Engine → MVP Launch
5. **Go 1.25 Stack** → Backend Performance → User Experience
6. **Knowledge Graph Integration** → Match Quality → Enterprise Value
7. **Event-Driven Architecture** → Real-Time Features → User Engagement

#### Business Dependencies
1. **Seed Data** → Initial Matches → User Validation
2. **Utility Partnerships** → Data Access → Market Reach
3. **First Customers** → Case Studies → Market Momentum
4. **Service Marketplace** → Regular Engagement → Network Effects
5. **Municipal Partnerships** → Free Business Access → Network Growth

### Risk Mitigation Milestones

#### Monthly Risk Reviews
- **Technical Risks**: Performance, security, scalability, Go 1.25 experimental feature availability
- **Market Risks**: Adoption, competition, regulation, cold start problem
- **Financial Risks**: Burn rate, revenue projections, CAC/LTV ratio
- **Data Risks**: Data quality, privacy compliance, GDPR adherence

#### Pivot Triggers (Revised with Realistic Targets)
- **Month 3**: <10 businesses registered → Pivot to different market or vertical
- **Month 6**: <€5k MRR (€60k ARR run rate) → Focus on enterprise sales, adjust pricing
- **Month 9**: <€15k MRR (€180k ARR run rate) → Restructure business model, evaluate partnerships
- **Month 12**: <€30k MRR (€360k ARR run rate) → Pivot to municipal/utility-focused model
- **Month 18**: <€50k MRR (€600k ARR run rate) → Consider seed extension or pivot strategy

#### Early Warning Signals
- **Week 4**: <20 businesses signed up for pilot → Accelerate seed data collection
- **Month 4**: <40% data completion rate → Simplify onboarding, add support
- **Month 6**: No implemented connections → Focus on low-capex matches
- **Month 6**: Conversion rate <3% (free-to-paid) → Improve value proposition, pricing
- **Month 8**: CAC > 3x monthly revenue per customer → Reduce marketing spend, improve conversion
- **Month 9**: Churn rate >10% monthly → Address product-market fit issues

### Resource Allocation

#### Engineering Team (60% of budget)
- **Backend Engineers (4)**: 
  - Go 1.25 APIs, matching engine, graph database
  - Event-driven architecture, message queue integration
  - Economic calculator, plugin architecture
- **Frontend Engineers (2)**: 
  - React + Next.js, Mapbox visualization
  - PWA development, real-time WebSocket UI
- **DevOps Engineer (1)**: 
  - Kubernetes infrastructure, CI/CD pipelines
  - Monitoring (Prometheus, Grafana), infrastructure automation
- **Data Engineer (1)**: 
  - Data pipelines, ETL, analytics
  - Knowledge graph integration, ML model deployment

#### Business Team (20% of budget)
- **Business Development (1 person)**: 
  - Utility partnerships, municipal sales
  - Channel partner development
- **Domain Experts (2 people)**: 
  - Industrial symbiosis facilitation
  - Regulatory compliance (EU, country-specific)
- **Operations/Customer Success (1 person)**: 
  - Customer onboarding, support
  - Facilitator marketplace management

#### Infrastructure & Tools (20% of budget)
**Note**: Infrastructure costs scale with usage. Below are peak estimates for Month 18.

**Cloud Costs** (scaling from Month 1 to Month 18):
- **Month 1-6**: €2k-€5k/month (development, MVP scale: 50-100 businesses)
  - AWS/GCP: €1.5k-€3k/month (EKS/GKE, managed databases small instances)
  - Neo4j: €500-€1k/month (Community or small Enterprise)
  - PostgreSQL RDS: €300-€500/month (small instances)
  - Redis: €200-€400/month (small cache)
- **Month 7-12**: €5k-€10k/month (growth phase: 200-400 businesses)
  - AWS/GCP: €3k-€6k/month
  - Neo4j: €1k-€2k/month
  - PostgreSQL RDS: €500-€1k/month
  - Redis: €400-€800/month
- **Month 13-18**: €10k-€15k/month (scale phase: 800-1,200 businesses)
  - AWS/GCP: €6k-€9k/month
  - Neo4j: €2k-€3k/month (Enterprise scaling)
  - PostgreSQL RDS: €1k-€2k/month
  - Redis: €800-€1.5k/month

**Third-party Services**:
- **Monitoring** (Datadog/New Relic): €500-€2k/month (scales with infrastructure)
- **Security** (Vault, secrets management): €200-€500/month
- **Payments** (Stripe): Transaction-based (typically 2.9% + €0.30 per transaction)
- **Mapbox**: €0 (free tier: 50k loads/month), then €200-€500/month at scale

**Development Tools**:
- **GitHub Enterprise**: €4/user/month (or GitHub Pro at €4/user/month)
- **IDEs**: €100-€200/month (JetBrains licenses, etc.)
- **CI/CD**: Included in GitHub or €50-€200/month (CircleCI, etc.)
- **Artifact Repositories**: €50-€100/month

**Total Infrastructure Costs** (18 months):
- **Conservative Estimate**: €120k-€180k (assumes gradual scaling)
- **Realistic Peak**: €180k-€270k (if growth exceeds expectations)

### Success Metrics Dashboard

#### Daily Metrics
- Active users, API calls, error rates
- Match generation, user engagement
- Revenue, customer acquisition

#### Weekly Metrics
- Customer satisfaction, feature usage
- Performance benchmarks, uptime
- Market feedback, competitor analysis

#### Monthly Metrics
- Revenue growth, customer retention
- Market expansion, partnership progress
- Technical debt, code quality
- Team productivity, burn rate

### Exit Strategy Milestones

#### Year 1: Product-Market Fit (Realistic Targets)
- **50-100 paying customers** (conservative but achievable for B2B industrial SaaS)
- **€300k-€600k total revenue** (€250k-€500k ARR) - realistic for seed stage first year
- Clear unit economics (LTV/CAC ratio >3-5x target, 70x would be exceptional)
- Validated market demand and willingness to pay
- 3-5 implemented connections proving ROI
- Service marketplace operational (basic version)

**Note**: Most seed-stage B2B SaaS companies take 12-18 months to reach €500k ARR. €2M ARR in Year 1 would be exceptional (top 5% of startups).

#### Year 2: Scale Validation (If Product-Market Fit Achieved)
- **200-400 customers** (growth from proven model)
- **€1.5M-€3M total revenue** (€1.2M-€2.5M ARR) - 4-5x growth if PMF achieved
- International presence (2-3 countries)
- Operational excellence and repeatable processes
- 5-8 utility partnerships (realistic timeline)
- Knowledge graph showing measurable match quality improvement

#### Year 3: Exit Preparation (If Scale Validated)
- **600-1,000 customers** (realistic growth trajectory)
- **€4M-€6M total revenue** (€3.5M-€5M ARR) - Series A territory
- 75-80% gross margins, approaching profitability
- Strategic partnerships (utilities, municipalities, ERP vendors)
- Competitive moat established (network effects, data accumulation)
- Ready for Series A fundraising (€3M+ ARR typically minimum)

### Contingency Plans

#### Technical Failure Scenarios
- **Database Performance**: Fallback to simplified matching
- **API Downtime**: Cached responses, maintenance pages
- **Data Loss**: Comprehensive backups, recovery procedures

#### Business Failure Scenarios
- **Low Adoption**: Pivot to enterprise-focused model
- **Competition**: Differentiate through partnerships
- **Regulatory Changes**: Adapt compliance requirements

#### Financial Failure Scenarios
- **Slow Revenue**: Extend runway through strategic partnerships
- **High Burn Rate**: Reduce scope, focus on core features
- **Funding Delay**: Bootstrap through early revenue

---

### Implementation Timeline Visualization

```
Month 1-3: Foundation & MVP
├── Team & Infra Setup (Go 1.25, Neo4j, NATS/Redis)
├── Data Architecture (Graph + Spatial)
├── Heat Matching MVP (manual entry)
└── Pilot Launch (Berlin industrial + hospitality)

Month 4-6: Expansion & Revenue
├── Multi-Resource Support (water, waste)
├── Service Marketplace MVP
├── Automated Ingestion (ERP, IoT)
└── Revenue Generation (subscriptions, leads)

Month 7-12: Enterprise & Scale
├── Knowledge Graph Integration
├── Advanced Features (WebSocket, analytics)
├── Enterprise Integrations (GraphQL, ERP)
├── Message Queue Migration (Kafka if needed)
└── International Expansion (Netherlands, Nordics)

Month 13-18: AI & Market Penetration
├── ML/AI Features (GraphRAG, predictive)
├── White-Label Platform
└── Strategic Partnerships
```

### Technology Evolution Timeline

#### MVP Phase (Months 1-6)
- **Message Queue**: NATS or Redis Streams
- **Go Version**: 1.25 with feature flags (fallback to 1.23)
- **Graph DB**: Neo4j Community/Enterprise
- **Deployment**: Kubernetes (EKS/GKE)

#### Scale Phase (Months 7-12)
- **Message Queue**: Evaluate Kafka migration (trigger: 1000+ businesses)
- **Go Version**: 1.25 stable features, evaluate experimental (JSON v2, GreenTea GC)
- **Graph DB**: Neo4j Enterprise (scaling), consider TigerGraph evaluation
- **Knowledge Graph**: Phase 2 implementation

#### Enterprise Phase (Months 13-18)
- **Message Queue**: Kafka if scale requires
- **Go Version**: Latest stable with production-ready experimental features
- **Graph DB**: Neo4j Enterprise or TigerGraph at scale
- **AI/ML**: GraphRAG, predictive analytics operational

**Total Timeline**: 18 months to product-market fit validation
**Total Budget**: €2.5M seed funding
**Success Criteria (Revised - Realistic)**: 
- **800-1,200 businesses** registered (vs. optimistic 5,000)
- **€3.6M-€4.8M ARR** (€300k-€400k MRR) vs. optimistic €21M ARR
- **75-80% gross margins** (vs. optimistic 82%)
- **Series A readiness** (€3M+ ARR typically required) vs. IPO-readiness

**Realistic Growth Path**:
- Month 6: €8k-€12k MRR (€100k-€150k ARR run rate)
- Month 12: €25k-€40k MRR (€300k-€480k ARR run rate)
- Month 18: €50k-€80k MRR (€600k-€960k ARR run rate)

**Note**: The original projections (€21M ARR Year 3, 5,000 customers) would place Turash in the top 1% of B2B SaaS startups. The revised projections are more realistic for seed-stage companies while still being ambitious. Exceptional performance could exceed these targets.