Roadmap : Financials
Financial Outlook &
Capital Efficiency
Roadmap
Financials
AVX operates with a disciplined financial structure that balances product innovation, efficient operations and controlled burn. Our multi-product model creates diversified revenue streams, improving margins over time and providing a predictable path toward sustainable scale.
1. Financial Model Summary (Key Assumptions)
Revenue Drivers
- SaaS subscriptions (Carpetify, Floorify, Wallsfy, Artlify, TryToBuy, SeeTryBuy Viewer)
- CPQ & Visual Configurator Projects (Furniture, Marine, Modular, Industrial)
- VTO (Jewelry, Eyewear, Apparel)
- 3D/AR Production Pipeline + AI modules
- AI-powered 2D → 3D Asset Engine reduces content production cost and increases delivery speed.
- AI VTO & AI Product Discovery modules increase ARPU and SaaS expansion potential across verticals.
Team Structure
- Medium team model: 15-17 FTEs
- Engineering + AI heavy structure
- Customer Success + Sales Pods for NA & EU
Pricing Basis
Real product pricing (global benchmarks reflected)
Gross Margin Target
78%-85%, driven by SaaS expansion and scalable AI infrastructure
AI Cost Structure
- GPU compute and inference optimized through shared AI Core Layer
- AI Asset Engine reduces 3D modeling cost significantly
- AI services scale horizontally across all AVX modules, allowing shared GPU inference and reducing marginal cost per product.
Marketing & Sales
- North America & Europe GTM
- Shopify, Etsy, Magento, Trendyol, ikas ecosystem inbound
- CAC Payback target: < 9 months
2. Revenue Projection (3-5 Years)
Topline growth based on real pricing, multi-vertical expansion, and CPQ project scale.
AI-driven automation (2D→3D, guided selling, visual discovery) increases per-customer expansion and accelerates ARR growth.
Revenue mix becomes more SaaS-heavy over time as AI & Platform V1 stabilize.
3. P&L Summary (3-5 Years)
High-level, investor-friendly P&L.
| Year | Revenue | COGS | Gross Margin | OpEx | EBITDA |
|---|---|---|---|---|---|
| Y1 | $1.3M-$1.7M | Moderate | 78% | High (Team+AI+GTM) | Negative |
| Y2 | $2.8M-$3.5M | Decreases % | 80%-82% | Stable | Approaching Break-even |
| Y3 | $6M-$7.5M | Efficient | 82%-85% | Controlled | Positive |
| Y4 | $11M-$14M | Very efficient | 85% | Scalable | Strong Positive |
Break-even expected between 24-30 months, depending on CPQ volume.
AI modules start contributing to margin improvement beginning in Year 2, especially through asset automation and higher ARPU.
4. Burn Rate (Monthly Operating Cost)
2026 H1: Stabilizing with medium-sized team (15-17 FTEs)
Primary cost drivers: Headcount, AI compute, GTM activities.
AI compute cost is optimized via shared inference layer and predictable monthly GPU usage.
5. Cash Runway
Target runway: 18-24 months
Given the burn rates:
This covers:
- Team expansion
- AI R&D
- Platform V1
- Global GTM
- Enterprise onboarding
- Roomlify V2 development
- AI VTO & Asset Engine reduce operational cost in the second year.
- Contingency buffer
Runway projection ensures AVX does not need another raise before achieving ARR acceleration and early profitability signals.
6. Use of Funds (Planned Allocation)
Includes 2D→3D AI Asset Engine, AI-guided selling, VTO 2.0, and shared inference infrastructure.
Allocation focuses on accelerating AI capabilities, scaling SaaS products, and capturing multi-vertical demand efficiently.
7. Breakeven Point
AVX reaches EBITDA break-even in 24-30 months, driven by:
- High-margin SaaS expansion
- Increased CPQ ACV
- AI Asset Engine reducing 3D production cost
- Platform V1 efficiencies
- Multi-vertical cross-selling
This timeline is normal and healthy for a global SaaS/CPQ/AI platform.
8. Key Metrics (Investor KPI Snapshot)
1. Financial Model Summary (Key Assumptions)
Revenue Drivers
- SaaS subscriptions (Carpetify, Floorify, Wallsfy, Artlify, TryToBuy, SeeTryBuy Viewer)
- CPQ & Visual Configurator Projects (Furniture, Marine, Modular, Industrial)
- VTO (Jewelry, Eyewear, Apparel)
- 3D/AR Production Pipeline + AI modules
- AI-powered 2D → 3D Asset Engine reduces content production cost and increases delivery speed.
- AI VTO & AI Product Discovery modules increase ARPU and SaaS expansion potential across verticals.
Team Structure
- Medium team model: 15-17 FTEs
- Engineering + AI heavy structure
- Customer Success + Sales Pods for NA & EU
Pricing Basis
Real product pricing (global benchmarks reflected)
Gross Margin Target
78%-85%, driven by SaaS expansion and scalable AI infrastructure
AI Cost Structure
- GPU compute and inference optimized through shared AI Core Layer
- AI Asset Engine reduces 3D modeling cost significantly
- AI services scale horizontally across all AVX modules, allowing shared GPU inference and reducing marginal cost per product.
Marketing & Sales
- North America & Europe GTM
- Shopify, Etsy, Magento, Trendyol, ikas ecosystem inbound
- CAC Payback target: < 9 months
2. Revenue Projection (3-5 Years)
Topline growth based on real pricing, multi-vertical expansion, and CPQ project scale.
AI-driven automation (2D→3D, guided selling, visual discovery) increases per-customer expansion and accelerates ARR growth.
Revenue mix becomes more SaaS-heavy over time as AI & Platform V1 stabilize.
3. P&L Summary (3-5 Years)
High-level, investor-friendly P&L.
| Year | Revenue | COGS | Gross Margin | OpEx | EBITDA |
|---|---|---|---|---|---|
| Y1 | $1.3M-$1.7M | Moderate | 78% | High (Team+AI+GTM) | Negative |
| Y2 | $2.8M-$3.5M | Decreases % | 80%-82% | Stable | Approaching Break-even |
| Y3 | $6M-$7.5M | Efficient | 82%-85% | Controlled | Positive |
| Y4 | $11M-$14M | Very efficient | 85% | Scalable | Strong Positive |
Break-even expected between 24-30 months, depending on CPQ volume.
AI modules start contributing to margin improvement beginning in Year 2, especially through asset automation and higher ARPU.
4. Burn Rate (Monthly Operating Cost)
2026 H1: Stabilizing with medium-sized team (15-17 FTEs)
Primary cost drivers: Headcount, AI compute, GTM activities.
AI compute cost is optimized via shared inference layer and predictable monthly GPU usage.
5. Cash Runway
Target runway: 18-24 months
Given the burn rates:
This covers:
- Team expansion
- AI R&D
- Platform V1
- Global GTM
- Enterprise onboarding
- Roomlify V2 development
- AI VTO & Asset Engine reduce operational cost in the second year.
- Contingency buffer
Runway projection ensures AVX does not need another raise before achieving ARR acceleration and early profitability signals.
6. Use of Funds (Planned Allocation)
Includes 2D→3D AI Asset Engine, AI-guided selling, VTO 2.0, and shared inference infrastructure.
Allocation focuses on accelerating AI capabilities, scaling SaaS products, and capturing multi-vertical demand efficiently.
7. Breakeven Point
AVX reaches EBITDA break-even in 24-30 months, driven by:
- High-margin SaaS expansion
- Increased CPQ ACV
- AI Asset Engine reducing 3D production cost
- Platform V1 efficiencies
- Multi-vertical cross-selling
This timeline is normal and healthy for a global SaaS/CPQ/AI platform.
8. Key Metrics (Investor KPI Snapshot)
Not suitable for mobile use
Please use a desktop computer or tablet.
