WITH FUSEBOX OS, YOU CAN
Scale energy flexibility with lower TCO
3 paths to flexibility at scale
Architecture determines whether growth compounds cost or compounds efficiency. The right model reduces not only upfront investment and operating costs, but also long-term development burden and structural lock-in.
Total cost of ownership (TCO) comparison
| Interoperable Fusebox OS | Single-vendor stack | Own VPP + EMS | |
|---|---|---|---|
| Feature depth | Modular building blocks via APIs and integrations | Broad but constrained extensions | Anything you build |
| Time to production | Weeks–months | 4–12 months | 9–30 months |
| Upfront investment (Year 1) | €0.05–€0.6M | €0.3–€2.5M | €1.2–€5M |
| Operating costs (annual) | €0.1–€0.6M/y | €0.8–€3.0M/yr | €0.8–€4.5M/yr |
| Dev / change burden | Low–medium (config + API extensions, less core maintenance) | Medium (roadmap + paid CRs; vendor cadence) | Permanent high (markets/OEMs change = your backlog) |
| Interoperability | Designed open + modular | Often ecosystem-bound | Whatever you build |
| Lock-in | Lower (swappable components) | High vendor lock-in | High internal lock-in |
Understand your true cost to scale.
Why interoperability reduces long-term TCO
FAQ – Frequently asked questions
Beyond initial CAPEX, the largest driver is change frequency – new TSOs, new products, OEM updates, integrations, and compliance requirements. Architectures not designed for change accumulate long-term engineering burden.
Time to production depends on integration complexity and rollout scope. Custom builds often take 9-30 months, single-vendor stacks 4-12 months, while interoperable operating layers can go live in weeks to months.
Not necessarily. An interoperable operating layer is designed to connect existing systems rather than replace them, reducing re-platforming risk.
Custom builds create internal lock-in through key-person and maintenance dependency. Vendor stacks create ecosystem lock-in via proprietary data models and roadmap control. Modular, interoperable architectures reduce both risks.
Consider these three inputs
- Starting stack (controllers, EMS, forecasting, trading, TSO connections)
- Scope (asset types, MW, number of sites, geography)
- Expected change rate (new integrations, markets, compliance updates)
Time-to-production and cost ranges scale primarily with integration complexity and rollout scope.