The AI compute boom needs power it can't get fast enough. The clean-energy boom needs a buyer who will pay for distributed capacity at the household level. DCDATA sits exactly at that intersection — and is raising a US$18M Seed to fund the first fleet.
Global AI data-centre capex forecast by 2030 (Dell'Oro Group, Jul 2026).
Projected global VPP / distributed-energy market by the mid-2030s.
Share of Australian homes with solar / with battery — DCDATA's beachhead whitespace.
Sources: Dell'Oro Group Data Center IT Capex Forecast (Jul 2026); Global Market Insights, Fortune Business Insights, Precedence Research (VPP market, 2026); Clean Energy Council / Clean Energy Regulator (AU solar & battery attach, 2025).
Global AI data-centre capex is forecast to exceed $3.1T by 2030, but interconnection queues and permitting are measured in years, not months.
Major AI and cloud buyers are moving from annual renewable offsets to hour-matched clean compute — a standard centralised grids struggle to meet alone.
Australian home battery sales roughly quadrupled in H2 2025 alone — the installed base DCDATA needs is now being built by the market itself.
Sources: Dell'Oro Group (Jul 2026); Clean Energy Council Rooftop Solar & Storage Report (H2 2025).
Global AI data-centre capital expenditure forecast by 2030 (Dell'Oro Group; NVIDIA management guidance of $3–4T is directionally consistent).
~35% of AI infra spend goes to inference/rendering/latency-sensitive workloads suited to distributed deployment.
Bottom-up: ~40,000 Nodes live across AU/US/EU-UK/Asia-SE Asia by year 5, at ~US$10K illustrative annual compute revenue per Node.
TAM/SAM/SOM figures are illustrative DCDATA planning estimates built on cited third-party market data; not guaranteed outcomes. A secondary $30–45B VPP/DER market is additive and not included above.
Solar, battery and compute hardware financed by capital partners; facility owner hosts at zero upfront cost; asset-backed, amortised over Node life.
Compute sold to AI/cloud offtake customers, priced at a premium for verified 24×7 CFE; grid-services revenue (demand response) as a secondary stream.
Facility owner: hosting fee + revenue share. Utility/retailer: service fee + grid-value share. Capital partner: amortised return. DCDATA: platform margin on all.
DCDATA is positioned as both fully distributed and fully verified 24×7 clean — building a repeatable playbook across five global regions.
| Company | Category | Model | Capital raised / valuation | Gap DCDATA fills |
|---|---|---|---|---|
| CoreWeave | AI neocloud | Centralised hyperscale GPU cloud | ~$28B equity+debt (12mo to Mar '26); IPO'd at $23B (Mar '25) | Fully grid-dependent; no distributed or CFE-verified model |
| Crusoe Energy | AI neocloud + energy | Centralised sites on stranded/clean energy | $1.375B Series E at >$10B val. (Oct '25); ~$3.9B raised | Vertically integrated but still single-site, not residential |
| SPAN.io | Home energy platform | Smart panels + utility grid tech | $426M+ raised; Series C ~$163–176M (Jan '26); ~$103M rev. | Energy visibility only — no compute monetisation layer |
| XFRA (by SPAN) | Distributed AI compute | Solar+battery+compute Nodes in US homes | Backed by SPAN's balance sheet & utility relationships | US-only roadmap; DCDATA is global-first from day one |
DCDATA's direct analog, XFRA, validates the category from within SPAN's own ecosystem — but is US-only. DCDATA is designed global-first, with transparent multi-party payments and 24×7 CFE verification as core differentiators. Sources: Sacra (CoreWeave, Crusoe); CoreWeave/Crusoe press releases; CB Insights, Latitude Media, Tracxn (SPAN.io); DCDATA analysis of public XFRA materials.
Homeowners, utilities and capital partners are paid automatically and transparently — a network that wants to grow, not one that must be sold into.
Real-time, Node-level 24×7 CFE verification and multi-party settlement is genuinely hard to replicate — the platform, not the hardware, compounds.
One repeatable model designed from day one for AU → US → EU/UK → Asia/SE Asia, versus single-market competitors retrofitting for expansion later.
Household battery attach rates are inflecting now; capturing installer and utility relationships early compounds into a durable distribution advantage.
| Year | Nodes deployed (cumulative) |
|---|---|
| Yr 1 | 350 |
| Yr 2 | 2,200 |
| Yr 3 | 8,500 |
| Yr 4 | 20,000 |
| Yr 5 | 42,000 |
| Year | Revenue (US$M) |
|---|---|
| Yr 1 | $2M |
| Yr 2 | $15M |
| Yr 3 | $62M |
| Yr 4 | $165M |
| Yr 5 | $400M |
DCDATA's own revenue is a platform-margin share of gross fleet compute revenue, plus grid-services income — not the full amount shown above. Illustrative planning model; actuals will depend on pilot results, financing terms and market conditions.
Structured with flexibility to extend to US$22M to accelerate US market entry alongside the Australian pilot.
Solar, battery & compute hardware for the first ~300 Nodes.
Core team to build scheduling, 24×7 CFE verification & payments.
Market-entry legal work, utility partnership structuring, and team growth across GTM and operations.
Small, heavily instrumented pilot before any scale commitment; milestone-gated capital deployment.
Pursue signed pilot LOIs with compute customers in parallel with hardware deployment, not after.
Sequence markets by regulatory clarity; embed utility partners from day one in each region.
Asset-backed financing structures for hardware, separate from equity used for platform & team.
Strict phase-gating — no Phase 2 capital committed until Phase 1 milestones are met.
Fleet-level failover and battery buffering absorb generation variance; capacity planned for low-generation periods.
Leads strategy, capital formation and global market entry — building the commercial and regulatory playbook that takes DCDATA from Australia to every subsequent market.
Leads DCOS platform architecture, Node engineering and fleet operations — building the orchestration layer that turns thousands of household Nodes into one coherent cloud.
The compute market is worth trillions. The clean-energy market is worth trillions. DCDATA is built to sit at their intersection.