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Siemens recently launched an industrialized reference design built specifically for Nvidia’s next-generation DSX Vera Rubin NVL72 AI supercomputer clusters
[https://press.siemens.com/global/en/pressrelease/siemens-and-partners-develop-reference-architecture-purpose-built-nvidia-ai-data#:\~:text=Siemens%20%E2%80%93%20together%20with%20NVIDIA%20and,controls%20architecture%20for%20hyperscalers%2C%20colocation](https://press.siemens.com/global/en/pressrelease/siemens-and-partners-develop-reference-architecture-purpose-built-nvidia-ai-data#:~:text=Siemens%20%E2%80%93%20together%20with%20NVIDIA%20and,controls%20architecture%20for%20hyperscalers%2C%20colocation)
Fluence is the only battery energy storage system (BESS) vendor integrated natively into this pre-engineered blueprint.
Fluence's financial outlook is defined by substantial revenue visibility rather than speculative demand:
\-Total contracted backlog stands at $5.6 billion. Management projects 50% to 55% of this will convert to recognized revenue over the next 12 months.
\-Year-to-date order intake hit $2.0 billion, doubling the $1.0 billion booked during the same period last year.
\-The company signed master supply agreements with two top-tier hyperscalers, with initial deployments scheduled for Q3.
\-Despite a Q2 revenue miss ($464.9M vs. $611.5M expected) driven by transient supply-chain and shipping bottlenecks at international ports ( which will show on Q3 rather than Q2), full-year 2026 revenue guidance was reaffirmed at $3.2 billion to $3.6 billion. The fiscal calendar is back-half heavy, with 70% of deliveries weighted to the remaining two quarters.
The long-term upside lies in the deployment of the Fluence OS and Digital Applications infrastructure. The digital segment is tracking toward an estimated $180 million Annual Recurring Revenue (ARR) run-rate by fiscal year-end 2026. This recurring stream creates a structural lever to pivot the company out of historical net losses toward GAAP profitability.
How does the software work?
Fluence OS is an edge-computing software platform embedded directly into every battery container at the factory. It operates locally with sub-second response times (down to 150 milliseconds) to manage the physical health and immediate power dispatch of the system.
* **Micro-Second Balance:** It monitors individual battery cells, managing thermal dissipation, state-of-charge, and cell degradation. If one rack of batteries is heating up faster than another, the OS dynamically shifts the internal electrical load to preserve the system's lifespan.
* **Application Stacking:** It enables the batteries to perform multiple physical functions simultaneously. For example, it can reserve 20% of capacity for instant voltage protection (to protect Nvidia GPUs from a micro-second power drop) while utilizing the remaining 80% for peak shaving (discharging power when grid prices spike).
* **Grid Synchronization:** It translates commands from external utility operators or regional transmission organizations (RTOs) into physical charging or discharging actions using standardized industrial protocols.
Basically, it allows the supercomputer to properly work by stabilising the loads into constant power .
Fluence IQ is a cloud-based software suite that uses machine learning to maximize the financial return on investment (ROI) of the energy asset. This is where the company generates its high-margin SaaS revenue.
Wholesale energy markets fluctuate continuously based on weather, supply, and regional demand spikes. Humans cannot calculate optimal trading fast enough across volatile day-ahead and real-time markets.
* **Data Integration:** Mosaic ingests massive streams of external data: regional weather forecasts, historical grid congestion patterns, real-time fuel prices, and current grid load parameters.
* **Predictive Modeling:** Neural networks generate probabilistic price forecasts to determine exactly *when* energy prices will peak or drop.
* **Automated Execution:** The software autonomously structures and submits complex, co-optimized financial bids directly into wholesale energy markets. It calculates when to buy cheap electricity to charge the batteries and when to discharge it back to the grid to lock in maximum spread arbitrage, increasing asset revenue by up to 50% compared to manual bidding
* **Digital Twin Technology:** It creates a cloud-based digital replica of the physical asset. By comparing real-time operational data against the digital twin's ideal performance curves, machine learning algorithms can predict component failures or maintenance bottlenecks before they cause downtime.
* **Portfolio Aggregation:** For hyperscalers or large independent power producers (IPPs), it aggregates data across geographically separated wind, solar, and battery assets into a single dashboard, identifying macro-level efficiency drops or revenue leakages.
The software suite operates via a pure **Software-as-a-Service (SaaS)** model. Once deployed, the incremental cost to deliver the cloud algorithms to a new asset is minimal, carrying typical software gross margins exceeding **60% to 80%**.
Siemens remains a dominant strategic shareholder, retaining roughly a 35% to 39% stake. A secondary public block offering of 20 million shares in May 2026 created structural price overhang. While it provides no cash to Fluence and does not impact operations, strategic liquidations by parent companies place a temporary ceiling on equity price action.
Also, Siemens being a very big owner of Fluence Energy, probably it s the whole reason they landed contract with Nvidia to develop Vera Rubin clusters
(used AI to show most important bits)
TLDR:
mkt cap around 4.5b, revenues of up to 3.6b in 2026, backlog of 5.6b and a very high marging SaaS that will generate profits for the company and make it sticky for thelong term once integrated, Nvidia and hyperscalers validating their business this year
At current price, considering all the above, I think it has a very good entry point .

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