Redwood’s $425M Series E signals a new race to power AI data centres

Redwood Materials has closed its Series E at $425 million—upsized from a previously announced $350 million—positioning the company to scale energy storage systems aimed at powering AI data centres and industrial sites. As the ai world organisation tracks the infrastructure stack behind AI adoption, this round is a clear signal that “power” and “storage” are becoming core AI enablers, not background utilities, and that’s exactly the kind of shift we spotlight across ai world organisation events and ai conferences by ai world.

This raise also underscores how strategic investors are increasingly treating energy storage and grid reliability as part of the AI buildout, alongside chips, cloud, and data. In the lead-up to the ai world summit 2025 / 2026 conversations, developments like Redwood’s show why the AI ecosystem now includes climate-tech, critical minerals, and industrial-scale infrastructure—because AI compute depends on stable electricity at scale.

A $425M close, upsized by demand

Redwood Materials completed the final close of its Series E financing, bringing the total round to $425 million to support energy solutions for AI data centres and industrial customers. The extension drew continued participation from Capricorn and Goldman Sachs Alternatives and added Google as a new investor, with the total moving beyond the earlier $350 million announcement due to strong demand.

The company did not publicly disclose its valuation, though reporting cited a post-money valuation above $6 billion, and the new capital brings Redwood’s total private funding to $2.3 billion. Redwood itself framed the raise as a move to accelerate its energy storage platform while also strengthening its integrated recycling and critical minerals business.

From an AI-industry lens, this is not “just another funding headline” because it links two fast-moving curves: the rising electricity requirements of AI and the growing need to source, reuse, and recover battery materials domestically at scale. That intersection is increasingly relevant to the ai world summit and to the broader agenda of the ai world organisation, where practical deployment realities (power availability, uptime, resilience, and cost) now shape real-world AI roadmaps.

Redwood’s circular battery playbook

Redwood was founded in 2017 by JB Straubel with the aim of building a circular supply chain for batteries. In its earlier phase, the company focused on recycling scrap from battery manufacturing and consumer electronics, recovering materials such as lithium and nickel and supplying processed outputs to battery makers, including Panasonic.

Over time, Redwood expanded beyond recycling into cathode production, broadening its role across the battery value chain rather than staying only at end-of-life processing. This “integrated” approach—materials recovery plus downstream manufacturing capability—sits behind the company’s claim that it is scaling a domestic battery ecosystem, which is also part of how it describes the purpose of the new capital.

For AI builders and enterprise leaders, the key takeaway is that circularity is being commercialised not only as sustainability positioning, but as a practical supply and resilience strategy in a world where electrification and data-centre growth create new constraints. At the ai world organisation, this is exactly the kind of “under-the-hood” theme we bring into ai conferences by ai world: AI’s future is inseparable from how we modernise energy systems and industrial supply chains.

Second-life EV batteries as data-centre power assets

A central driver of investor interest is Redwood’s energy storage business, which gives used EV batteries a second life before they are fully recycled. Redwood describes repurposing these batteries into microgrids that can supply power to AI data centres and large industrial customers, directly tying battery reuse to the uptime needs of compute-heavy facilities.

In its funding announcement, Redwood argued that surging electricity demand—driven by AI, data centres, manufacturing, and electrification—makes energy storage “essential infrastructure,” not an optional add-on. The company has also stated that it recovers more than 70% of used or discarded battery packs in North America, and that many of these packs can be suitable for reuse in energy storage applications.

Redwood previously said it had more than 1 gigawatt-hour of batteries in inventory, expected more, and is targeting deployment of 20 gigawatt-hours of grid-scale storage by 2028, outlining both near-term capacity and a longer deployment ambition. If that scale materialises, it would make “second-life” storage not a niche experiment but a meaningful infrastructure layer that can buffer demand spikes and support reliability for high-load customers such as data centres.

For the ai world organisation and the community that gathers at the ai world summit, this shift matters because the AI era is forcing new thinking about where resilience comes from: not only larger grids, but faster-deployable storage, microgrids, and systems that can reduce exposure to supply shocks. It also reframes battery recycling as a strategic input into AI readiness, which fits squarely within the practical, implementation-focused discussions we push across ai world organisation events and ai conferences by ai world.

What’s next—and why the AI ecosystem should care

Redwood says the funding will be used to scale both its energy storage platform and its recycling and critical minerals operations, reinforcing the “domestic battery ecosystem” message in its announcement. The strategic logic is straightforward: pairing recycling, materials, and storage deployment can shorten loops between battery supply, reuse, and industrial power delivery.

For AI operators, the broader signal is that solving AI’s growth constraints increasingly requires cross-sector execution: power electronics, software, industrial operations, and battery supply chains moving in sync. That’s one reason the ai world organisation keeps expanding the conversation beyond models and apps—because the AI world summit agenda is ultimately about what enables adoption on the ground, and energy reliability is now a first-order requirement for AI scale.

This also aligns with the ai world organisation’s global convening focus: our flagship AI World Summit 2026 Asia & Global AI Awards is scheduled for 28th May, 2026 in Singapore, and our event calendar spans multiple summits and geographies that reflect how AI adoption challenges differ across regions. In India, the same infrastructure themes show up in a different form—skills, GCC enablement, and enterprise transformation—areas our platform also covers, including events like Talent, Tech & GCC Summit - Delhi 2026 (17th April, 2026 at IIT Delhi).

If you are building in AI—whether as a hyperscaler, enterprise CIO team, or a fast-scaling startup—this funding round is another reminder that compute strategy and power strategy are converging. And for everyone engaging with the ai world summit 2025 and ai world summit 2026 conversations, the message is clear: the most durable AI advantage will come from pairing innovation with infrastructure execution, which is why the ai world organisation keeps bringing together leaders across technology, business, and real-world deployment at ai world organisation events and ai conferences by ai world.