Tem Secures $75M to Transform AI in Electricity Markets

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Overview of Tem’s Funding and Valuation

London-based Tem is pushing to modernize how electricity is bought and sold. The financing was led by Lightspeed Venture Partners, with participation from AlbionVC, Allianz, Atomico, Hitachi Ventures, Revent, Schroders Capital, and Voyager Ventures.

Item Detail (as reported)
Round Series B (oversubscribed)
Amount raised $75 million
Lead investor Lightspeed Venture Partners
Other participants AlbionVC, Allianz, Atomico, Hitachi Ventures, Revent, Schroders Capital, Voyager Ventures
Reported valuation More than $300 million (per a source familiar with the deal)
Company HQ London
Planned use of funds Expansion to Australia and the U.S. (starting with Texas)

A source familiar with the deal said the round—an important marker for a company trying to turn a notoriously complex, intermediary-heavy market into something closer to modern digital infrastructure. Tem’s pitch is straightforward: electricity markets have accumulated layers of brokers, trading desks, and back-office systems that add cost and friction. If software can compress those layers, customers can pay prices closer to wholesale.

The timing is also notable. As AI data centers drive up electricity demand and, in turn, put pressure on prices, Tem is betting that AI can be part of the solution—by automating decisions and streamlining transactions in the market itself.

Tem’s CEO and co-founder, Joe McDonald, framed the raise as a choice rather than a necessity. He told TechCrunch the company has meaningful control over its own profitability and could have remained closer to a bootstrapped business. Instead, Tem raised to pursue a larger ambition: scaling quickly and building toward a public-market future.

One context note on sourcing: the funding amount, investor list, and valuation reference are reported in TechCrunch’s Feb. 9, 2026 coverage by Tim De Chant (Senior Reporter, Climate; PhD in environmental science, policy, and management—relevant for interpreting energy-market infrastructure claims).

Key Features of Tem’s AI-Powered Transaction Engine

At the core of Tem is an energy transaction engine called Rosso, which matches electricity generators with consumers. Tem describes itself as a marketplace: it connects supply and demand, but it also aims to change the mechanics of how the matching happens and how money flows between the two sides.

Rosso relies on machine learning algorithms and large language models (LLMs) to help predict supply and demand. In electricity markets, forecasting and execution are everything—especially as generation becomes more decentralized and variable. Tem’s approach is to use AI to automate work that, in today’s market structure, is distributed across multiple organizations and teams.

Forecast to Settlement Flow
1) Forecast
– Inputs Tem implies it uses: generator availability, expected demand, and market conditions.
– Checkpoint: forecasts must update fast enough to reflect renewable swings (e.g., wind/solar variability) and customer load changes.
2) Match
– Rosso pairs supply offers with buyer demand to form executable positions.
– Checkpoint: matching quality depends on having enough participants on both sides (liquidity) and clean, timely data.
3) Execute
– Trades/positions are placed through the market’s required mechanisms.
– Checkpoint: execution needs to handle constraints like timing windows and product types; otherwise “better forecasts” don’t translate into better prices.
4) Settle
– Money and contractual obligations flow from buyer to seller.
– Checkpoint: settlement is where many intermediaries historically sit; if this step isn’t streamlined, cost savings can be limited even if matching improves.

McDonald’s critique of the status quo is that electricity trading often involves “five to six intermediaries” enabling the flow of money from one side to the other. Each layer comes with its own systems, labor costs, and profit margin. Tem’s bet is that a single transaction infrastructure can replace much of that fragmentation.

The intended outcome is not just operational elegance; it’s price. By reducing the number of hands in the transaction, Tem wants the price customers pay to move closer to wholesale electricity costs. That’s a direct challenge to the way many commercial customers experience energy procurement today, where the final bill reflects not only generation costs but also the accumulated overhead of market plumbing.

Importantly, Tem is not positioning Rosso as a theoretical platform. It is already deployed—though, for now, in a controlled way through Tem’s own utility business.

Impact of Funding on Tem’s Expansion Plans

Tem says it will use the new capital to expand beyond the U.K. That sequencing matters: Texas is a large, distinctive electricity market, and it has long attracted energy innovators because of its scale and market dynamics.

The Series B gives Tem the resources to do what energy-market startups often struggle to do: expand while navigating operational complexity. Electricity is not a pure software category; it’s a regulated, high-stakes environment where reliability, settlement, and customer trust are as important as product features. Tem’s model—running both infrastructure and a customer-facing utility—suggests it is building expansion muscle by operating end-to-end, not just selling tools.

McDonald also signaled that Tem’s ambition is bigger than building a profitable niche. He told TechCrunch he could have avoided raising altogether, but that Tem is “not that kind of business,” adding that he wants to go public over the years. That implies a strategy oriented toward scale, market access, and eventually broader adoption of Rosso beyond Tem’s own retail channel.

Interpreting the Texas-First Strategy
Market-entry logic (how to read Tem’s “Texas first” move)
1) Why this market?
– Look for: high transaction volume, meaningful price volatility, and enough independent generators/retail activity for a marketplace to learn.
2) What must be built locally?
– Market connectivity: integrations for trading, metering/usage data, and settlement workflows.
– Operating capability: customer onboarding, billing, and support (if RED-like retail is part of the wedge).
3) What would “working” look like?
– Adoption: repeatable customer acquisition without relying on one-off pilots.
– Performance: measurable spread reduction versus incumbent procurement routes (not necessarily for every customer, every month).
– Reliability: fewer manual interventions in execution/settlement as volume grows.
4) What tends to break first?
– Data quality/latency, thin liquidity early on, or market-specific rules that force more manual handling than expected.

In practical terms, the funding can accelerate hiring, market entry work, and the operational lift required to replicate Tem’s U.K. playbook abroad. It also buys time to keep prioritizing growth of Tem’s “neo-utility” while preparing Rosso for a future where other utilities can plug in.

Customer Base and Energy Savings Achieved

Tem says it has signed up more than 2,600 business customers across the U.K. through its utility division, RED. The hook is savings: Tem promises customers that buying energy from RED can save them up to 30% on their energy bills.

Interpreting Reported Savings Claims
What’s concrete vs. what varies (based on what’s reported)
– Reported traction: “more than 2,600 business customers” in the U.K. via RED.
– Named examples: Boohoo Group, Fever-Tree, Newcastle United FC.
– Savings claim: “up to 30%” on energy bills.
What the “up to 30%” likely depends on in practice
– Baseline: what the customer was paying before (contract terms, broker fees, risk premiums).
– Load shape: how predictable/shiftable the customer’s usage is.
– Market conditions: wholesale volatility during the contract period.
– Product/contract structure: how much price risk is passed through vs. hedged.
How to interpret it responsibly
– “Up to” signals a ceiling outcome, not a typical result for every customer.
– The strongest validation would be customer-level before/after comparisons over the same period and product type (not provided in the reporting).

Those customers include fast-fashion retailer Boohoo Group, soft drink company Fever-Tree, and Newcastle United FC—examples that signal Tem is not limited to microbusinesses, even if it initially focused on smaller commercial users. McDonald has argued that decentralization helps the algorithms: the more distributed the market participants, the better the system can learn patterns and optimize matching. But he also said the approach “works all the way up to enterprise.”

Tem’s customer traction is tightly linked to its two-business structure. RED is the customer-facing utility designed to prove the value of Rosso in the real world. That matters because Tem tried a more traditional enterprise-sales route first—selling its infrastructure to existing energy companies—and “got nowhere,” according to McDonald. RED became the workaround: instead of persuading incumbents to adopt new infrastructure, Tem built a utility that could use Rosso immediately and demonstrate results.

For now, RED is the only utility using Rosso. And its growth has influenced Tem’s priorities: McDonald said the company has focused more on scaling RED than on opening Rosso to other utilities. The customer base, then, is both a commercial asset and a validation mechanism—evidence Tem can acquire and serve businesses while running its AI-driven transaction stack underneath.

Future Market Strategies for Tem

Tem’s longer-term strategy is to shift from being primarily a utility to being the infrastructure layer that utilities and market participants rely on. In other words, RED is a wedge; Rosso is the endgame.

McDonald has been explicit that Tem does not want RED to become dominant in a way that resembles a monopoly. He said that even if RED is excellent, it “is not going to get above a 40% market share,” and that it shouldn’t—because that would create monopoly dynamics. Instead, he said he would “much rather go to get access to all the transaction flow.”

Balancing Platform and Utility Priorities
Two paths Tem is balancing
1) Stay RED-first (neo-utility focus)
– Upside: guaranteed transaction flow for Rosso; faster learning cycles; direct control over customer experience.
– Downside: capital- and ops-heavy; expansion requires building retail capability market by market; can look like “just another utility,” making platform adoption harder.
2) Open Rosso to other utilities sooner (infrastructure focus)
– Upside: faster scale via partners; more transaction flow without owning the customer; aligns with the AWS/Stripe-style ambition.
– Downside: harder integrations; slower sales cycles with incumbents; less control over data quality and operational discipline; platform trust must be earned before others will route critical transactions through it.
A practical sequencing tension
– The more Tem proves with RED, the easier it may be to sell Rosso.
– The longer it waits, the more it risks being optimized for its own utility workflows rather than being a neutral “rail” others can adopt.

That framing points to a platform strategy: Tem wants Rosso to become the transaction infrastructure used broadly across the market, regardless of who owns the customer relationship or the generation assets. McDonald compared the ambition to infrastructure plays like AWS or Stripe—companies that became foundational layers for other businesses rather than owning every end-user relationship themselves.

The sequencing is pragmatic. Tem is prioritizing RED today because it is the only guaranteed channel for Rosso’s usage and learning. But the company’s stated direction is to eventually allow other utilities in. If Tem can make that transition—proving value through its own utility, then opening the rails to others—it could move from a single-market operator to a broader market utility in the infrastructure sense.

The expansion to Australia and the U.S. will test whether that strategy travels: whether Tem can repeat its “prove it yourself” approach in new markets, and whether the promise of lower-cost, AI-driven transactions is compelling enough to bring other utilities onto Rosso over time.

Challenges Addressed by Tem’s Technology

Electricity markets are under pressure from multiple directions at once: rising demand, the complexity of integrating renewables, and the operational drag of legacy market structures. Tem’s pitch is that AI can reduce friction in the transaction layer—where forecasting, matching, and settlement decisions translate directly into cost.

Tem is also responding to a broader tension in the moment: AI is both a driver of electricity demand (through data centers) and, in Tem’s view, a tool that can help markets operate more efficiently. The company’s approach is not about building new generation or new grid hardware; it is about changing how existing supply and demand meet, and how many intermediaries are required to make that meeting happen.

Streamlining Energy Market Transactions
Problem → what Tem claims to change
– Too many intermediaries
→ Rosso aims to consolidate fragmented roles (back office, trading desks, multiple counterparties) into a single transaction infrastructure.
– Renewables-driven volatility
→ ML/LLM-assisted forecasting and matching are positioned as a way to respond faster to variable supply and decentralized participation.
– Legacy market plumbing (disparate systems, manual workflows)
→ Tem’s “operate it yourself” approach (RED running on Rosso) is meant to prove the stack works end-to-end before asking incumbents to adopt it.
– High all-in customer prices vs. wholesale
→ By reducing layers and operational overhead, Tem’s stated goal is to narrow the gap between wholesale costs and what businesses ultimately pay.

Renewable Energy Integration

Tem intentionally started by focusing “almost exclusively” on renewable energy generators and small businesses, aiming to fill both sides of its marketplace early. That choice reflects a view that decentralized, distributed generation is not an edge case—it is the direction of travel.

Renewables also introduce variability. Wind and solar output can change quickly, and markets must constantly rebalance supply and demand. McDonald argued that decentralization benefits the algorithms: “The more decentralized and the more distributed, the better it is for the algorithms.” In practice, that suggests Tem expects its models to improve with a broader set of participants and more granular data—many generators, many buyers, many transactions—rather than relying on a small number of large, predictable actors.

By building a marketplace that can match renewable generators with business consumers, Tem is positioning itself as a software layer that can help make renewables easier to transact, not just easier to generate.

Aging Infrastructure

Tem’s critique of current electricity markets is fundamentally a critique of infrastructure—specifically, the market infrastructure that moves money and contracts, not the physical grid. McDonald described a system with multiple teams, multiple systems, and “five to six intermediaries” between generator and customer.

That kind of fragmentation is, in effect, institutional aging: processes that evolved over time, often with manual workflows and disconnected tooling. Tem’s response is to consolidate those functions into “one single transaction infrastructure,” using AI to replace human labor costs and disparate systems.

The company’s decision to build RED after failing to sell Rosso to existing energy companies also hints at how hard it can be to modernize legacy environments from the outside. Incumbents may be slow to adopt new transaction infrastructure, even if it promises efficiency. Tem’s workaround—operate a utility that uses the new infrastructure by default—lets it modernize the stack without waiting for permission.

As Tem expands to Australia and the U.S., it is effectively betting that similar structural inefficiencies exist in other markets, and that a software-first transaction layer can be deployed faster than traditional market reforms.

Economic Efficiency

Tem’s economic argument is that electricity customers pay more than they should because too many entities take a cut between wholesale generation and retail consumption. Rosso is designed to remove layers of profit-taking and operational overhead, pushing end prices closer to wholesale.

RED’s customer proposition—up to 30% savings on energy bills—turns that infrastructure claim into a commercial promise. While “up to” is not a guarantee for every customer, it signals that Tem believes the inefficiency gap is large enough to be felt at the invoice level, not just in back-office metrics.

McDonald’s description of replacing “humans, the labor costs, and the disparate systems” with AI-driven infrastructure is also a statement about cost structure. If Tem can automate tasks currently performed across multiple intermediaries, it can potentially operate with a leaner cost base and pass some of that advantage to customers to win market share.

The longer-term infrastructure strategy reinforces this: Tem says it doesn’t ultimately matter who owns the customer or the generation, as long as its transaction rails are used. That’s a classic efficiency play—becoming the low-friction layer that reduces costs for everyone moving through the system.

Tem’s Vision for the Future of Energy Markets

The Role of AI in Energy Efficiency

Tem’s story sits at the intersection of two AI narratives: AI as a growing electricity load, and AI as a tool to make electricity markets run better. The company’s bet is that the market layer—how electricity is priced, matched, and transacted—has enough inefficiency that modern AI-driven automation can materially reduce costs.

Rosso’s use of machine learning and LLMs to predict supply and demand is central to that vision. But Tem’s broader claim is structural: that AI can help collapse a chain of intermediaries into a single transaction infrastructure. If that works, the efficiency gain is not only about better forecasts; it’s about fewer handoffs, fewer duplicated systems, and fewer margins stacked on top of one another.

RED, meanwhile, is Tem’s proof mechanism. By operating a “neo-utility” that runs on its own infrastructure, Tem can demonstrate that AI-driven market operations are not just a lab exercise. It can show customer acquisition, billing outcomes, and the day-to-day reality of serving businesses—while continuously feeding Rosso with transaction flow.

McDonald’s comparison to AWS and Stripe is telling: the vision is for AI-enabled market infrastructure to become a default layer, embedded in how energy companies operate, rather than a specialized tool used by a few.

Expanding Horizons: Tem’s Global Ambitions

Tem’s immediate horizon is geographic. But the ambition is also about market position. Today, Tem is running two businesses—Rosso and RED—because it needs both adoption and proof. Over time, it wants to be the infrastructure that others use.

McDonald has suggested Tem will eventually allow other utilities onto Rosso. That shift—from a single-utility deployment to a multi-utility platform—would be a major step toward Tem’s stated goal of accessing “all the transaction flow,” rather than competing for retail market share alone.

The company’s willingness to raise capital despite having control over profitability underscores that it is optimizing for scale and long-term reach, not just near-term margins. And the stated desire to go public “over the years” signals a roadmap that depends on expanding beyond one country and one utility brand.

If Tem can replicate its U.K. traction abroad and then open Rosso to other utilities, it could move from being a promising energy retailer to something closer to a foundational layer in electricity markets—an AI-driven transaction backbone designed to make power cheaper, simpler, and more responsive to a changing generation mix.

This lens is informed by weidemann.tech’s work building and scaling transaction-heavy digital infrastructure in regulated environments (notably payments and multi-industry digital transformation), where reducing intermediaries and consolidating fragmented systems is often the fastest path to measurable cost and reliability gains.

This article reflects information reported as of Feb. 9, 2026, including the round size, investor list, and valuation reference. Performance claims such as “up to 30%” savings are presented as reported and may vary based on customer baselines, contract terms, and market conditions. As Tem expands beyond the U.K., results may differ materially due to market-specific operational and regulatory factors.

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