Power Factors is a trusted global renewables intelligence and infrastructure partner, managing over 310 GW of wind, solar and BESS assets, serving utility-scale asset managers, developers, IPPs and analysts. 

Unity REMI (Renewable Energy Management Intelligence) is a purpose-built AI intelligence engine for renewables, designed to help asset managers increase asset yield and improve revenue margins. We built REMI to solve a critical operational bottleneck: as portfolios grow from a handful of sites to hundreds or thousands, spanning multiple renewable energy technology types, operators face a data management challenge that has outgrown manual analysis. Solutions like REMI cut through the data overload, filtering project data down to the signals that matter so asset managers can troubleshoot faster, identify underperformance sooner, and reduce asset downtime. 

Embedded into Power Factors’ Unity Asset Performance Management (APM) platform, REMI bridges raw site data and strategic execution, from automating data cleansing across disparate systems to surfacing the performance insights teams need from massive data volumes, tailored to how they actually work.

The press release cites “operational data from more than 310 GW of assets” and “30 GW active”; can you share independently verifiable performance outcomes (e.g., measurable uptime, yield, or revenue improvements) that REMI has delivered for named customers?

We’re working closely with the customers who’ve adopted REMI to help answer exactly that question. There are a number of different applications for REMI right now, and we’re developing and validating them in real time, together with those customers.

Origis Energy is a good example. Origis has set a goal of operating every plant at 98% of expected energy or higher, which means hunting every loss source, such as vegetation, soiling, DC health issues, and correcting it. Chad Nelson, Origis’s Senior Director of Digital Technology, has highlighted that Unity APM’s fleet-wide visibility helps the team find “issues that otherwise would be hard to see just looking at a meter itself.” 

Within Unity APM, REMI is the piece that speeds up diagnosis. Origis uses it to surface definitions, equations, and logic-based flow paths directly in metadata and signal views, cutting tasks that used to take up to an hour or two of documentation-digging down to an instant.  Noah Johnson, Origis’s ROC Supervisor, has explained that REMI helps answer “how to fix, who to fix, and where to fix” faster. 

How does optimizing renewable portfolio returns translate into a sustainability outcome SBM readers would recognize – e.g., additional clean energy delivered to the grid, curtailment avoided, or carbon displaced, rather than purely a financial efficiency gain?

Smart asset management that maximizes the efficiency of clean power sources also improves grid resilience and stability – ultimately helping us reduce our reliance on fossil fuels. By eliminating manual delays, REMI reduces asset downtime to ensure more reliable, continuous clean energy generation and dispatch. For hybrid sites that combine generation and energy storage, this gives operators more control to match output with real-time demand. Ultimately, this level of control unlocks a wider range of essential grid services tailored to real-time needs.

REMI was built and trained using 310GW of operational data, including root-cause history behind events, so it understands how a project behaves throughout its entire lifecycle, not just in a specific moment. That means it doesn’t need the constant re-prompting generic AI tools do.

This enables agentic optimization for renewable energy. REMI allows users to look across an entire series of sites and workflows simultaneously, picking up on how O&M teams and analysts actually operate day-to-day and taking over the time-consuming and inefficient parts of that work. This automation factor is a need of the hour, giving teams an instant read on whether they need to dig deeper into a specific site or parse a signal correlated across multiple assets, rather than working it out manually. These are sustainability gains, not just financial ones.

Is there a broader shift in renewable asset management (e.g., agentic AI adoption, grid complexity, BESS growth) this story illustrates beyond a single product release?

Renewable asset management has grown more complex as the technology mix has become more sophisticated, grid stability challenges have increased, typical climatic conditions have changed, and the commercial landscape has altered. Consequently, asset managers are seeking new tools that can simplify their workload and enable them to focus on the tasks that can improve portfolio performance most.

Solutions like REMI are part of a broader shift in modern renewable asset management: the transition from passive data monitoring to automation and AI-embedded workflows. Historically, traditional energy management has followed a remedial “fix it when it’s broken” approach, acting only on alerts of errors or loss. Today, the industry is focused on moving beyond reactive fixing to proactive monitoring and performance optimization. 

This has been bolstered by agentic AI which can autonomously handle much of that manual work, freeing up time for revenue- and production-focused tasks. By cutting down on manual tasks, automation frees up time and produces insights that support better decisions. REMI responds to an industry-wide pivot toward more robust and autonomous operations, to keep pace with the rapid portfolio growth and the fresh complexity the industry has seen.

What would a sustainability or asset-management professional actually take away from this story beyond product capabilities—is there a transferable insight about managing renewable fleets at scale?

The transferable insight is about what has to change organizationally when a renewable fleet scales faster than headcount can. Continuing to manage renewable energy assets the way we have historically is unsustainable now that the energy transition has grown and become more complex.

Origis Energy, which operates roughly 4.6 GW across ~29 sites today and is growing toward 20 GW and beyond, is a prime example of a pipeline growing significantly that will not be met with a proportionate team.  

Origis’s Senior Director of Digital Technology states that the goal is “making each person that has access to the platform as efficient as possible,” but underlined that a good tool only pays off if the organization builds the skill and process around using it well. 

One concrete example of that kind of efficiency gain in practice is Origis’ use of REMI to surface definitions, equations, and logic-based flow paths directly from documentation, cutting a task that used to take up to an hour or two down to near-instant.  

Can you provide a documented case study, third-party validation, or methodology behind the “agentic” and “predictive” claims that SBM could cite?

The technology is new, and it is too early to share a detailed case study yet. But, today, REMI’s agentic capabilities include editing and reprocessing operational events, rerunning signal/calculation pipelines, submitting and mapping new time-series data, and building and adding dashboard widgets from a chat description. All of these are actions that change data or configuration in the platform, not just retrieval.

Origis Energy have described the early benefits they have seen from their early access to the technology like this:
“Every minute we spend searching for data or reading documentation is a minute that we aren’t optimizing our asset performance,”

said Noah Johnson, ROC Supervisor at Origis Energy.

“With REMI, we don’t have to make that trade-off. We can ask specific questions to diagnose asset performance, understand events and KPI details with clarity, and define terminology for complex solar power plant-specific components and variables. REMI gives us immediate, clear, and actionable answers. It’s like having the industry’s most experienced engineers and technical support analysts available 24/7, assisting every member of our team.”