Industries
CleanTech, Energy, and Utilities
Building AI-based predictive models to optimize energy production and support clean technology initiatives
Scaling clean energy while balancing cost, efficiency, and regulation is a constant challenge Energy and utility providers face pressure to modernize legacy systems, integrate renewable sources, and make operations more efficient,with limited visibility and disconnected data.
We help bridge the gap by designing AI-powered tools, predictive models, and intelligent workflows that support smarter, more sustainable energy systems.
From forecasting to field operations, we build practical solutions that reduce waste, improve uptime, and accelerate clean innovation
Future trends
annual savings potential by 2035
International Energy Agency (IEA)AI optimization targets USD 110 billion in utility savings
AI optimization will move from plant experiments into a sector-wide operating model as utilities pursue 2035 savings. Operators that modernize asset data can defend their cost base.
The IEA estimates AI-enabled power-plant optimization could deliver up to USD 110 billion in annual savings by 2035.
International Energy Agency (IEA)
control rooms expected to use AI
Deloitte InsightsAI control rooms become a 2027 reliability benchmark
By 2027, AI-assisted control rooms will become a mainstream reliability capability as grid complexity outpaces manual monitoring. Utilities should fund production-grade decision support now to protect reliability performance.
Nearly 40% of utility control rooms are expected to use AI by 2027.
Deloitte Insights
tree-related outage reduction
Cleantech GroupAI vegetation intelligence cuts tree-related outages 48%
Over the next 12 months, utility field programs will shift toward AI-ranked vegetation risk rather than calendar trimming. Reliability leaders can protect outage performance with the same constrained crews.
An Ontario utility reported a 48% reduction in tree-related outages after deploying AI-driven vegetation prioritization.
Cleantech Group
3D seismic processing time
Boston Consulting GroupTwo-week seismic processing reshapes exploration decision cycles
Over the next two years, AI subsurface workflows will compress exploration evaluation from annual cycles to rapid screening. Faster prospect decisions can shorten time-to-market for commercially viable drilling programs.
AI can reduce 3D seismic data processing from about one year to about two weeks.
Boston Consulting Group
Our use cases
We can build predictive models that anticipate energy usage and optimize load balancing—helping reduce waste and support grid stability
We provide tools to monitor performance data, detect anomalies, and schedule proactive maintenance, minimizing downtime and extending asset life
We can create intelligent agents that support field teams by generating reports, summarizing operational data, and guiding task execution
We offer lean, testable platforms for clean energy startups and utility innovation teams, ready to iterate, scale, and integrate into live environments
We provide automation solutions that collect and manage environmental data, supporting accurate reporting and alignment with regulatory standards
We know how to design dashboards that track energy production, usage, and emissions, supporting compliance and operational decisions
