Kieran Stone
Head of Digital Twin Engineering
Leads development of EnerLith's digital twin architecture, ensuring accurate virtual representations of energy assets and industrial infrastructure at scale.
Model your energy and industrial assets as living digital twins — simulate scenarios, uncover inefficiencies, and optimize operations before touching physical systems.
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EnerLith combines digital twin modeling, simulation, and AI optimization into one platform, helping teams plan, test, and improve energy infrastructure with confidence.
Create accurate virtual representations of energy assets and infrastructure, complete with system state tracking, asset relationship mapping, and centralized digital twin management.
Test operational conditions before they happen. Model demand, simulate system behavior, and compare parameters across scenarios to plan with precision and reduce risk.
Uncover efficiency gains automatically. AI-driven analysis surfaces resource and operational optimization opportunities, with performance recommendations ranked by projected impact.
Gain full visibility into complex industrial energy systems through asset performance monitoring, infrastructure analytics, operational trend analysis, and proactive capacity planning.
A centralized command center for energy operations: track active simulations, live performance metrics, asset health, and optimization opportunities in one unified view.
Evaluate multiple infrastructure and operational scenarios side by side, so teams can make data-backed decisions before committing resources to physical changes.
EnerLith turns raw energy and infrastructure data into actionable intelligence: building digital twins, running simulations, and optimizing decisions in one continuous flow.
Connect energy assets, sensors, and infrastructure data sources into a unified digital environment.
Build accurate digital twins that mirror real-world energy systems and operational behavior.
Simulate scenarios and operational conditions to test changes without physical disruption.
Apply AI-driven optimization to recommend the most efficient path forward.
Applies AI analysis to simulation results, surfacing efficiency opportunities and ranked recommendations for confident decision-making.
Runs operational scenarios and demands modeling on the digital twin, testing conditions safely before real-world implementation.
Models energy assets and infrastructure into virtual representations, capturing system state, asset relationships, and real-time conditions.
SCADA · EMS · Historians · IoT sensors · Metering · CMMS · Market feeds
Each engine is independently addressable through the EnerLith API and console, and each one reads from the same calibrated twin.
Connect energy assets, sensors, meters, and infrastructure systems, streaming operational data into a unified platform environment.
Build accurate virtual representations of energy assets, capturing system state, relationships, and real-world operating conditions.
Map physical infrastructure and asset dependencies, creating a detailed foundation for simulation and optimization analysis.
Run operational scenarios and demand models, testing system behavior under varying conditions without physical disruption.
Apply AI-driven analysis to simulation results, identifying efficiency gains and ranking recommendations by potential impact.
Deliver clear, data-backed insights so teams can confidently plan, validate, and implement infrastructure changes.
One command surface for twin state, live simulations, performance telemetry, asset health, and ranked optimization opportunities — powered by calibrated physics models.
Grid efficiency
94.7%
+2.1% — vs. 30-day baseline
Net generation
638 MW
-3.8% — curtailment event active
Dispatch cost
$34.20/MWh
-11.4% — AI-optimized setpoints
CO₂ intensity
214 g/kWh
-18.3% — vs. regional grid avg
Digital twin topology
Active simulation scenarios
ETA: ~4 min
ETA: next
Modelled savings (YTD)
$163k accumulated · Jan–Aug 2025
Asset health index
HRSG upstream
110/33 kV, 150 MVA
48 MWh, SoC 76%
fuel gas supply
Ranked optimization opportunities
Pre-cool cooling water loop 06:00–07:30 UTC to reduce GT heat rate by 0.4%
$63k / yr
Advance TR-22A tap change schedule to reduce no-load losses at night
$38k / yr
Re-sequence K-11 suction valve timing — reduce discharge temp by 8 °C
$24k / yr
Model, simulate, and optimize large-scale energy generation and distribution systems.
Improve grid planning and operational efficiency with digital twin insights.
Optimize energy usage and equipment performance across production facilities.
Monitor and simulate infrastructure health to prevent costly failures.
Test infrastructure changes virtually before implementing them in the field.
Track asset performance and identify energy efficiency opportunities in real time.
Use simulation-driven insights to streamline operations and reduce waste.
Prototype and validate energy models in a risk-free virtual environment.
We were built by engineers, energy specialists, and technologists focused on turning complex infrastructure challenges into simulation-driven, optimized operational outcomes.
Head of Digital Twin Engineering
Leads development of EnerLith's digital twin architecture, ensuring accurate virtual representations of energy assets and industrial infrastructure at scale.
Head of AI & Optimization
Drives the AI-powered optimization engine, designing algorithms that turn simulation data into actionable, ranked efficiency recommendations.
Head of Energy Systems Engineering
Brings deep energy and industrial domain expertise, guiding platform capabilities to reflect real-world infrastructure and operational needs.
Head of Platform Infrastructure
Oversees the scalable data pipeline and cloud architecture powering EnerLith's simulation and digital twin infrastructure.
Head of Product & Customer Success
Ensures EnerLith's platform delivers measurable value to energy and industrial teams, from onboarding through ongoing optimization.
EnerLith helps us visualize complex energy systems, test operational scenarios, and make more informed decisions before implementing changes across critical infrastructure.
Irroshan Devapriya
Energy Operations Manager
EnerLith brings digital twins, simulation, and optimization together, giving our team a clearer view of infrastructure performance and potential efficiency improvements.
Jordan Doyle
Industrial Optimization Lead
Using EnerLith, we can evaluate different infrastructure scenarios virtually, helping our team plan changes with greater confidence and reduce operational uncertainty.
Cherith Banda
Infrastructure Planning Director
EnerLith provides a powerful environment for analyzing asset performance, comparing scenarios, and identifying practical opportunities to improve energy system efficiency.
Naomi Rich
Energy Systems Analyst
The calibrated simulation engine inside EnerLith gave our engineering team a reliable way to stress-test dispatch strategies without any risk to live generation assets.
Marcus Osei
Generation Asset Engineer
From single-facility pilots to enterprise-wide deployments, EnerLith scales with your infrastructure needs. Choose a plan that fits your simulation workload, asset complexity, and optimization goals.
Ideal for teams beginning their digital twin journey with a single facility or asset group.
Built for growing teams managing multiple facilities and running advanced optimization workflows.
Designed for large-scale operations requiring unlimited assets, custom deployment, and dedicated support.
Connect with our energy engineering team. We'll analyze your telemetry data formats, system topology, and operational targets.
44 Montgomery Street, Suite 1800
San Francisco, CA 94104, USA
Phone: +1 415 555 7624
19 Wijerama Mawatha
Colombo 07, Sri Lanka
Phone: +94 11 271 5086
Bring one site, one feeder, or one process line. We will stand up a calibrated digital twin and run your first optimization scenario against real operating data.
Enterprise deployment · SSO · On-premise available