The opportunity
$30B
Industrial energy-management software by 2030
As industries seek greater efficiency and control over increasingly complex energy systems, software is becoming a larger part of the energy-management market.
The Intelligence
Orchestrating Energy.
Building the intelligence layer for the world's energy infrastructure.
THE CHANGING ENERGY LANDSCAPE
01 DEMAND/02 SUPPLY/03 COMPLEXITY
The world needs
more energy.
AI compute, data centres, electrification and industrial growth are increasing the demand for reliable, uninterrupted power.
Energy is becoming
more dynamic.
Renewables, distributed generation and storage are changing when and where energy is available.
Everything is
connected.
Grid constraints, energy prices, industrial demand, storage and operational requirements increasingly influence one another.
Energy can no longer be
managed in isolation.
The next generation of energy infrastructure needs intelligence that can see across the system and coordinate decisions within it.
SYSTEM DYNAMICS•01 // DEMAND GROWTH
SCROLL TO ADVANCE NARRATIVE ↓
01 // DEMANDThe world needs
The world needs
more energy.
AI compute, data centres, electrification and industrial growth are increasing the demand for reliable, uninterrupted power.
02 // SUPPLYEnergy is becoming
Energy is becoming
more dynamic.
Renewables, distributed generation and storage are changing when and where energy is available.
03 // COMPLEXITYEverything is
Everything is
connected.
Grid constraints, energy prices, industrial demand, storage and operational requirements increasingly influence one another.
Energy can no longer be
managed in isolation.
The next generation of energy infrastructure needs intelligence that can see across the system and coordinate decisions within it.
One energy system.
Fragmented decisions.
Generation, grids, storage, procurement and industrial demand are deeply interconnected. Yet the systems and teams managing them often operate across separate data, objectives and planning horizons.
Physical energy flowsIndependent decision pathways
The missing layer isn't another dashboard.It's intelligence that connects the decisions.
A system-wide view of energy, where decisions can account for their impact across the wider ecosystem.
The scale of the opportunity
Energy is entering a new era ofscale and complexity.
AI, electrification and renewable generation are reshaping how the world produces and consumes electricity. Demand is rising. Flexibility is becoming more critical. And coordinating the system is becoming an increasingly complex challenge.
The demand shift
~1,000TWh
Annual data-centre electricity demand by 2030
AI and digital infrastructure are driving a rapid increase in electricity consumption, placing new demands on power systems.
The system challenge
4×
Potential increase in flexibility needs
In the IEA's net-zero pathway, power-system flexibility needs rise almost fourfold by 2050 as electricity demand and variable renewable generation grow.
More demand. More complexity.A greater need for intelligence across the entire energy system.
Energy infrastructure needsintelligence that connectsthe whole system.
Dhipromethi is building an intelligence layer that connects energy signals, physical constraints and operating objectives to support better decisions across the energy system.
ONE CONNECTED ENERGY SYSTEMONE INTELLIGENCE LAYER
Three capabilities. One connected intelligence.
From understanding what is changing to identifying and coordinating better decisions.
Anticipate what the energy system will need.
Bring together signals from generation, markets, storage and consumption to understand what is changing and what comes next.
What is changing across the system, and what comes next?Find the best path through competing priorities.
Evaluate economics, asset availability, physical limits and operating objectives to identify decisions that work in the real world.
Which decision best meets the objective within real-world constraints?Turn intelligence into coordinated decisions.
Translate recommendations into actionable decisions for the people and systems responsible for energy procurement, infrastructure and operations.
How can the right decisions reach the right people and systems?THE DECISION MODEL
What makes a better energy decision?
01
+Energy economics
Prices, tariffs, procurement and markets.
02
+Physical reality
Asset availability, capacity and infrastructure.
03
=Operating intent
Reliability, production and business priorities.
THE OUTCOME
The best feasible decision.
Meets the objective. Respects the constraints of the real world.
One intelligence layer.
Different industrial realities.
Energy decisions are shaped by the physical realities of every operation. The opportunity is to connect those realities with energy economics, infrastructure constraints and business priorities.
Data centres
Power cannot blink.
Around-the-clock demand leaves little room for interruption. Cooling, backup capacity and grid constraints make energy decisions increasingly interconnected.
The opportunity
Coordinate procurement, cooling flexibility and storage around the priority that matters most: continuity.
Steel & metals
Production moves in powerful bursts.
Electric arc furnaces and other power-intensive processes create sharp demand swings. Production timing, electricity prices and power availability are tightly connected.
The opportunity
Bring production schedules, procurement decisions and power-intensive processes into a shared optimisation picture.
Cement
Some processes cannot stop. Others can shift.
Kilns require continuous, carefully controlled operation. Grinding, material handling and other loads can have different degrees of scheduling flexibility.
The opportunity
Identify and coordinate flexible loads without compromising the thermal and operational requirements of the core process.
Manufacturing
Every production line competes for capacity.
Multiple lines, machines and utility systems operate on different schedules. Their combined demand can compete for limited electrical capacity.
The opportunity
Coordinate production and utility loads against energy costs, available capacity and operating priorities.
From energy forecasts to
operational decisions.
An intelligence layer that connects what is coming, what to do, and how decisions change when conditions shift.
01
Forecast
See what lies ahead.
Understand the energy picture before it unfolds. Forecast facility demand, renewable generation and electricity prices to build a forward-looking view of energy requirements.
0:00
02
Optimise
Turn understanding into action.
Translate forecasts into operating plans. Evaluate energy costs, grid imports, battery dispatch and infrastructure constraints together to identify better ways to meet demand.
0:00
03
What-if
Explore what changes.
Change assumptions around solar availability, electricity prices and battery capacity. Compare scenarios and understand how different conditions reshape the resulting plan.
0:00
Building the intelligence layer for energy takes two kinds of expertise.
AI and energy infrastructure are coming together at a critical moment. We're bringing both disciplines together to build what the next generation of energy systems needs.
IIT Guwahati, Mechanical Engineering. Builds at the intersection of AI, enterprise technology and business, with experience leading functions at early-stage and growth-stage technology companies.
Gnani.ai
AI · Enterprise technology
Head of Marketing & Inside Sales. Scaled key marketing and sales KPIs approximately 10× without adding headcount through AI-led workflows.
Ripik AI
Industrial AI
Chief of Staff. Helped drive international expansion across the US, Canada, Latin America and the Middle East.
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Around 12 years of experience across energy infrastructure and industrial automation, spanning grid operations, power systems and offshore energy projects.
TenneT
Dutch national transmission system operator
Experience spanning grid operations, power systems and offshore HVDC infrastructure.
McDermott
Offshore energy · Energy infrastructure · Project engineering
Experience across offshore energy infrastructure and complex engineering projects.
Energy infrastructure is entering a new era of complexity.
It needs an intelligence layer that connects the decisions.
That's the category we're building.
Dhipromethi.
Bringing fire to ideas.
Inspired by two ideas: the power of intellect, and the transformative force of fire.
Dhiti
Sanskrit · Intellect, ideas and thought.
Prometheus
Greek mythology · The bringer of fire to humanity.
Bringing intelligence to energy.
Our interpretation of the name, expressed through what we're building: intelligence for the energy systems on which everything depends.
Energy's next chapter will be built together.
Help shape the intelligence layer for energy infrastructure.
We're building Dhipromethi at the intersection of AI and energy infrastructure. We're speaking with the people who operate, build and invest in energy-intensive systems to understand where better intelligence can make the biggest difference.
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