Model every clean energy decision with confidence
Plan, procure, and operate with the ES Suite: sub-hourly resolution, your market policy built in.
10 GW+ of projects and $1B+ in energy decisions simulated for industries carrying the grid’s largest loads
The solar-heavy mix looks strongest. Hold 70% RE offset under a $40M capex ceiling — what breaks?
ES Agents · grounded in 3 sources
- SimulateRe-run TEIP at $40M ceilingrun #482
- TariffRe-price on the ToD orderMSEDCL 2024/17
- FinanceCheck DSCR headroomterm sheet v3
Equity IRR
LCoE
DSCR
Proven on the loads at grid scale, from IPPs to C&I consumers.
10 GW+
Solar & wind simulated
4 GWh
Battery storage modelled
$1B+
Energy decisions run
5
Industries served
Billion-dollar energy decisions still run on annual averages
9–18 months
for a large consumer to sign a single renewable agreement, most of it spent reconciling numbers nobody fully trusts.
Sub-hourly
settlement is the reality of modern power markets. Value is won and lost in intervals annual averages hide.
$100M+
rides on one project’s capex, tariff, and IRR calls. Small modelling errors compound across a portfolio.
20–30%
Revenue loss
of a battery’s revenue is forfeited when schedules run on rules of thumb instead of price-aware optimisation.
Every 1%
of avoidable network loss compounds into millions when grids are planned on annual balances, not power flows.
The ES Suite closes the gap: from plan to procurement to live operations.
AI Agents for energy decisions
Ask anything in plain language. The Agents work across the platform, running simulations, automating workflows, and watching markets and regulations.
- PlanSize solar + BESS for a 67M-unit factoryRunning70% offset · IRR 14.4%
- ProcureCompare 12 RFP proposals like-for-likeQueuedVendor B · 91/100
- OperateBid a 200 MW portfolio across DAM & RTMQueued96 blocks placed
Watching
- IEX DAM · evening peak+$8/MWh
- MSEDCL ToD orderRevised
Run tasks autonomously
Describe the outcome. The Agents draft the scenarios, run the sweeps, and iterate autonomously.
Custom workflow
Turn any repeatable task into a standing automation: run on schedule, results handed back.
AI-based monitoring
Agents watch your portfolio, markets, and regulations, flagging what changed and what it does to your numbers.
Grounded and cited
Every answer runs the model and cites its sources: the simulation, the tariff order, the market series.
The ES Suite simplifies your clean energy transition
RE offset target: 65% · State: Tamil Nadu
Global policies built in
Tariffs, settlement rules, and incentives are built into the engine, so every market is modelled the way it actually settles.
The world’s most granular power market
India settles electricity every fifteen minutes, across day-ahead, green, and real-time exchanges, priced against twenty-eight state rulebooks, no two alike. EarthSync was built here, in the deep end. That is why it models the block, not the average.
What the engine encodes
- IEX DAM, GDAM, and RTM forecasting
- 28 state open-access, banking, and wheeling regimes
- ToD tariffs and RPO obligations as hard constraints
- Sub-hourly DSM deviation-band economics
The work behind the numbers
EarthSync in the news
Ready to optimise your
energy strategy?
10 GW+
Solar & wind simulated
4 GWh
Battery storage modelled
$1Bn+
Energy decisions run










