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The unified platform for your clean energy portfolio

Plan projects, buy and sell power, and operate assets, with AI agents working from the same data at every step.

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10 GW+ of projects simulated and 1 GW+ of energy assets under operation for industries carrying the grid’s largest loads

ES Operate · Plant agent, 45 MW hybrid
Agent

Spawn an agent for the 45 MW hybrid: watch the plant, keep today on schedule, and tell me what every deviation costs.

Plant agent · grounded in 3 sources

  • PlantRead the SCADA through the edge agent
  • BlocksPrice every block against the schedule
  • AdviseDraft the revision for 14:30–16:00

Export now

Under schedule

Revision

Sources: plant telemetry · schedule rev 3 · market imbalance rules

How the energy system is changing

Four shifts, and what each one now demands.

24/7 clean energy

Buyers are moving from annual renewable-energy matching towards clean electricity matched to consumption hour by hour.

Size supply and storage around when power is needed.

Model your clean-energy target

New technologies

Storage, hybrids, hydrogen and flexible loads have multiplied the ways a project can be built.

Optimise technology, size and dispatch together to find the right mix.

Compare project designs

The electron economy

Industry, transport and data centres are electrifying at once, adding load and congestion to the grid.

Plants have to be monitored live and kept within the grid code.

Connect plant and market operations

Rise of prosumers

Consumers are becoming asset owners, generating and storing their own power and buying the rest directly.

Compare power offers on landed cost, renewable coverage and contract terms.

Buy with Marketplace

ES Suite digitises and automates your clean energy transition

One model of each project, from simulation to settlement. Buyers, developers and operators work from the same assumptions, contracts and operating data.

ES Suite · Plan, buy, bid and operate
Connected
01Simulate

Agents size every mix before you build

Plan with ES Solve
  • AI agents
  • 100+ inputs
  • 15-min resolution
  • P50 / P90
02Buy and bid

Buyers and sellers, one marketplace

Bid with ES SourceBuy with Marketplace
  • Matched RFPs
  • Landed-cost comparisons
03Operate

Monitor live, act in real time, automate

Run with ES Operate
  • SCADA and EMS
  • Digital twin
  • Autonomous agents
  • Power markets
  • 01

    AI agents and skills

    Compare scenarios, prepare bids and flag operating issues

    • Plant-specific agents
    • Skills that learn from your workflows
    • Fine-tuned models in your environment
    • Automations within your limits
    • Answers linked to their sources
  • 02

    Integrations

    Plugs into what you already run

    • SCADA and EMS
    • Edge connectors for Modbus and OPC UA
    • Power exchanges
    • Meter data and SFTP feeds
    • Excel and accounting exports
    • Email
  • 03

    Shared data

    One model of each project, from simulation to settlement

    • Digital twins
    • Plant telemetry
    • Prices and forecasts
    • Tariffs and regulations
    • Contracts and invoices
    • Isolated per resource, with role-based access
  • 04

    Security

    The same controls under every product

    • Flexible security controls
    • Every action logged
    • Roles and approvals
    • Cyber compliance checks
    How we secure it

What you gain with ES Suite

From project design to power purchases and daily dispatch: see what changes when the work runs on one platform.

Find the project mix that improves returns, with solar, wind and storage sized together at 15-minute resolution. Explore

ES Solve · Project IRR
Example

Project IRR

Initial project design0.0%
Optimised project design0.0%
+2.4 pts
+0.0 ptsof IRR in this illustrative design comparison.
Illustrative designs evaluated on the same load, tariffs and financing assumptions. Project size and dispatch change; results depend on the project.
Slide 1 of 2

Proven at grid scale, from IPPs to C&I consumers

10 GW+

Projects simulated

1 GW+

Assets under operation

$1Bn+

In energy decisions modelled

5

Industries served

Trusted by
  • KP Group
  • Vibgyor Energy
  • Play Solar
  • & more
Built for
  • C&I energy consumers
  • IPPs & developers
  • Advisors & consultants
  • Financiers & investors
  • Traders & market desks
  • DISCOMs & utilities
Working across
  • Auto manufacturing
  • Data centres
  • Metals & mining
  • Chemicals
  • Textiles
As featured in
  • Forbes
  • Entrackr
  • Saur Energy
  • The Tribune

Global policies built in

Tariffs, settlement rules and incentives are part of the engine, so every market is modelled the way it actually settles.

Fifteen-minute settlement, state by state

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, which 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

Technologies we model

  • Solar
  • Wind
  • Battery storage
  • Pumped hydro
  • Diesel generators
  • Green hydrogen
  • Green ammoniaNew

Insights, case studies and news

All resources
AI × Energy · 16 min read

Tokens per megawatt-hour: the energy economics of frontier AI

One megawatt of AI computing uses about $78 of electricity an hour, a small share of what it costs to run and what its tokens earn. What the labs cannot buy at a premium is a grid connection on the date the chips arrive.

One hour of one megawattH100 worked case · USD
Electricity$78
Cost to own and run$880
Tokens sold$1,800 to $3,000
Electricity · 9% of the costTokens · at the prices labs collect
Read the article
Case study · 6 min read01

A 67M-unit industrial consumer, optimised

How multi-scenario simulation at 15-minute resolution turned a swinging industrial load and a tightening settlement regime into a decision-grade renewable energy plan.

Read the case study
Case study · 7 min read02

Scheduling a 200 MW IPP portfolio across DAM & RTM

An independent power producer needed to place generation block-by-block across the day-ahead and real-time markets. How forecast-driven bidding turned a daily judgement call into a repeatable schedule, and kept deviation exposure in check.

Read the case study

Built for enterprise trust

Working towards the standards enterprise finance and security teams require, with our controls monitored continuously.

Visit the trust center
  • SOC 2
  • ISO/IEC 27001
  • GDPR

All three in progress

  • No stored keysSystems sign in with short-lived identities, not saved passwords or keys.
  • Controlled changeEvery infrastructure change is versioned and checked before it goes live.
  • AI with sourcesEvery answer shows the data and source it came from. No customer’s data is ever used to train another’s model.

Ready to optimise your energy decisions?

Book a demoExplore the platform

10 GW+

Projects simulated

1 GW+

Assets under operation

$1Bn+

In energy decisions modelled