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Smart-grid intelligence

The grid, worst-first, with the reasoning attached.

Network risk, transformer health, and demand — ranked by what deserves attention now, each with the method that produced it.

Today Transformers fail unseen. Planning runs on stale single-line diagrams and gut feel.
The future A grid that sees itself — every asset watched, failures predicted, every capex rupee placed by physics.
How we get there Load flow on your real topology, agents watching thermal stress, spend ranked by re-solved loss reduction.
What it decides

Decisions with the case attached. Not another dashboard.

Which feeder breaches at peak
Load-flow on your own topology, not a generic model.
Which transformer fails next
Asset health ranked worst-first, before the monsoon decides for you.
Where the capex rupee works hardest
Reconductoring ranked by loss reduction per rupee — each claim re-solved, not assumed.
How much solar the network can host
Headroom per transformer before voltage or thermal limits bind.
What load is coming
Forecasts that state their uncertainty as bands — never a certain-sounding guess.
Whether the network survives a fault
Contingency analysis on the real network, worst cases first.

activates on your network model & meter feed

Operations, previewed

The control-room surface, on your grid.

The map owns the fold; the worklist stacks below. Shown here as a marketing preview — the working surface runs on your network.

Sutra grid operations surface — network map with ranked worklist
How we engage

Start with the feeders that worry you most.

One bounded zone, forward-deployed, an exit clause from day one. The license that follows is flat per DISCOM — it does not grow as you add meters.

Sutra.
The audited utility intelligence layer for India's power distribution.
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