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Shrimp farm management software

AquaOS is shrimp farm management software for pond-level stocking, feeding, mortality and water quality. A shrimp operation is a set of ponds that each run their own cycle, on their own feed curve, with their own water. AquaOS holds each pond as its own production record and rolls them up when you need the farm view.

The pond status report listing fish count, average weight and total weight for every pond, split by species
Inventory per pond, as of any date, exportable to Excel or PDF
  • Pond-level stocking and cycles
  • Feed tables by species and weight band
  • Cellular monitoring for remote clusters
  • Site and multi-site rollups

How AquaOS fits the pond cycle

Each pond is its own cycle

Ponds stock, grow, and harvest on their own schedule.

Each carries its own batch, its own feed record, its own mortality, and its own water quality history. The farm view is a rollup of those records rather than a substitute for them.

Feed tables by weight band

Shrimp feeding is driven by a table of rates against weight band and phase, and that table is farm-specific.

AquaOS holds the operation own matrix and calculates a daily ration per pond from current biomass, so the plan changes as the animals grow without anyone re-deriving it.

Feed cost visibility

Feed is the dominant cost in a shrimp cycle.

Confirmed feedings become the feed record, feed items draw down stock, and runway shows how many days remain before the next delivery has to land.

Remote pond clusters

Pond clusters are rarely near a network.

Controllers are cellular-native, so monitoring reaches ponds with no site infrastructure, and readings buffer locally when the cellular link drops.

Water quality where it decides the cycle

Dissolved oxygen, temperature, pH, and salinity-related parameters read continuously and bound to the pond.

Threshold alarms reach the people on duty, and the reading history sits on the same report as the mortality it explains.

Partial and staged harvest

Stock can leave a pond partially, whether for a staged harvest or a transfer.

The residual remains an accurate live placement, so the pond keeps reporting a correct count and the feed plan follows it down.

Two workers on a shrimp pond levee pick shrimp out of a cast net into a basin for the weekly growth sample, with paddlewheel aerators running behind them

What changes across a cycle

Feed conversion per pond, not per farm

A farm-level FCR hides the ponds that are performing badly behind the ones that are not. Per-pond records make the variance visible while there is still cycle left to act on.

Night events have a record

An overnight oxygen event on a remote pond is captured with timestamps, whether or not anyone was watching, and the mortality that followed sits next to it.

Cycle comparison

Because each pond keeps its complete history after harvest, this cycle can be compared against the last one on the same pond, in growth, feed, and mortality.

Frequently asked questions

Does AquaOS work for vannamei and monodon?

Yes. Species and varieties are configured per operation, and the feed matrix is defined per species and weight band by the farm. The platform does not assume a species, which is also why it runs for operations that keep more than one.

Can it handle a farm with dozens of ponds across several sites?

Yes. The platform is multi-site and multi-user. Each pond is a growing unit under a site, each site has its own units and users, and reporting rolls up from the pond to the site to the whole operation.

How does monitoring reach ponds with no network?

Field controllers connect over cellular and need no site network. When cellular drops, readings are buffered on the controller and delivered when it recovers, so the history has no gap for the period the link was down.

Can we start with production tracking and add sensors later?

Yes. Stocking, feeding, mortality, and reporting all work on manually entered data. Sensors join the same record whenever they are installed, without redoing the setup.

See AquaOS on your operation

Bring a real production scenario. AquaOS is walked through on your operation, not a canned dataset.