Skip to content
Open App
 
Aquaculture Data + Intelligence

The Intelligence
Platform for
Aquaculture.

We help teams understand how biology, farming practices, and products interact. Explain outcomes, anticipate what's next, and improve with every production cycle.

Explore your application See how Manolin works
Kvarøy
Hofseth
Veramaris
Cargill
The data problem We Solve

Operations create data everywhere.

Production, feeding, health, environment, transport, and site operations all generate records. Each system captures a different part of the biological story.

Different systems hold different pieces of the same history.

As records leave their source systems, inconsistent identifiers, formats, and timestamps prevent them from arriving as one coherent history.

Reconstruction becomes the work before the work.

Teams spend time matching fragments, resolving gaps, and determining which events belong to the same fish population before analysis can begin.

Structure turns fragments into an analytical foundation.

When entity lineage and events are normalized together, the historical context needed for comparison and investigation becomes usable.

Then the investigation can actually start.

The questions farms and suppliers need to answer become much clearer when they begin from one structured history rather than disconnected records.

manolin // continuity tracefish-production data system
site + pen wellboat operations feed records environment health + treatment
site_24 / cage_08
boat_transfer / time
feed_lot / dosage
oxygen / temp / current
evt_treatment / mech
same history // different records
normalized fish historyinvestigation-ready
ENTITYgroup_17 → site_24 → cage_08linked
EVENTSfeed + treatment + transfer + healthaligned
CONTEXTenvironment + operations + generation retainedready
For farms // operational investigation

Why did treatment performance diverge between two sites?

What changed this generation compared with the last?

Which conditions shaped the mortality event?

For suppliers // field evidence

Did the product drive the outcome, or were other variables involved?

Where does the signal remain consistent?

What should R&D investigate next?

The data problem // 01

Operations create data everywhere.

Production, feeding, health, environment, transport, and site operations all generate records. Each system captures a different part of the biological story.

fish-production data sources
site_24 / cage_08 boat_transfer / time feed_lot / dosage oxygen / current treatment / mech
The data problem // 02

Different systems hold different pieces of the same history.

As records leave their source systems, inconsistent identifiers, formats, and timestamps prevent them from arriving as one coherent history.

record fragmentation
site_24 / cage_08 boat_transfer / time feed_lot / dosage oxygen / current treatment / mech
same history // different records
The data problem // 03

Reconstruction becomes the work before the work.

Teams spend time matching fragments, resolving gaps, and determining which events belong to the same fish population before analysis can begin.

manual reconstruction
 
site_24 / cage_08 → group_17 ?
treatment_event → source timestamp ?
feed_lot → exposure window ?
mortality → generation context ?
The data problem // 04

Structure turns fragments into an analytical foundation.

When entity lineage and events are normalized together, the historical context needed for comparison and investigation becomes usable.

normalized continuity
normalized fish historyentity + event model
ENTITYgroup_17 → site_24 → cage_08linked
EVENTtransfer → feed → treatment → observationaligned
TIMEsource timestamps reconciledordered
CONTEXThealth + environment + operations retainedready
The data problem // 05

Then the investigation can actually start.

The questions farms and suppliers need to answer become much clearer when they begin from one structured history rather than disconnected records.

investigation-ready history
normalized fish historyready
ENTITYgroup_17 → site_24 → cage_08linked
EVENTSfeed + treatment + transfer + healthaligned
CONTEXTenvironment + operations + generation retainedready
For farms // operational investigation

Why did treatment performance diverge between two sites?

What changed this generation compared with the last?

Which conditions shaped the mortality event?

For suppliers // field evidence

Did the product drive the outcome, or were other variables involved?

Where does the signal remain consistent?

What should R&D investigate next?

the manolin data network

How we deliver trusted aquaculture intelligence.

Trusted by the world's leading aquaculture companies.

Generations analyzed
Fish traced
Data points modeled
Avg. model accuracy
Years of global data
connect your existing data systems

Get more value out of the data running your operations.

Manolin does not require a new hardware layer or a replacement for the systems your teams already use. It connects the records between them and reconstructs the data context behind the analysis.

01

Production systems

Biomass, transfers, splits, merges, site movements, and harvest records.

02

Feeding systems

Feed delivery, appetite, composition, growth, and production performance.

03

Fish health records

Mortality, disease, lice, welfare observations, and intervention histories.

04

Environmental data

Temperature, oxygen, salinity, weather, and regional pressure context.

05

Laboratory and veterinary data

Samples, diagnoses, field notes, and the clinical context behind decisions.

06

Product and operational records

Treatments, vaccines, feed products, genetics, and site-level activity.

Discuss your data environment
Frequently asked questions

Understand what's behind the platform.

These are the most common questions teams usually ask when they first evaluate the platform.

Our technology
What is Manolin?

Manolin is the platform for aquaculture data intelligence. It connects fragmented farm data, reconstructs the history behind each fish population, and gives teams a more coherent foundation for investigation, reporting, and product-performance analysis.

What does population tracing mean in aquaculture?

Fish populations move through splits, merges, transfers, changing sites, and changing conditions. Population tracing preserves the record behind those movements so teams can compare outcomes against the right biological history rather than only the current cage location.

Does Manolin replace our existing farm systems?

No. Manolin is designed to work with the systems already running the operation. It connects production, feeding, health, environmental, laboratory, and operational records into a population-level traced intelligence layer.

What is the difference between Watershed and Harpoon?

Watershed is the farm-intelligence application. It supports fish-health risk investigation, intervention comparison, reporting, and audit readiness. Harpoon is the supplier-intelligence application. It connects commercial farm data to product usage so R&D and product teams can evaluate observed performance and prioritize the next study.

How does Manolin handle farm and supplier data confidentiality?

Manolin structures analysis around data anonymization, controlled access, clear permissions, and the appropriate level of aggregation for the use case. Supplier analysis is designed to support evidence generation without exposing farm-level information outside the agreed scope.

How is Manolin different from dashboards, BI tools, or general AI assistants?

Dashboards and AI assistants can summarize the records they receive. Manolin adds the aquaculture-specific infrastructure required before that analysis begins: population tracing, data cohesion, domain context, and models built around the biological system.

Start with your application

Run your next analysis with Manolin's intelligence.

Explore how our intelligence software changes the way your team works with farm risk, reporting, and commercial product evidence.

For farms // Watershed

Investigate fish health risk with the fish history intact.

Connect fish records, compare outcomes, and prepare a clearer evidence trail for the questions your team needs to answer.

Explore Watershed
For suppliers // Harpoon

Build more defensible product evidence from the field.

Evaluate observed performance across comparable farm sites and identify the next question your team should investigate.

Explore Harpoon