Get started. Raise the bar.

Built to match your specific needs, eOceans® is the first* all-in-one platform — processing desired biological, environmental, pollution, socio-economic, cultural, and operational inputs from field team observations, sensors, eDNA, historical datasets, and more. As you add data, it generates auditable insights and reports. The app and platform work for any study area, supports over one billion variable combinations, and automates any repetitive analyses. Accelerate workflows, everywhere on our blue planet.
*patent pending.

Watch the series: "Why we built it”.

Track everything, everywhere

Big or small, local or global—your projects can use any data sources, include any team members, and engage any collaborators.

1 billion+ variable combinations—

All metrics in one place

Your efforts, species, activities, biodiversity, pollution, social values, fisheries, policies, markets, diseases, engagement, and more.

A collage of four images: a person jumping from a rock into the ocean, a lion walking on a rocky terrain, an underwater scene with seaweed and yellow bubble-like structures, and a fishing scene with boats, a canoe, and baskets of fish on a beach.

Backed by experts—

Credibility, Auditability needed

Built by PhD scientists — experts in socio-ecology, environmental monitoring, and policy — eOceans handles all your complex data tasks. It’s like having a million dollar data science team working full-time on your project.

Person working at desk with two monitors displaying spreadsheets and charts.

Opportunities unlocked—

Act on insights, drive opportunity

With near real-time updates, eOceans reveals emerging opportunities—so you and your stakeholders can move faster and make smarter decisions, actions, and investments.

Laptop screen displaying an environmental project dashboard for eOceans with fish images, data charts, a heat map, and navigation menu.

Data used, without delays—

Mobilise data, on demand

Magic Uploads™ turns your existing data into instant insights—helping you act faster, demonstrate impact, and build trust. Clean datasets can also be downloaded for maximum use and efficiency.

A digital infographic illustrating a data workflow. It shows a CSV file transferring data to eOceans, which then connects to a laptop displaying a project dashboard with various graphs and charts, under the headline 'Magic Uploads™ & Data Downloads'.

Scale—

Collaborate locally, globally

With eOceans, it's easy to link efforts across projects, teams, regions, and scales. The Ocean Ledger™ and Global Biodiversity Ledger™ are built right in the app to make it effortless to set shared goals and track success.

Screenshot of the Ocean Ledger's global observations map from eOceans, showing worldwide locations of ocean species observations with color-coded intensity bar on the right.

Everything you need, all in one place.

Infographic illustrating data management processes, including data management, storage, collection, communications, onboarding, analysis, maps, graphs, reports, and dissemination, with checkmarks next to each.

Old, manual tools are insufficient for today’s fast changing world.

Paper logsheets?

Messy handwriting in the field, then hours spent re-entering data into spreadsheets—doubling the time and risk of mistakes.
R and GIS?

Using R and GIS can easily eat up hundreds to thousands of hours.
Data to be used 'later'?

Data analysis reveals what’s happening and what’s needed—but most data goes unused, underused, or delayed. That’s wasted effort, costing time, money, credibility, and smarter decisions.
Open Acces 'Free' apps?

Nothing is “free.” Who owns data and who can access it matters. All risks must be disclosed and mitigated in research. Some communities — including tourism groups, fisheries, and First Nations — have called for bans on open-access nature-logging apps after harvesters used them to locate medicinal plants and animals. The open-access model must be used with care.
Consultants?

If you don’t have in-house data science experts, expect to spend $60,000–$150,000+ per project—and still start from scratch next time. Efficiency is key.
In-house data science?

Just one data scientist can take 8 months to execute even a small data project—at $100/hour, that’s $140,000. Shouldn’t their time be spent on important tasks, not on basics like data cleaning and exploratory analysis?
Phone hotlines?

Many organizations still use phone hotlines for public reports—animals, injured animals, pollution, illegal activities, invasive species, and more—but the experience is frustrating, leading to apathy, underused data, and growing conflict.
Guessing, without data?

Decision making—without analysed data—means you are left guessing. What’s the cost of getting it wrong?