Investment Notes: CounterCurrent

Investible Climate Tech Fund has made its third investment through the TRaCE co-investment program, alongside UNSW and angel investors.

CounterCurrent offers hyper-local, real-time, vessel-specific route guidance that helps ships harness favourable ocean currents rather than fight against them. Their AI-driven navigation system, often described as a “Google Maps for the sea”, combines advanced ocean models with machine learning to optimie routes dynamically based on currents and eddies. By leveraging more accurate ocean forecasts, ships can reduce fuel consumption and emissions while maintaining transit schedules.

The Pre-Seed round is targeted to convert the current pilot programs into commercial contracts, scale up operations to 10-25 vessels and validate superior performance of their product versus existing competitors.

The sea is getting priced and slow movers will pay for it.

The Ocean Is Now Metered

Since the International MaritimeOrganisation (IMO) turned operational efficiency into mandatory compliance(reporting in 2023 to ratings from 2024 and a Net-Zero Framework with pricing from 2028 onwards), fuel efficiency has moved from a “nice to have” into a quantifiable regulatory and commercial risk. This creates an urgent, high-ROI market for route and voyage optimisation solutions.

The IMO’s EEXI and CII frameworks now rate vessels continuously on carbon intensity, while upcoming carbon pricing mechanisms attach explicit dollar penalties to excess emissions. The global merchant fleet (ships >100) totals~112,500 vessels according to UN Trade and Development and with the global shipping burning ~330 million metric tonnes of fuel annually, this combination makes shipping a significant emitter, accounting for ~2.5% of global CO₂, and creates very large absolute exposure to fuel-price + carbon-price shocks. Fuel burn is no longer just a cost, it’s a regulated performance metric, and even small efficiency gaps now translate into real financial and commercial consequences.

When Incentives and Control Finally Align

At the same time, the industry’s structural incentives have quietly flipped. Ownership and operation are increasingly decoupled: charter/operating control has shifted so owners now directly control only ~40% of fleet capacity in relevant segments; large operator-owners(Maersk, MSC, CMA CGM, COSCO, ONE, Evergreen) command a concentrated share of capacity and therefore the operational levers to change routing and fuel use. This structural shift closes the historical misalignment between the buyer of a solution (operator who pays fuel) and the decision-maker (operator who controls voyages).

Weather and route optimisation sit at the centre of this shift. Proven routing tools already deliver 2–5% fuel savings per voyage, translating into billions of dollars in global fuel savings and immediate protection against regulatory penalties. As data itself becomes commoditised, competitive advantage is moving toward decision quality:higher-fidelity, real-time routing that preserves ETA while cutting fuel and emissions. This is where operational spend, regulatory pressure, and decarbonisation targets now converge, and where the next wave of maritime software adoption is being pulled, not pushed.

Why Weather Intelligence Isn’t Trusted on the Bridge

Most people have experienced this: your Apple or Google weather app says it’s clear, yet it’s raining outside, and you didn’t pack an umbrella. The data isn’t wrong in aggregate; it just isn’t local or timely enough to be useful in that moment.

A similar dynamic plays out on the bridge of a vessel. Captains are often presented with routing or weather recommendations that conflict with what they can see and feel in real time: wave state, vessel motion, current set and drift. When a system recommends a heading that contradicts lived conditions, it is quickly discounted.

This distrust is structural, not behavioural. Most routing tools rely on coarse, global models that are not hyper-local to the vessel’s exact position, hull form, loading condition, or the surrounding mesoscale currents. Critically, they lack real-time feedback from the ship itself. As a result, recommendations often fail to reflect the true conditions the vessel is actually experiencing.

On the bridge, where safety, schedule integrity and professional judgement dominate, tools that cannot earn trust do not get used, regardless of how sophisticated the underlying models appear onshore.

How CounterCurrent Earns Trust on the Bridge

CounterCurrent doesn’t compete on “better forecasts”; it competes on better decisions. Where incumbents such as StormGeo and ZeroNorth rely on shared global models augmented by analyst interpretation, CounterCurrent delivers vessel-specific, hyper-local ocean intelligence that reflects the conditions a ship is actually experiencing in real time.

By resolving conditions at the scale that matters on the bridge, including mesoscale currents and eddies where much of the ocean’s kinetic energy resides,CounterCurrent converts previously invisible dynamics into routing decisions captains can validate against lived conditions. This alignment between recommendation and reality is what drives trust and sustained use.

In initial trials with digital twins, CounterCurrent has demonstrated 13–15% fuel savings, materially exceeding standard routing benchmarks. These gains deliver immediate, recurring cost reductions while simultaneously improving IMO EEXI and CII performance, aligning operator economics with decarbonisation outcomes rather than forcing a trade-off.

A Breakthrough Product With a Structural Data and IPAdvantage

CounterCurrent’s performance is underpinned by a vertically integrated platform comprising Triton (onboard sensing), Hydra (generative ocean forecasting), and Odysseus (AI route optimisation). Together, these components form a closed-loop system that continuously improves with every voyage.

The core advantage isa hardware-enabled data moat. Triton’s in-situ measurements feed directly intoHydra’s models, enabling vessel-specific learning that satellite-only and forecast-only competitors cannot replicate. Each additional vessel strengthens model accuracy and widens the performance gap rather than commoditising it.

CounterCurrent has filed a provisional patent and holds an exclusive licence to UNSW ocean-forecasting IP, while protecting its core forecasting, data assimilation, and optimisation algorithms as trade secrets. This reflects a pragmatic IP strategy in a fast-moving AI domain where integration, iteration speed, and accumulated data matter more than narrow patent claims.

The tight coupling of physics-based ocean modelling, generative AI forecasting, and uncertainty-aware optimisation is technically difficult to replicate and improves with scale, reinforcing durable performance leadership and increasing switching costs overtime.

Who’s building this technology?

CounterCurrent is anchored by deep scientific leadership. CEO and founder Shane Keating is an Associate Professor of Oceanography at UNSW and a globally recognised expert in ocean dynamics, data assimilation, and machine learning–driven forecasting. He brings over 15 years of domain experience across mesoscale ocean modelling, turbulence, and real-time sensing, capabilities that sit at the core of CounterCurrent’s generative forecasting engine (Hydra) and its route-optimisation thesis.

Importantly, Shane is not approaching this as a purely academic exercise. Our engagement with him demonstrated strong product intuition and a clear understanding of operational realities on the bridge, including the central role of trust, usability, and repeatable performance under live conditions. His scientific approach is explicitly grounded in deployment, with a focus on systems that learn from in-situ vessel data rather than static, global models. Shane is also thinking commercially from day 0 and doesn’t shy from sales conversations.

Beyond Shane, CounterCurrent is supported by a small, highly technical team spanning oceanography, applied machine learning, and software engineering. Team members have backgrounds across ocean sensing, numerical modelling, and production-grade software systems, and have been directly involved in the development of the Triton sensing stack, the Hydra forecasting pipeline, and the Odysseus optimisation layer. This group has been instrumental in translating advanced ocean physics into a deployable, operator-facing product.

Investible are excited to be riding this momentous wave with Shane and his team, and we look forward to seeingCounterCurrent make the ocean finally work for shipping’s bottom line.