Year: 2026

For months we’ve been mining verified, publicly available EU MRV submissions at vessel level and turning them into something concrete: for each ship in your fleet, three cost drivers that compound simultaneously.

• Fuel-efficiency gap — what each vessel burns above its within-fleet median, priced per year ($).
• CII charter-rate exposure — the charter sensitivity of a deteriorating CO₂-intensity trajectory (a derived peer-band proxy, not an official IMO rating).
• EU ETS procurement savings — what forward-purchasing EUAs ahead of the September 2026 surrender is worth vs buying at the deadline.

Every figure comes back with a vessel name, a cause and a recommended action. No input required from your side for the first brief — we reconstruct it entirely from public data. The interpretation is ours; you just have to look at yours.

→ Get your fleet’s brief Run your company through the same pipeline and get a complimentary brief — fuel gap, CII exposure and ETS saving — in days, not weeks.

Figures are indicative; the peer band is a derived percentile of CO₂ intensity within the ship-type cohort — a commercial proxy for decision-support, not an IMO CII result or regulatory penalty.

Every vessel in the 2025 MRV book — 14,370 ships, 10 types, 3,736 operators — scored on real data, not a demo.

• See the band shape at a glance. Live A–E distribution per ship type, so you know where your fleet sits before you open a single file.
• Filter like an operator. Type, CII band, operator, percentile range, FuelEU 2030 status — or just type a name and hit enter. Sort on any metric.
• Open a vessel, get the story. CII band & percentile, CO₂ per nautical mile, P(D/E) risk score, charter sensitivity in $, ETS exposure, and FuelEU screening — plus its full 2021→2025 trajectory.
• Know your own fleet. Sister-fleet view groups same-operator × same-type ships and puts your percentile delta against them front and center — where you stand, not where the market does.
• FuelEU-ready. GHG intensity in g/MJ and a clean 2030 compliant / over-target read for every ship.

No build step. No spin-up. Load it, filter, click through — your fleet is one refresh away. → Check our dashboard

Since January 2024, maritime transport has been included in the EU Emissions Trading System (EU ETS). Ships within scope now have obligations to monitor, report, and ultimately surrender EU allowances for covered greenhouse-gas emissions. The phase-in is 40% for 2024 emissions, 70% for 2025 emissions, and 100% from 2026 emissions onward, with surrender taking place in the following compliance cycle. The geographical scope also matters: emissions are treated differently for voyages between EU/EEA ports, voyages between an EU/EEA port and a non-EU/EEA port, and emissions occurring while ships are at EU/EEA ports.

In parallel, FuelEU Maritime, Regulation (EU) 2023/1805, applies from 2025 and introduces a different compliance mechanism based on the greenhouse-gas intensity of energy used on board ships. Its requirements are expressed on a well-to-wake basis and become progressively more stringent over time.

And alongside the EU regimes sits the IMO’s Carbon Intensity Indicator (CII) framework. Since 2023, applicable ships have been required to calculate an annual operational CII and receive an A-to-E rating. A ship rated E for one year, or D for three consecutive years, must submit a corrective action plan showing how it will achieve a C rating or better.

These regimes overlap in their underlying operational data, but they are not three versions of the same calculation.

• EU ETS is an emissions-allowance regime.
• FuelEU is an annual greenhouse-gas-intensity and compliance-balance regime.
• CII is an IMO operational carbon-intensity rating regime.

That distinction matters.

A single voyage can generate data relevant to all three systems, but the resulting compliance calculations operate over different scopes, time periods, methodologies, and regulatory definitions.

The practical result is a data and software problem:

the same fuel-consumption and voyage records may feed several regulatory engines, but those engines cannot safely share the same assumptions.

Most operators still rely heavily on spreadsheets, manually maintained calculation tools, or internal systems whose regulatory assumptions are difficult to inspect and reproduce.

That is where a purpose-built calculation library can help—but only if the software treats the regulations as versioned rules rather than as a handful of constants.

Asset-integrity teams live with a recurring failure mode: a corrosion or remaining-life model arrives with impressive demo numbers, and then the conversation stops. What is the model actually doing? Is its rate within published literature for X65 carbon steel in atmospheric service? Does it hold up when you replay real survey history? Can your buyer’s engineer reproduce your numbers, not just trust a screenshot?

“Trust the vendor” is not a validation strategy. It’s how you get a surprise corrosion event three years after commissioning — and a very awkward conversation with whoever signs the integrity plan.

The Model Validation Framework (MVF) is a staged, evidence-producing pipeline that puts a degradation engine under test before it earns a seat in your integrity workflow:

Two design decisions matter more than any metric:

1. The engine is imported as a pinned library. MVF does not fork, wrap, or “improve” vendor math. The report names the exact engine commit, so there is no ambiguity about what was tested.
2. Every report carries a provenance block — framework version, git SHA, engine commit, dataset checksums, config hash, run stamp — and is deterministic for a given stamp. A buyer re-running the pipeline gets byte-identical numbers. That sentence is the whole business case in miniature.