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Maritime · head to head

Bearing AI vs Vortexa

Bearing AI logo

Bearing AI

Maritime

Machine learning vessel performance models for voyage and commercial decisions, embedded in partner platforms

From
On request
Rated
-
Full reviewWebsite
Vortexa logo

Vortexa

Maritime

Real-time seaborne energy cargo flow data sold as a subscription to a feed, not an application

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Bearing AI bearing increasingly reaches customers embedded in partner platforms such as StormGeo, so the contract, support path and commercial relationship may be with the partner rather than with Bearing.; Vortexa cargo attribution is inference from AIS, imagery and pattern analysis, not measurement, so grade and volume figures carry an error band that matters if you size a position on them and the vendor cannot fully quantify it for every route.
  • They diverge on capability: Bearing AI covers Vessel-specific consumption models, Vortexa covers Cargo-level flow tracking.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Bearing AI and Vortexa actually diverge.

Attributes where Bearing AI and Vortexa differ
AttributeBearing AIVortexa

Identical on both: starting price (On request), pricing model (quote), free tier (No), platforms (Web, Cloud, API), user rating (Not yet rated), category (Maritime).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Bearing AI

  • Vessel-specific consumption models
  • Speed optimisation
  • Emissions forecasting
  • Voyage evaluation
  • AIS-derived data
  • Weather-aware routing inputs
  • Fleet benchmarking
  • Partner platform embedding

Only in Vortexa

  • Cargo-level flow tracking
  • Multi-commodity coverage
  • Floating storage analytics
  • API, Excel and Python access
  • Anywhere Freight Pricing
  • Satellite and AIS fusion

What people use each for

The jobs each tool is most often brought in to do.

Bearing AI

  • A chartering desk evaluating fixtures against learned consumption rather than a delivery-era speed and consumption tablenot Vortexa
  • Projecting a vessel CII rating for a planned trading pattern before committing to itnot Vortexa
  • Identifying which sister ship in a series is underperforming because of hull condition rather than routingnot Vortexa
  • Feeding realistic consumption predictions into an existing voyage optimisation platform through an APInot Vortexa

Vortexa

  • A crude trading desk sizing a position on inferred cargo flows into a region before customs data confirms them weeks laternot Bearing AI
  • A shipowner assessing tonne-mile demand and ballast patterns to decide where to reposition vesselsnot Bearing AI
  • A refiner tracking competing product cargoes arriving into its market to anticipate margin pressurenot Bearing AI
  • A research team pulling flow data into Python models rather than reading a vendor dashboardnot Bearing AI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Bearing AI

  • Bearing increasingly reaches customers embedded in partner platforms such as StormGeo, so the contract, support path and commercial relationship may be with the partner rather than with Bearing.
  • Model accuracy depends on the volume and honesty of historical voyage data, and fleets with sparse or inaccurate noon reporting get materially weaker vessel-specific models.
  • It is a modelling layer rather than a voyage management system of record, so it must be bought alongside a platform that handles the operational workflow.
  • As a venture-funded specialist with a small headcount, its long-term independence is uncertain, and a modelling layer inside someone else product is a fragile position if a partnership lapses.
  • Nothing is published on pricing or fleet size thresholds, so small owners cannot tell whether they are a viable customer without entering a sales process.

Vortexa

  • Cargo attribution is inference from AIS, imagery and pattern analysis, not measurement, so grade and volume figures carry an error band that matters if you size a position on them and the vendor cannot fully quantify it for every route.
  • What you buy is a feed rather than an application, so a firm without quantitative capability to consume it gets far less value than the subscription costs, and the terminal alone rarely justifies the price.
  • Pricing is by seat and by data scope with nothing published, so cost scales with how many analysts need access, which discourages exactly the broad internal distribution that would make the data useful.
  • It overlaps materially with other commodity flow subscriptions and price reporting services, and most desks that buy Vortexa are paying twice for a partly duplicated picture.
  • Coverage quality varies by trade and region; dark fleet activity, ship-to-ship transfers and sanctioned trades are the hardest cases and also the ones where accurate data is worth the most.

Pricing, plan by plan

Bearing AI

On request
  • Bearing AI$undefined/year
    • Priced per vessel per year on annual agreements
    • Often purchased indirectly as a component of a partner voyage optimisation service
    • Model onboarding requires historical voyage data supplied by the customer

Vortexa

On request
  • Vortexa$undefined/year
    • Subscription priced by seat and by data scope
    • API, Excel add-in and Python SDK access licensed separately from terminal seats
    • Commodity coverage selectable, crude, products, LPG, LNG

Which should you pick?

Choose Bearing AI if

  • You need vessel-specific consumption models.
  • You work on Web, Cloud, API.
  • You also want speed optimisation.
Bearing AI review

Choose Vortexa if

  • You need cargo-level flow tracking.
  • You work on Web, Cloud, API.
  • You also want multi-commodity coverage.
Vortexa review

Questions people ask

Is Bearing AI or Vortexa better?
Neither clearly leads. Bearing AI starts at On request and Vortexa at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Bearing AI or Vortexa?
Bearing AI starts at On request and Vortexa at On request.
Does Bearing AI or Vortexa run on more platforms?
Both run on Web, Cloud, API, so platform support will not decide this one for you.
What is Bearing AI best used for?
Bearing AI is most often used for a chartering desk evaluating fixtures against learned consumption rather than a delivery-era speed and consumption table, projecting a vessel cii rating for a planned trading pattern before committing to it, identifying which sister ship in a series is underperforming because of hull condition rather than routing, feeding realistic consumption predictions into an existing voyage optimisation platform through an api. Of those, a chartering desk evaluating fixtures against learned consumption rather than a delivery-era speed and consumption table and projecting a vessel cii rating for a planned trading pattern before committing to it are not what Vortexa is typically brought in for.
What can Bearing AI do that Vortexa cannot?
Bearing AI covers Vessel-specific consumption models, Speed optimisation, Emissions forecasting, Voyage evaluation. Vortexa covers Cargo-level flow tracking, Multi-commodity coverage, Floating storage analytics, API, Excel and Python access.

Answered from the vendors’ own pages

Bearing AI: Can I buy Bearing AI directly?

Yes, but a growing share of its distribution is through partners such as StormGeo, where the models are embedded in that vendor voyage optimisation service.

Vortexa: Is Vortexa an application or a data feed?

Fundamentally a data feed. There is a web terminal, but the API, Excel add-in and Python SDK are how most subscribers actually use it.

Bearing AI: Does it replace a voyage management system?

No. It is a performance modelling layer that feeds commercial and operational decisions made in another system.

Vortexa: Are the cargo volumes measured or estimated?

Estimated. Vortexa infers cargo, grade and volume from AIS, satellite imagery and pattern analysis. Treat the numbers as estimates with an error band.

Bearing AI: What data does it need?

Historical voyage data, noon reports and AIS positions, plus weather history. Data quality drives model quality directly.

Vortexa: How is it priced?

By seat and by data scope, quoted annually. Redistribution and derived-data rights are negotiated separately and matter for internal use.

Bearing AI: Does it cover CII?

Yes, it projects CII ratings from the learned vessel model rather than from nominal consumption figures.

Vortexa: Does it cover LNG and LPG as well as oil?

Yes, alongside crude and refined products, though commodity scope affects what you pay.

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