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Maritime · head to head

Bearing AI vs MDS Transmodal

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
MDS Transmodal logo

MDS Transmodal

Maritime

Freight transport data and analysis

From
$600/month
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.; MDS Transmodal no pricing published on website, consulting-based engagement only
  • They diverge on capability: Bearing AI covers Vessel-specific consumption models, MDS Transmodal covers Container trade data.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Bearing AI and MDS Transmodal actually diverge.

Attributes where Bearing AI and MDS Transmodal differ
AttributeBearing AIMDS Transmodal
Starting priceOn request$600/month
Pricing modelquotesubscription
PlatformsWeb, Cloud, APIWeb
FoundedUnknown1988

Identical on both: free tier (No), 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 MDS Transmodal

  • Container trade data
  • Port statistics
  • Intermodal analysis
  • Custom research
  • Data exports
  • Custom reports
  • Web support

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 MDS Transmodal
  • Projecting a vessel CII rating for a planned trading pattern before committing to itnot MDS Transmodal
  • Identifying which sister ship in a series is underperforming because of hull condition rather than routingnot MDS Transmodal
  • Feeding realistic consumption predictions into an existing voyage optimisation platform through an APInot MDS Transmodal

MDS Transmodal

  • Transport market feasibility studies and demand forecasting for new opportunitiesnot Bearing AI
  • Infrastructure planning and transport network capacity analysisnot Bearing AI
  • Due diligence and risk assessment for freight investment decisionsnot Bearing AI
  • Freight sector policy analysis and regulatory impact evaluationnot Bearing AI
  • Quantitative modeling across maritime, rail, road, and logisticsnot 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.

MDS Transmodal

  • No pricing published on website, consulting-based engagement only
  • Requires direct contact and negotiation for each project engagement
  • Results and services dependent on consultant experience and proprietary databases
  • Not a self-service platform, requires human expertise and custom analysis

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

MDS Transmodal

$600/month
  • Data Access$1200/month
    • Container data
    • Port statistics
    • Trade flows

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 MDS Transmodal if

  • You need container trade data.
  • You also want port statistics.
MDS Transmodal review

Questions people ask

Is Bearing AI or MDS Transmodal better?
Neither clearly leads. Bearing AI starts at On request and MDS Transmodal at $600/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Bearing AI or MDS Transmodal?
Bearing AI starts at On request and MDS Transmodal at $600/month.
Does Bearing AI or MDS Transmodal run on more platforms?
Bearing AI runs on Web, Cloud, API. MDS Transmodal runs on Web.
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 MDS Transmodal is typically brought in for.
What can Bearing AI do that MDS Transmodal cannot?
Bearing AI covers Vessel-specific consumption models, Speed optimisation, Emissions forecasting, Voyage evaluation. MDS Transmodal covers Container trade data, Port statistics, Intermodal analysis, Custom research.

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.

MDS Transmodal: How much does MDS Transmodal cost?

MDS Transmodal does not publish pricing on its website. It is a consulting firm providing bespoke strategic advice. Pricing is quote-based and depends on project scope, duration, data requirements, and consultant time allocation. Contact them directly to discuss your specific transport economics needs.

Source
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.

MDS Transmodal: Does MDS Transmodal offer a software platform or only consulting?

MDS Transmodal is primarily a transport economics consulting firm, not a software vendor. They provide strategic consulting, quantitative analysis, and modeling services. While they maintain proprietary databases and models, they do not offer a self-service software platform.

Source
Bearing AI: What data does it need?

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

MDS Transmodal: Does MDS Transmodal cover all transportation modes?

Yes. MDS Transmodal provides analysis and consulting across road, rail, air, and maritime freight sectors. Their expertise spans port connectivity, global shipping networks, trade corridor analysis, and multi-modal supply chain optimization for clients worldwide.

Source
Bearing AI: Does it cover CII?

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

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