Maritime · head to head
Bearing AI vs SpeedyDock
Bearing AI
Maritime
Machine learning vessel performance models for voyage and commercial decisions, embedded in partner platforms
- From
- On request
- Rated
- -
SpeedyDock
Maritime
Dry stack, boat club and boat rental operations software with member launch scheduling
- From
- On request
- Rated
- -
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.; SpeedyDock nothing about pricing is published, so evaluating SpeedyDock requires a sales conversation before any cost comparison is possible.
- They diverge on capability: Bearing AI covers Vessel-specific consumption models, SpeedyDock covers Member launch requests.
- Prices and features above were last checked on 1 September 2026.
Where they differ
Only the attributes on which Bearing AI and SpeedyDock actually diverge.
| Attribute | Bearing AI | SpeedyDock |
|---|---|---|
| Platforms | Web, Cloud, API | Web, iOS, Android |
Identical on both: starting price (On request), pricing model (quote), 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 SpeedyDock
- Member launch requests
- Launch queue scheduling
- Yard dispatch
- Fleet management
- Digital agreements
- Reservations and billing
- Utilisation reporting
- Member communication
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 SpeedyDock
- Projecting a vessel CII rating for a planned trading pattern before committing to itnot SpeedyDock
- Identifying which sister ship in a series is underperforming because of hull condition rather than routingnot SpeedyDock
- Feeding realistic consumption predictions into an existing voyage optimisation platform through an APInot SpeedyDock
SpeedyDock
- A dry stack marina sequencing Saturday morning launch demand against limited forklift timenot Bearing AI
- A boat club letting members reserve vessels and request launches from their phonenot Bearing AI
- A rental fleet tracking vessel availability, agreements and maintenance in one placenot Bearing AI
- An operator replacing a whiteboard and radio dispatch process in the yardnot 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.
SpeedyDock
- Nothing about pricing is published, so evaluating SpeedyDock requires a sales conversation before any cost comparison is possible.
- It is built around dry stack and rental operations, so a marina whose business is wet slips, seasonal contracts and transient dockage will find most of the product irrelevant.
- There is no consumer marketplace, so unlike Dockwa it generates no demand; it makes an existing membership base easier to serve rather than growing it.
- Deployment and support are concentrated in the United States, which limits it for operators elsewhere and means integrations assume American payment and accounting tooling.
- As a narrow single-purpose system it usually sits alongside separate accounting, storage billing or general marina software rather than replacing them, so it adds a system rather than consolidating one.
Pricing, plan by plan
Bearing AI
On request- Bearing AI$undefined/year
- Priced per vessel per year on annual agreements
- Often purchased indirectly as a component of a partner voyage optimisation service
- Model onboarding requires historical voyage data supplied by the customer
SpeedyDock
On request- SpeedyDock$undefined/month
- Quoted by facility size and modules selected
- No published rate card or self-serve signup
- Setup and onboarding charged separately
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.
Choose SpeedyDock if
- You need member launch requests.
- You work on Web, iOS, Android.
- You also want launch queue scheduling.
Questions people ask
- Is Bearing AI or SpeedyDock better?
- Neither clearly leads. Bearing AI starts at On request and SpeedyDock at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Bearing AI or SpeedyDock?
- Bearing AI starts at On request and SpeedyDock at On request.
- Does Bearing AI or SpeedyDock run on more platforms?
- Bearing AI runs on Web, Cloud, API. SpeedyDock runs on Web, iOS, Android.
- 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 SpeedyDock is typically brought in for.
- What can Bearing AI do that SpeedyDock cannot?
- Bearing AI covers Vessel-specific consumption models, Speed optimisation, Emissions forecasting, Voyage evaluation. SpeedyDock covers Member launch requests, Launch queue scheduling, Yard dispatch, Fleet management.
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.
SpeedyDock: What does SpeedyDock cost?
It is quoted by facility size and the modules you take. There is no published price list and no self-serve signup.
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.
SpeedyDock: Is it a general marina management system?
No. It is built for dry stack, boat club and rental operations where launch scheduling and fleet availability are the core problems.
Bearing AI: What data does it need?
Historical voyage data, noon reports and AIS positions, plus weather history. Data quality drives model quality directly.
SpeedyDock: Does it bring in new customers?
No. There is no marketplace or booking demand attached; it serves the members and renters you already have.
Bearing AI: Does it cover CII?
Yes, it projects CII ratings from the learned vessel model rather than from nominal consumption figures.
SpeedyDock: Why not use a normal marina system?
Because berth and contract software has no model for retrieval order, forklift capacity or launch queues, which is the actual constraint in a dry stack operation.
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