Comparison
Mirage vs Shipamax
Both companies use machine learning to extract data from freight documents without templates. The difference is how the system gets deployed and who owns the integration work.
Executive Summary
Mirage and Shipamax both process unstructured freight documents, bills of lading, commercial invoices, accounts payable invoices, using machine learning rather than template-based OCR. Neither requires you to maintain per-supplier or per-carrier templates.
Shipamax is positioned as a software product: it syncs with your email inbox and existing TMS or ERP (including CargoWise) in real time, running document classification and extraction through a four-stage ML pipeline.
Mirage's logistics agent is deployed through forward-deployed engineering: Mirage engineers work inside your operation to map your specific document formats and wire the agent into your systems, rather than a self-service software rollout.
The core extraction approach is similar between the two. The practical difference for a buyer is deployment model: self-configured software product versus an engineering team embedded in your operation during rollout.
Key Takeaways
- Both Mirage and Shipamax use machine learning instead of templates for freight document extraction.
- The main difference is deployment model: forward-deployed engineering versus a self-configured software product.
- Neither publishes a single headline accuracy percentage: Mirage publishes per-deployment results (OFRET Groupe, Transwin), Shipamax describes its approach without one.
- Both integrate with CargoWise; the deciding factor is usually how much embedded engineering support you want during rollout.
At a Glance
| Aspect | Mirage | Shipamax |
|---|---|---|
| Extraction approach | AI agent, no template dependency | Machine learning models, no rules or templates to maintain |
| Deployment model | Forward-deployed engineers integrate the agent into your systems | Software product configured to sync with your email and TMS/ERP |
| Reported accuracy | No single accuracy figure published: per-deployment results instead, 90%+ of standard freight RFQs answered automatically (OFRET Groupe) and 70% less manual data entry on freight documents (Transwin) | Not publicly quantified in Shipamax's own materials |
| Deployment time | 2-4 weeks for most Logistics deployments | Not publicly specified |
| System integration | CargoWise, Descartes, Amber Road, and custom TMS/ERP via API and EDI/SFTP | CargoWise and other logistics systems, real-time email sync |
| Document scope | Bills of lading, commercial invoices, customs declarations, CMRs, carrier paperwork | Bills of lading, commercial invoices, accounts payable invoices |
| Team involvement | Mirage engineers embedded in your operation during and after rollout | Shipamax team supports configuration; workflow runs as a software product |
Key Differences
Deployment model, not extraction philosophy
Both companies reject template-based extraction in favor of machine learning, so the technical approach is closer than most comparisons in this category. The real divergence is delivery: Mirage sends engineers to embed the agent inside your operation, while Shipamax positions itself as a product your team configures against your own email and systems.
Published results
Mirage publishes results per deployment rather than a headline accuracy percentage: 90%+ of standard RFQs answered automatically at OFRET Groupe, 70% less manual data entry on freight documents at Transwin. Shipamax's public materials describe its ML approach and training on millions of logistics documents without a single headline accuracy percentage, which makes a direct numeric comparison difficult to make responsibly.
Ongoing ownership
Mirage's forward-deployed model means engineers stay involved as document formats or systems change. Shipamax's software-product model puts more of that ongoing adaptation in the customer's hands, supported by Shipamax's own team.
Advantages and Limitations
Mirage
Advantages
- Forward-deployed engineers handle document-format and workflow mapping
- Published first-pass accuracy figure specific to freight documents
- Integrates into CargoWise, Descartes, Amber Road, and custom TMS/ERP
- 2-4 week deployment for most Logistics rollouts
Limitations
- Pricing is scoped per engagement, not published publicly
- Engineering-led rollout may take longer to start than a self-serve signup
Shipamax
Advantages
- No-template ML approach trained on millions of logistics documents
- Real-time email sync into TMS/ERP, including CargoWise
- Software-product model may onboard faster for teams wanting self-service
Limitations
- No publicly quantified accuracy figure to compare against
- Ongoing configuration and adaptation sit more with the customer
Real-World Use Cases
Freight forwarders wanting embedded engineering support
Operations that want a team mapping document formats and system integration directly, rather than a self-configured product, are a closer fit for Mirage's forward-deployed model.
Teams wanting a self-service ML product
Operations that prefer syncing an existing email inbox and TMS to a software product with less upfront engineering engagement are a closer fit for Shipamax's positioning.
Accounts payable invoice processing
Both companies process AP-related freight invoices; the deciding factor is typically whether the buyer wants an embedded engineering engagement or a configurable software product.
Mirage Products
Logistics
Mirage's AI agent for freight document intelligence, bills of lading, customs documents, and carrier paperwork, integrated directly into your TMS and ERP.
See the comparisonDocument Intelligence
Mirage's broader document understanding platform for operational teams handling invoices, contracts, reports, and industrial documentation.
See the comparisonHow to Choose
Mirage and Shipamax are both machine-learning-native, template-free document processing systems, closer to each other technically than most vendor comparisons in this space. The decision usually comes down to how much you want an outside engineering team involved in mapping your document formats and systems versus configuring a software product yourself.
Teams with complex, non-standard document flows across multiple carriers and customs authorities often benefit from the hands-on mapping a forward-deployed engagement provides. Teams with more standardized flows and an existing preference for self-service software may find a product-led rollout faster to start.
FAQ
Both are machine-learning-native, template-free document processing systems. The main difference is deployment model: Mirage sends forward-deployed engineers to integrate the agent into your systems, while Shipamax is a software product configured to sync with your email and TMS/ERP.
No. Shipamax's own materials describe a machine-learning approach with no rules or templates to maintain, similar in principle to Mirage's Logistics agent.
Yes. Both integrate with CargoWise. Mirage's Logistics agent also connects to Descartes, Amber Road, and other TMS/ERP/customs platforms via API and EDI/SFTP.
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Logistics
Logistics is Mirage's AI agent for freight document intelligence. It processes bills of lading, customs documents, and carrier paperwork, and integrates directly with your existing TMS and ERP, deployed by engineers who work inside your operation.
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