Understanding Sub-Orbital Point-to-Point Freight

Sub-orbital space flight differs fundamentally from orbital missions. Instead of achieving the velocity needed to enter Earth’s orbit, a sub-orbital spacecraft, often a rocket-powered spaceplane, follows a ballistic trajectory that crosses the recognized boundary of space—the Kármán line at 100 kilometers altitude—before being pulled back to Earth by gravity. For freight, this means a vehicle could launch from a spaceport, ascend into the upper atmosphere, and then glide to a landing on the other side of the planet. Early proposals, such as those discussed between U.S. and Taiwanese officials in mid-2025, suggest a sub-orbital cargo route between Houston and Taipei could cut delivery times to just two and a half hours .

The complexity of managing these flights, however, is immense. Unlike conventional air freight, sub-orbital vehicles must contend with rapidly changing atmospheric conditions across multiple altitudes, complex re-entry dynamics, and precise landing requirements. This is where AI becomes indispensable. AI-powered freight planning systems are being designed to calculate every variable, from optimal launch windows to fuel-efficient ascent profiles and safe re-entry corridors, all in real-time .

The Critical Role of AI in Space Logistics

Traditional logistics software is ill-equipped to handle the four-dimensional problem that is sub-orbital flight planning. AI and machine learning algorithms, however, excel in this environment. They can process vast datasets—including space weather, atmospheric density, global air traffic, and vehicle telemetry—to generate and adapt flight plans instantaneously. According to experts in the field, the success of sub-orbital cargo hinges not just on the reusable launch vehicles themselves, but on the sophisticated AI systems that will route, monitor, and coordinate them .

Companies like NextBillion.ai and Locus, currently leaders in terrestrial AI route optimization, represent the technological foundation upon which space-based logistics could be built. Their existing APIs and algorithms, which optimize for thousands of delivery constraints on the ground, offer a glimpse into the more complex systems needed for space . The evolution from optimizing truck fleets to managing spacecraft is a natural, albeit ambitious, progression for AI in the logistics sector .

Key Players in AI-Powered Freight and Space Planning

While dedicated “sub-orbital freight AI” platforms are not yet commercially available, a robust ecosystem of companies provides the core technologies—route optimization, real-time tracking, predictive analytics, and autonomous operations—that will form the backbone of this new logistics category. The following companies represent the current market leaders whose AI capabilities are directly applicable to advanced freight planning.

1. NextBillion.ai

NextBillion.ai provides a suite of AI-powered mapping and routing APIs designed for enterprises with complex logistics needs. Its strength lies in its customizability, allowing logistics firms to build routing engines that account for highly specific constraints, a feature essential for the dynamic nature of sub-orbital flight planning.

Key Features: Customizable routing APIs that account for vehicle dimensions, weight, and hazardous materials; real-time traffic and weather integration; isochrone maps for service area analysis; and matrix APIs for large-scale distance and time calculations. It supports multi-leg and multi-modal journeys, a crucial capability for integrating spaceplane landings with ground transport .
Current Pricing: Pricing is custom and quote-based, typically scaled to API usage volume and specific feature requirements (Retrieved: February 2026).
Pros: Highly flexible and developer-friendly; enterprise-grade scalability; strong data privacy controls; excellent for businesses needing to build proprietary systems.
Cons: Requires significant technical expertise to implement; can be over-complicated for simple, out-of-the-box solutions; pricing can be high for smaller firms.
Best For: Large logistics providers and aerospace companies developing custom in-house planning software.
Where to Buy: Available directly through the NextBillion.ai website.

2. Locus

Locus offers an AI-driven dispatch and route optimization platform widely used in last-mile and mid-mile logistics. Its core technology uses deep learning to automate complex decision-making, making it a prime candidate for the kind of automated, real-time decision support needed in spaceport operations and ground integration .

Key Features: Intelligent order allocation and dispatching; automated route planning considering time windows and vehicle capacity; real-time tracking and proactive alerts; advanced analytics for operational insights. It integrates seamlessly with existing TMS, OMS, and WMS solutions .
Current Pricing: Enterprise-level pricing is available upon request, typically based on shipment volume and modules used (Retrieved: February 2026).
Pros: Proven track record in optimizing complex logistics; excellent at reducing costs and improving on-time performance; strong post-implementation support.
Cons: More suited to operational logistics rather than vehicle flight mechanics; implementation can be a lengthy process.
Best For: Logistics operators managing the “last-mile” from a spaceport to final destination, and coordinating ground fleets with incoming cargo.
Where to Buy: Available through the official Locus website.

3. project44 Movement

project44 is a leading supply chain visibility platform that uses AI to provide real-time tracking and predictive analytics across all modes of transport. For sub-orbital freight, a platform like project44 would be critical for providing end-to-end visibility, alerting stakeholders to delays or issues the moment they are predicted by AI .

Key Features: Real-time visibility for ocean, air, road, and rail shipments; predictive ETAs using machine learning; automated exception management; supply chain analytics and reporting; extensive carrier connectivity network.
Current Pricing: Basic plans start at approximately $500 per user per month, with enterprise pricing varying based on scale and required integrations (Retrieved: February 2026) .
Pros: Unmatched global carrier connectivity; highly accurate predictive analytics; centralized dashboard for end-to-end supply chain visibility.
Cons: Primarily a visibility and tracking tool, not a route planning engine; can be expensive for smaller logistics operations.
Best For: Shipper and freight forwarders needing to track high-value sub-orbital cargo with complete transparency from launch to delivery.
Where to Buy: Available via the project44 website.

4. Shipwell

Shipwell provides a comprehensive transportation management system (TMS) that integrates order management, execution, and visibility into a single platform. Its AI capabilities focus on optimizing carrier selection and streamlining workflows, functions that will be vital for managing the multi-modal journey of a space-bound package .

Key Features: Unified platform for order, inventory, and shipment management; AI-powered carrier rate comparison and selection; real-time shipment tracking; automated document generation and workflows; robust analytics for cost optimization.
Current Pricing: Basic plans start around $1,000 per month, with higher tiers for advanced features and support (Retrieved: February 2026) .
Pros: All-in-one TMS solution; simplifies complex logistics processes; excellent for automating freight booking and execution.
Cons: May not offer the deep, specialized AI for aerospace-specific flight dynamics; more focused on commercial freight brokerage.
Best For: Logistics companies looking to integrate sub-orbital freight into a broader, multi-modal supply chain management workflow.
Where to Buy: Available through the Shipwell website.

5. GoComet

GoComet is an AI-powered logistics platform specializing in enhancing supply chain visibility and automating freight procurement. Its strength lies in simplifying complex data from multiple carriers, a feature that will be essential when coordinating between space launch operators, ground transport, and last-mile delivery services .

Key Features: Multi-carrier real-time shipment tracking; automated freight procurement and rate management; actionable analytics dashboards for logistics performance; proactive delay alerts and exception management.
Current Pricing: Custom pricing based on shipment volume and selected modules (Retrieved: February 2026).
Pros: User-friendly interface; significantly reduces manual tracking efforts; strong focus on cost savings through procurement optimization.
Cons: Primarily focused on surface and air freight; its direct application to space launch coordination is still evolving.
Best For: Freight forwarders and shippers who need to track sub-orbital shipments and seamlessly hand them off to ground transport networks.
Where to Buy: Available on the GoComet website.

6. TMSfirst

TMSfirst delivers an AI-powered transportation management solution designed to streamline logistics, route planning, and delivery operations. Its AI focuses on the practical aspects of fleet management and delivery execution, which will be a critical component of the terrestrial half of any space logistics network .

Key Features: AI-driven route optimization for delivery fleets; real-time vehicle tracking and status updates; automated dispatch and scheduling; performance analytics for fleet managers.
Current Pricing: High-end enterprise pricing is available, with basic plans quoted at approximately $36,000 per month for comprehensive services (Retrieved: February 2026) .
Pros: Powerful AI focused on tangible operational efficiency; robust real-time tracking capabilities; suitable for managing large, complex fleets.
Cons: High cost makes it inaccessible for small businesses; primarily designed for trucking and local delivery fleets.
Best For: Large-scale ground logistics operators partnering with spaceports for high-volume cargo distribution.
Where to Buy: Available through the TMSfirst website.

7. Logiwa WMS

Logiwa is a cloud-based warehouse management system (WMS) that uses AI to optimize inventory and fulfill high-volume orders. In a sub-orbital freight scenario, where speed is paramount, a WMS like Logiwa is essential for ensuring that cargo is picked, packed, and ready for launch the moment a spaceplane lands .

Key Features: AI-driven inventory optimization and wave planning; support for high-volume, direct-to-consumer fulfillment; real-time inventory visibility across multiple locations; seamless integration with sales channels and carriers.
Current Pricing: Custom pricing based on order volume and required functionality (Retrieved: February 2026).
Pros: Excellent for high-speed fulfillment operations; cloud-native and highly scalable; optimizes warehouse labor and space utilization.
Cons: Focuses on warehouse operations, not transportation; best suited for businesses with significant e-commerce or D2C components.
Best For: Space-adjacent logistics hubs and warehouses needing to prepare, receive, and transfer cargo with maximum speed and accuracy.
Where to Buy: Available via the Logiwa website.

8. Shipsy

Shipsy is an intelligent logistics platform that automates and optimizes end-to-end logistics operations, from order management to last-mile delivery. Its AI-driven features for route optimization, real-time tracking, and predictive analytics make it a versatile tool for managing the complex, multi-leg journeys associated with space freight .

Key Features: AI-driven route planning and optimization; real-time shipment tracking and customer notifications; automated courier allocation based on cost and service levels; comprehensive analytics dashboard for logistics performance.
Current Pricing: Available upon request, typically based on monthly transaction volumes (Retrieved: February 2026).
Pros: End-to-end platform covering order to delivery; strong focus on customer experience with proactive notifications; proven scalability for high-volume operations.
Cons: Primarily focused on surface transportation; may require customization for aerospace-specific use cases.
Best For: Logistics service providers needing a unified platform to manage the entire post-landing journey of a sub-orbital shipment.
Where to Buy: Available through the Shipsy website.

9. 7bridges

London-based 7bridges is an AI architect, building a platform that fully automates supply chain operations. Its AI is designed to make autonomous decisions—selecting carriers, optimizing routes, and managing inventory in real-time. For sub-orbital freight, a system like this could autonomously manage the entire supply chain, triggering a launch based on inventory levels and predicted demand .

Key Features: Autonomous logistics orchestration; real-time supply chain visibility across all modes; predictive analytics for demand and disruption; automated freight procurement and carrier management.
Current Pricing: Enterprise-level, custom pricing (Retrieved: February 2026).
Pros: Represents the cutting edge of autonomous logistics; reduces human intervention in routine decisions; highly adaptive to changing conditions.
Cons: A very advanced solution that may be ahead of the current market for many businesses; requires significant trust in AI-driven decision-making.
Best For: Forward-thinking enterprises aiming to build a fully autonomous, AI-driven supply chain that can integrate with future sub-orbital freight networks.
Where to Buy: Available through the 7bridges website.

10. Vorto

Vorto (formerly Stord) is another AI architect that uses autonomous AI to streamline supply chain operations. Its platform focuses on optimizing freight movement and warehouse utilization by automatically matching shipments with capacity. Vorto’s technology represents the kind of dynamic, real-time resource allocation that will be crucial for booking space on sub-orbital flights .

Key Features: Autonomous freight procurement and execution; AI-driven supply chain analytics; network optimization for warehousing and transportation; real-time shipment visibility.
Current Pricing: Custom pricing based on business scale and needs (Retrieved: February 2026).
Pros: Strong focus on automation and reducing manual freight booking; dynamic optimization of logistics networks; data-driven insights for cost reduction.
Cons: A highly specialized platform for freight and fulfillment; its integration with space launch scheduling is theoretical at this stage.
Best For: Large shippers looking to automate the procurement of all freight services, including future sub-orbital options, as they become available.
Where to Buy: Available through the Vorto website.

Pricing Comparison: AI Freight Software Market (as of February 2026)

NextBillion.ai: Custom Quote (Enterprise)
Locus: Custom Quote (Enterprise)
project44 Movement: ~$500/user/month (Basic Plan)
Shipwell: ~$1,000/month (Basic Plan)
GoComet: Custom Quote (Volume-based)
TMSfirst: ~$36,000/month (Enterprise Plan)
Logiwa WMS: Custom Quote (Volume-based)
Shipsy: Custom Quote (Transaction-based)
7bridges: Custom Quote (Enterprise)
Vorto: Custom Quote (Enterprise)

How to Choose an AI Platform for Future-Proof Freight Planning

Selecting the right AI tool for an emerging field like sub-orbital logistics requires looking beyond current features to future potential. Here are five key criteria to guide your decision:

Customization and Flexibility: Can the platform’s algorithms be customized to handle the unique constraints of spaceflight, such as re-entry angles, fuel consumption in near-vacuum, and spaceport availability? Platforms like NextBillion.ai, with its highly customizable APIs, are built for this level of specificity .
Real-Time Data Integration: Sub-orbital flight is highly sensitive to real-time conditions. Your chosen platform must be able to ingest and act upon live data streams, including space weather, upper-atmosphere wind shear, and global air traffic. project44’s strength in real-time visibility is a prime example of this capability .
Multi-Modal Orchestration: The journey doesn’t end at the spaceport. The AI must seamlessly orchestrate the handoff from spaceplane to ground transport. An end-to-end platform like Shipsy or an autonomous orchestrator like 7bridges is designed to manage these complex, multi-modal transitions .
Predictive Analytics and Autonomy: Look for AI that doesn’t just report on the present but predicts the future. Can it anticipate a delay at launch and automatically rebook ground transport? Can it predict demand for a sub-orbital route? Companies like Vorto and 7bridges are building exactly this kind of predictive, autonomous decision-making engine .
Scalability and Integration: The platform must grow with the industry. It should integrate with existing TMS, WMS, and ERP systems while also being able to connect to new, specialized aerospace APIs. Solutions like Locus and Logiwa are proven to scale and integrate within complex logistics ecosystems .

Buying Guide: 8 Factors for Future-Proofing Your Investment

Investing in AI for a nascent sector like sub-orbital freight requires a forward-looking strategy. Consider these eight factors to ensure your investment remains viable as the industry matures:

1. Aerospace-Specific Algorithm Development: Assess if the vendor has a roadmap for developing algorithms that can handle the physics and regulations of space transport, not just road networks.
2. Partnership Ecosystem: Does the AI company have partnerships with aerospace firms, spaceport authorities, or satellite data providers? A strong ecosystem indicates future readiness.
3. Data Security and Sovereignty: Space logistics will involve highly sensitive data. Ensure the platform offers robust data encryption and complies with international data sovereignty laws.
4. API-First Architecture: An API-first design ensures the platform can connect to the specialized software used by launch providers and space traffic management systems as they come online.
5. Support for Digital Twins: The ability to create a digital twin—a virtual replica of the entire logistics network—will be crucial for simulating and testing sub-orbital routes before they go live. Look for platforms that support this.
6. Sustainability Metrics: As regulations on emissions tighten, the AI should be able to calculate and optimize for the full carbon footprint of a sub-orbital journey, from launch to last-mile delivery.
7. Talent and Expertise: Does the vendor employ data scientists and engineers who understand both AI and the complexities of aerospace? The team behind the software is as important as the software itself.
8. Financial Stability of the Vendor: Sub-orbital freight is a long-term play. Choose a vendor with strong financial backing and a long-term vision to ensure they will be a stable partner for years to come.

Current Market Prices and Deals

The market for AI-powered freight software is currently geared towards terrestrial logistics, with pricing models that are often customized for enterprise clients. However, the trend is towards modular pricing, where companies pay for specific API calls, shipment volumes, or user seats. For instance, project44 offers a tiered model starting around $500 per user, while Shipwell’s SaaS model begins at $1,000 monthly . For those seeking high-end, comprehensive TMS solutions like TMSfirst, the investment is significantly higher, reflecting the depth of the platform .

Notable promotions in this space are rare due to the enterprise focus, but many vendors, such as project44 and Cogoport OS, offer free trials or demos to showcase their AI capabilities . For companies exploring the cutting edge, engaging with AI architects like 7bridges or Vorto usually begins with a consultation to build a bespoke pricing model .

Pros and Cons Summary

NextBillion.ai: Pro: Ultimate flexibility; Con: Requires developer expertise.
Locus: Pro: Proven optimization; Con: Focused on ground operations.
project44: Pro: Best-in-class visibility; Con: Cost can be high.
Shipwell: Pro: Unified TMS platform; Con: Standard freight focus.
GoComet: Pro: User-friendly tracking; Con: Space applications unproven.
TMSfirst: Pro: Powerful fleet AI; Con: Enterprise-level price point.
Logiwa: Pro: High-speed fulfillment; Con: Warehouse-centric.
Shipsy: Pro: End-to-end management; Con: Surface transport focus.
7bridges: Pro: Full autonomy; Con: Ahead of current market.
Vorto: Pro: Autonomous procurement; Con: Integrations theoretical.

Pro Tips for Navigating AI in Space Logistics

As you explore this new frontier, keep these expert insights in mind. First, focus on interoperability; the best AI will be the one that can talk to everything else . Second, prioritize data quality. AI is only as good as the data it’s trained on, so invest in clean, reliable data from the start. Third, don’t underestimate the terrestrial leg; the space portion might take hours, but the ground portion can still take days if not optimized . Fourth, build for scalability. Choose platforms that can handle a surge from one shipment to one thousand without a hitch . Fifth, start planning for space traffic management now; as more players enter the field, AI will be essential for deconflicting launch and landing slots . Sixth, consider the insurance implications. AI-driven predictability could drastically lower insurance premiums for high-value cargo. Finally, stay engaged with regulatory bodies like the FAA and international space agencies to ensure your logistics plans remain compliant as the rules evolve .

Frequently Asked Questions

What is sub-orbital point-to-point freight?

It is the use of sub-orbital spacecraft to transport cargo between two points on Earth very quickly, often crossing continents in under two hours by briefly traveling into space .

How does AI improve sub-orbital freight planning?

AI algorithms can process the vast and complex datasets required for sub-orbital flight—such as real-time space weather and atmospheric conditions—to create safe, efficient, and adaptable flight paths that human planners couldn’t manage alone .

When will sub-orbital cargo services become a reality?

While early discussions and feasibility studies are underway, such as the talks between the U.S. and Taiwan in 2025, commercial sub-orbital cargo is likely still several years away, pending technological maturation and regulatory approvals .

Can current AI logistics software handle space freight?

Existing AI platforms excel at terrestrial route optimization and visibility. These core technologies provide a strong foundation, but they will need significant enhancement to handle the specific dynamics of spaceflight .

What types of cargo are best suited for sub-orbital transport?

Initially, it will likely be ultra-high-value, time-sensitive goods such as critical medical supplies, emergency repair parts, essential electronics, and important documents where the cost of speed is justified.

How will sub-orbital freight integrate with ground logistics?

This integration will be managed by AI platforms that treat the entire journey as a single, multi-modal event. The same system that tracks the spaceplane will automatically dispatch ground vehicles to meet it upon landing, ensuring a seamless handoff .

What are the main challenges facing AI-powered space freight?

The primary challenges are regulatory approval for routine sub-orbital flights, the development of robust and fail-safe AI for autonomous flight control, and the high initial infrastructure costs for spaceports and vehicle fleets .

Which companies are leading in this field?

While aerospace primes like SpaceX and Blue Origin are developing vehicles, the AI software layer is being pioneered by advanced logistics firms like 7bridges and Vorto, as well as established mapping and routing giants like NextBillion.ai .

Conclusion

The dream of delivering freight across the globe in under an hour is rapidly moving from science fiction to an engineering reality, with AI serving as the critical brain behind the operation. As government entities and private industry begin to lay the groundwork for sub-orbital spaceports and craft, the logistics software sector is evolving in parallel, creating the intelligent systems needed to plan, execute, and monitor these complex journeys. The AI tools profiled here, from custom mapping APIs to autonomous supply chain architects, represent the foundational technologies that will soon power the fastest supply chain on—and above—Earth. For logistics professionals and investors, the message is clear: the future of freight is being planned at the edge of space, and artificial intelligence is the pilot.