Who is the target customer?

Mid-to-large B2B enterprises with frequent less-than-truckload (LTL) or less-than-container-load (LCL) shipping needs, and freight carriers (trucking, rail, long-haul couriers) seeking to monetize otherwise empty or underutilized capacity.

The core problem of inefficient LTL/LCL and empty miles is enormous and persistent. SplinterPath attacks this with a unique deep-tech approach, offering significant cost savings for shippers, new revenue streams for carriers, and substantial environmental benefits. Its real-time, ultra-granular optimization capabilities represent a leap beyond traditional logistics aggregation, creating a compelling value proposition across the entire supply chain.

What is the biggest risk?

The primary risk lies in achieving sufficient network density – a classic chicken-and-egg problem requiring simultaneous onboarding of a critical mass of both shippers and diverse carriers. This is compounded by the immense R&D challenge of developing the sophisticated AI/ML for real-time, multi-modal, fractional capacity matching and the integration complexity with varied legacy carrier systems, ensuring security and liability for co-mingled cargo.

SplinterPath

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SplinterPath

Massive inefficiencies and environmental waste in logistics stemming from underutilized cargo space (empty backhauls, partial truckloads, less-than-container-load shipments) and the inability to dynamically aggregate these 'fractional' capacities across diverse, existing carrier networks in real-time.

3Wackiness

24-36 months for a regional pilot focused on specific carrier types, requiring extensive R&D in AI/ML routing algorithms, data integration protocols, and potential prototyping of specialized sensor-equipped modular cargo units.Transactional fee charged as a percentage of the shipment cost for each 'SplinterPath' facilitated, akin to a marketplace commission. Premium services for expedited delivery or specific cargo handling requirements could also introduce tiered pricing.

The Solution

SplinterPath is a deep tech logistics platform that leverages advanced AI/ML, predictive analytics, and potentially specialized modular cargo units to dynamically identify, match, and optimize 'micro-routes' for fractional shipments. Our system processes real-time data from a network of partnered carriers regarding their scheduled routes and available interstitial space, then intelligently consolidates multiple small, disparate shipments into shared legs of a journey, maximizing cargo utilization and minimizing transit costs and environmental footprint.

Confidential Investment MemoIsraeli Deep Tech

"The core algorithmic complexity required to dynamically route and co-mingle disparate fractional loads across a heterogeneous carrier network, maintaining security and integrity, is immense. If their predictive AI and sensor fusion platform can achieve the precision and resilience they claim, this isn't just logistics optimization; it's a new paradigm in physical supply chain orchestration, offering a significant and defensible technical moat. This isn't trivial software; it's an engineering challenge on a military-grade scale."

— Partner at DeltaPoint Ventures

* This is a work of fiction. Any resemblance to actual persons, living or dead, or actual VCs is purely coincidental.

The Solution

Target Customer

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Biggest Risk

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