Layer 03 Logistics Intelligence

Context Fabric

The continuously updated picture of an operation that every decision is made against, drawn from four kinds of signal: Demand (what was ordered and promised), Network (what the fleet, carriers and connected systems can do right now), Reality (what is happening this minute: traffic, weather, delays, exceptions) and Learning (what past deliveries have shown about providers, addresses and demand). A route optimizer decides against a thin slice of it. Delivery decisioning reads all four, for every order, and reads them again when any of them move. In Nash it hydrates from the TMS, WMS, ERP and carrier systems already in place, and every delivery across the network enriches it.

Where this fits

Layer 03 of the Nash platform: planning and live operations. Intelligent planning configures the routing rules, dynamic dispatch executes them, live operations adjusts as conditions change, and the provider network supplies the capacity to fulfill against.

Related terms

Routing constraint: A rule a route must respect to be executable rather than merely short: vehicle capability and capacity, driver certification, dock and appointment timing, service time per stop, shift length, and access at the address. A route that breaks a hard constraint is infeasible: it can be drawn on a map and cannot be run. An optimizer scoring only time and distance returns routes that look good on paper and cannot be run, which is how a sedan gets assigned five mattresses. Nash treats constraints as first-class inputs to dispatch and re-checks them on every re-optimization, not once at plan time.
Delivery decisioning: Deciding, for each order, who carries it, how and when: your own fleet, a contracted carrier, a courier network or store staff, each scored against the promise, the cost and its live state. Route optimization answers how a vehicle should run its stops. Delivery decisioning answers which capacity should take the work at all, and revisits that choice when conditions change. In Nash it is the decision layer, and it does not stop at assignment: the decision is carried through execution, exceptions and proof of delivery.
Optimization strategy: The named, reusable configuration that decides how a route gets built: which objective to favor (fewest drivers, balanced load, lowest cost, tightest promise), and which constraints are hard rather than soft. Operations keep several and apply different ones per shift, zone, or vehicle type. Changing the strategy changes the shape of the day, which is why it is an object you version rather than a setting you nudge.
Dispatch strategy: The named configuration that decides who runs the order: owned fleet first, then contracted carriers, then gig capacity, with the fallbacks and the conditions for each. Where an optimization strategy decides how a route is built, a dispatch strategy decides which capacity runs it at all. Workflows can apply one, branch on it, and hand the result to an agent.
Least-cost routing: Selecting the cheapest capacity that can still hold the promise, rather than the cheapest capacity outright. Cost-only selection looks good per order and shows up later as failed drops, redeliveries, and support volume, so Nash scores cost against reliability and the committed window before it assigns.