Set a goal, and Nash continuously reasons, hypothesizes, and tests how to get your logistics closer to achieving it. Every successful test gets baked in as a new baseline.
Traditional logistics software plans, dispatches, and assumes the day holds. But that's never how the world works. Nash treats the plan as a living thing — sensing, adapting, re-drawing itself against the goal you set. A route starts to slip, a provider goes dark, a zone softens against its promise; Nash reasons through the tradeoff, acts inside your rules, and every outcome teaches the next decision.
TRADITIONAL · 06:00 SNAPSHOT
Drawn once · frozen all day
06:00
One plan, generated at dispatch. Every slip becomes a human chase.
OTIF trajectory · no re-plan
91.0%
↘ slipping against promise · no corrective action
target 97.0%
NASH · LIVE RE-PLAN
Re-planning against the goal
06:00
Sense, re-reason, re-draw — every minute. The plan bends around reality instead of breaking against it.
OTIF · live
93.2%
↗ toward 97.0%
06
08
10
12
14
16
18
RE-DISPATCHDSP C → DSP B · south-loop·09:14
PROTECTEDroute 412 · rerouted around I-94 closure·09:22
BATCHED6 orders clustered · Wicker Park·09:31
Section 02
Continuous improvement
Constantly test, promote the best.
Nash uses its information-complete context to constantly hypothesize new experiments to improve your number, runs the experiments inside your rules, and surfaces only the proposals that need your call. Approve it, deny it, tune the rule that raised it, and move on. Everything else keeps running.
Approved automatically · no exceptions in last 14 days.
Doneby rule #47 · 6:14 AM
Specialized skills
Encoded best practices.
Skills are the operational definitions that only your org would write — the hard-won lessons. Encapsulated in a way that can be applied across everything Nash sees.
Skills24shared by every agent
01 Investigate a cancellation
02 Is this PoD valid?
03 When to protect a route
04 How to rebook after a miss
05 What counts as a stuck order
06 When to escalate to a human
Custom agents
Agents that do the work you already do.
The plays your best operators run in their heads — when to act, what playbook to use, how to get the plan back on track. The best person you have at a given scenario, replicated at scale.
Composed dispatcher note with rationale · held for ack (15s timeout)
Acknowledged · applied reassignment · logged to audit trail
Projected impact · +0.4% OTIF today · ran in 1.8s · $0 test cost
Command and control
One operator commands a team of AI Agents.
Your operators stop chasing tickets. They command a team of agents instead — approving the right calls, denying the wrong ones, and tuning the rules that raised each one. The seat moves from dispatcher to manager.
Action queue · live7 open · 23 auto-cleared today
Rebook 3 SLA-critical drops on lane CHI-NE
Carrier A reliability dropped below 0.82 this shift. Carrier B available.
Exceptionraised 09:14 · conf 0.91
Shift 18% of loop volume to batched routes
Batching saves 42 driver-minutes; no SLA impact in sim.
Auto-improveraised 09:22 · conf 0.87
Extend PoD grace window on Westside drops
Signal weakness on 4 of last 12. Suggest +10 min retry.
PoD sentinelraised 09:31 · conf 0.78
On-time rate · live
95.5%
+4.5 pt vs. baseline · 22 actions today
approved · 18
denied · 4
auto-cleared · 23
tuned · 2
Any interface
Wherever the work happens.
Slack, phone, MCP, A2A, web, API. Same goal, same memory, same rules wherever it answers. Same intelligence, summoned through whichever surface fits the moment.
The AgenticIntelligence Layersame goal · same memory · same rules
Slack
Phone
MCP
A2A
Web portal
API
Auto-research
Give it a KPI. Watch the number move.
Point the agent for automatic improvement at on-time rate, cost per drop, first-attempt success, or a goal of your own. It hypothesizes and designs experiments to test, measure, and validate — always with human approval before running or promoting to production.
Weekly log · 26 weeks
On-time rate · compounded
91.0%
week 01 · baseline · target 97.0%
trajectory · weekly
target 97.0%
0
Promoted
0
Rolled back
1
Weeks
Observe. Reason. Act. Repeat.
A new customer on day one inherits every decision the network ever made.
Every job a Nash Agent touches becomes a lesson the next one begins with. Intelligence. Compounded.
Target reached
97.2%
compounding holds · next customer inherits from day one
Try it now
Set a goal. Watch Nash earn it.
Hit a target, approve an action, see the number move. Live demo, in your browser.