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What Nash Agent is

Nash Agent is an AI operations copilot for deliveries. You can ask it about what’s happening with a job (delivery), have it investigate across your orders and jobs, and have it take action on your behalf — every action goes through a confirmation step before it runs. It can also analyze your operations to surface trends and answer higher-level questions. Nash Agent wears two hats. It’s an interactive assistant — you ask, it answers and acts. And it’s a workflow-driven operator: the same intelligence packaged as custom agents that run on a schedule or when something happens, without anyone typing a prompt. Nash Agent is org-scoped and permission-aware: it only sees and acts on data within your organization, and only within the permissions of the person using it.

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What you can do

Reach for Nash Agent when you’d otherwise be hunting through screens, exporting spreadsheets, or repeating the same checks every morning. A few concrete examples:
  • Check a delivery. “What’s the status and ETA of order ABC-123?” or “Pull up the tracking for this customer’s last delivery.”
  • Understand what went wrong. “Why did this delivery go late?” — and get a timeline of what happened.
  • Take an action. “Cancel this delivery,” “request a refund,” or “reassign this to another provider.” Sensitive actions pause for your approval first.
  • Answer an analytics question. “What was our on-time rate last week?” or “Compare provider completion rates this month” — answered from your own delivery data, with charts or a downloadable table.
  • Put work on autopilot. Stand up a custom agent that runs a playbook on a schedule or when something happens, or an improvement that pursues a goal over days.

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Where it lives

Nash Agent lives in the Nash Portal, and you can also work with it in Slack and the Nash mobile app — so you can reach it wherever your team already operates. It can additionally reach out to customers and drivers by text or voice on your behalf, always with your confirmation. See Channels for the details.

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How it works

Every run — whether you typed a question or a schedule fired — follows the same loop: observe, reason, improve.
  1. Observe. The agent gathers context: your request, the live state of your operation, historical data, and anything your org has taught it through knowledge or memory.
  2. Reason. It turns that context into conclusions — what happened, why it happened, what the options are — and recommendations with their assumptions stated.
  3. Improve. It closes the loop: answers your question, produces a report, proposes an action for your approval, or takes the action — so the next delivery benefits from what this one taught it.
A key part of the design is the safety model: read-only work (looking things up, running reports) happens automatically, while anything that changes your operation — cancelling a delivery, issuing a refund, reassigning a provider — pauses and shows you a confirmation first. Nothing destructive runs until you approve it. When a request is complex, Nash can break it into a visible plan, work through follow-up passes until it’s done, and produce downloadable files (CSV, XLSX, PDF, or charts) from the results.
What Nash can do for a given person depends on their role and permissions in your organization, and on your org’s settings. If something isn’t available, it’s usually a permissions or settings choice — not a missing capability.

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Why we built it

Running deliveries at scale means living in dashboards: clicking between screens to find one order, exporting data to answer a simple question, and repeating the same manual checks every day. The information is all there — it’s just slow to get to, and slower to turn into a decision. Nash Agent is our answer: one conversational entry point for operational intelligence and action. Ask the way you’d ask a sharp teammate, and get back not just what is happening but why it matters and what to do about it. The strategy is deliberately open-ended — ask for anything. When Nash can do the work, it does; when it can’t yet, that miss tells us exactly what to build next.

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Explore the docs

Custom agents

Define reusable, scoped agents for the jobs your team repeats.

Scheduling & execution

Run agents on a schedule or in response to events, hands-free.

Knowledge

Ground Nash with your SOPs, policies, and reference links.

Improvements

Set a multi-day goal and review recommendations as they come in.

Memory & learning

Let Nash carry context forward across conversations — opt-in and org-controlled.

Usage & cost

See what the agent is doing and what it costs, and cap spend.

Fleet overview

How a fleet reports delivery state back to Nash.

Nash API

Build delivery operations directly against the Nash API.