It doesn't wait to be asked.
NaviQ is how people talk to the control tower — and how the control tower talks back. Ask anything in plain English and get an answer in seconds. More usefully: when NaviQ sees risk forming, it opens the conversation itself, and shows the chain of reasoning behind what it's telling you.
From asking questions to being told the answer.
The old loop: you ask, you get a report, you interpret it, you decide. By the time you finish, the intervention window has closed. NaviQ inverts it — it watches continuously, surfaces the decision that needs making, explains why, and tells you what to do about it.
- 1Log into the WMS, find the export, set the filters, download the CSV15 min
- 2Log into the TMS, pull shipment status, export again10 min
- 3Open Excel, match orders to shipments, fix the mismatched keys30 min
- 4Build the pivot, apply conditional formatting, identify the at-risk orders15 min
By the time you have the answer, the window to act on it has usually closed.
- →"Show me orders at risk of missing SLA today"
- ✓NaviQ queries unified data across WMS, TMS and carrier feeds at once
- ✓Returns a ranked list with breach probability, root cause and recommended action
You get four to eight hours to intervene — and you already know what to do.
Four ways NaviQ drives a decision.
Plain-language questions
Ask anything the way you'd ask a colleague. No SQL, no report builder, no training course.
Predictive intelligence
Surfaces bottlenecks, capacity constraints and cost anomalies while they are still forming.
Recommendations, not alerts
Every alert arrives with a specific recommended action and the financial impact of taking it.
Root-cause analysis
Traces a cost spike or an SLA slip to its actual causal chain, rather than reporting the symptom.
What people actually ask it.
Operations
- “What was yesterday's throughput at the Chicago DC?”
- “Show me orders at risk of missing SLA today”
Freight & carriers
- “Which carriers have the worst on-time performance this month?”
- “What's driving the freight cost increase at Site B?”
Labour
- “What's driving the labour cost increase in Zone C?”
- “How should I staff the night shift given tomorrow's volume?”
Inventory
- “Which SKUs are at risk of stockout in the next 14 days?”
- “Show me inventory accuracy by zone”
Financial
- “What's our cost per order by customer this week?”
- “Show me SLA penalty exposure for this month”
Forecasting
- “What inbound volume should I plan for next week?”
- “Are there bottlenecks forming I should know about?”
What's underneath the conversation.
Supply-chain language understanding
Tuned to operational vocabulary, KPI definitions and your own site and carrier names — so it understands 'the Chicago DC' without being told what that is.
Forecasting
Time-series models for demand and capacity, projecting weeks ahead rather than reporting on last week.
Anomaly detection
Statistical and machine-learning methods running continuously over live operational streams, looking for the shape of a problem before it lands.
Explainable by construction
Every recommendation returns the causal chain it was derived from, because operations teams do not act on reasoning they cannot inspect.
See NaviQ answer a question about your operation.
Book a demo and we'll ask it something real about an operation shaped like yours — then show you the chain of reasoning behind the answer.