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Logistics · Internal Tooling

Northbeam Ops: Real-Time Logistics Fleet Dispatch & SLA Monitoring System

Dispatchers were refreshing a 50-column spreadsheet while 350 trucks pinged GPS. We built a live dispatch board that keeps up.

ClientNorthbeam Logistics
IndustryFreight & Regional Logistics
Timeline14 Weeks
What changed32 ms P99 API Query Latency
Northbeam Ops dispatch and fleet logistics dashboard
WHAT CHANGED

Numbers from after launch

Recorded in production, with real users, after the new system was live.

32 ms
P99 API Query Latency
Restructured read models and partial indexing reduced p99 latency from 1,840ms under 40,000 RPM peak load.
42%
Faster Dispatch Assignments
High-density keyboard-navigable operational UI cut dispatcher task completion times almost in half.
99.98%
SLA Adherence Tracking
Automated geofence triggers provided instant alerts for delivery trucks at risk of missing SLA deadlines.
THE PROBLEM, THEN THE BUILD

What was broken, and what we built

First the workflow that was failing. Then the product and the technical choices that made the change hold.

THE PROBLEM

What was broken: a spreadsheet view that died at rush hour

Northbeam's previous dispatch dashboard suffered severe performance degradation during morning rush hours when 350+ drivers were checking in and pinging GPS telemetry every 5 seconds. Operators were burdened with sluggish 50-column spreadsheet views that required constant manual browser refreshing.

Dispatchers had no automated warnings for trucks stuck in traffic or risking contractual SLA delivery deadlines, forcing reactive customer apology calls.

WHAT WE BUILT

What we built: live truck state off the database hot path

We re-architected the telemetry ingestion path using a Redis in-memory cache layer that aggregates GPS coordinates before batch-persisting to time-series partitioned PostgreSQL tables. This decoupled live UI updates from persistent database writes.

On the frontend, we designed a high-density, accessible React table interface featuring keyboard shortcuts, user-saved filter presets, pinned columns, and real-time WebSocket vehicle state indicators.

THE TECHNICAL CHOICES
  • High-density data tables designed for 8-hour daily dispatcher productivity
  • Redis memory buffering for vehicle GPS telemetry reducing database write load by 80%
  • Automated geofencing engine computing route ETAs and SLA breach probability
  • OpenTelemetry distributed tracing and Grafana dashboard alerts
WHAT IT RUNS ON

Stack in production

Libraries, databases and infrastructure on this product today.

ReactTypeScriptPythonFastAPIPostgreSQLRedisOpenTelemetry
HOW WE DID THIS

Services used on this build

All services
PRACTICE

Full-Stack Product Engineering & Ongoing Software Maintenance

You know what the product should do. We turn that into a frontend, a backend, a data model and a way to ship updates, then keep it healthy after launch with maintenance, SLAs and code ownership.

PRACTICE

Cloud & DevOps Engineering, Scalability & SRE

We run infrastructure like an engineering product: infrastructure as code, GitOps delivery on Kubernetes, automated CI/CD and SRE practice. When the product is already slow or old, we find the bottleneck and migrate without downtime.

PRACTICE

B2B UI/UX Product Design & Enterprise Design Systems

B2B software is not a landing page. We design the screens operators use for eight hours: dense tables, keyboard paths, and a Figma system that matches the code.

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