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Nearfleet

How Nearfleet Slashed PR Cycle Times by 75% and Reclaimed 30 Hours a Week Using Optibot

NearFleet’s engineering team replaced manual trans-Atlantic peer reviews with Optibot, resulting in faster shipping, calmer workflows, and 24/7 senior-level oversight.

Time Saved per Week

30 Hours

Reclaimed nearly a full work week previously lost to manual PR backlogs.

Reduction in Review Time

75%

Manual senior intervention dropped from 4 hours to just 1 hour per PR.

Security & Compliance Catch

99%

Successfully identified PII leaks across 15,000 lines of code that slipped through QA.

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"We’ve cut our review times from 4 hours down to just 1, saving the team at least 30 hours every week. It’s like having a second senior engineer available round the clock... If PR reviews are your bottleneck, Optibot is a no-brainer."

Simon Balkau

Senior DevOps Engineering Manager, Nearfleet

NearFleet is building a hubless, fully mobile logistics infrastructure. Their software-defined platform enables regional ground delivery at air-like speed, using AI to coordinate vehicle-to-vehicle relays and in-field mobile sortation.

Industry

Logistics & Supply Chain

Company size

11 - 50

Pain point

Timezone friction for a distributed team; senior reviewer bottlenecks; protecting HIPAA/PII data in a complex event-driven architecture.

Product used

Optibot (AI Code Review Senior Engineer Agent)

Location

Europe / United States (Distributed)

Quick metrics

Review Time ↓ 75%

Hours Saved: 30/week

Compliance: 100% PII Catch Rate

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The Problem

Timezone friction and senior bottlenecks in a distributed team

Nearfleet’s engineering team is geographically distributed spanning from Central Europe to both coasts of the United States. This created a "relay race" workflow where the baton was constantly being dropped due to sleep schedules. With only two senior engineers qualified to perform final reviews, they became involuntary global bottlenecks.

  • The 24-Hour Wait: Junior engineers in the US often waited an entire day for European seniors to wake up.
  • Senior Burnout: Reviewers spent up to 12 hours a day—their entire shift—clearing the global PR queue.
  • Repetitive Friction: Seniors spent excessive time pointing out obvious, "simple" mistakes that should have been caught before the review reached a different continent.

We are a geographically distributed team... juniors often had to wait for me to actually wake up because it was nighttime for me. That added hours and even a full day of delay.

Simon Balkau

Senior DevOps Engineering Manager, Nearfleet

Without an automated layer, the team couldn't scale their velocity. Every new feature was held hostage by a manual review queue that never slept, but wasn't always awake in the right timezone.

The Solution

An AI "Senior Engineer" for a 24/7 workflow

NearFleet integrated Optibot as the first line of defense. Rather than replacing humans, Optibot acted as an automated "second senior engineer" that provided immediate, high-context reviews regardless of which timezone the developer was in.

  • Closing the Timezone Gap: Optibot provides instant preliminary reviews at 2:00 AM, allowing US-based juniors to fix issues before European seniors even wake up.
  • Human-Readable Summaries: Optibot generates clean summaries of every PR, allowing seniors to understand the "intent" of a change instantly, without the need for a synchronous hand-off call.
  • Compliance at Scale: During a major 15,000-line refactor, Optibot identified PII leaks that had slipped past manual QA—preventing a major compliance breach across the distributed codebase.

I pretty much didn't do anything after just introducing the team to it. It was a self-runner. My team is really liking it... it takes the blame off.

Simon Balkau

Senior DevOps Engineering Manager, Nearfleet

The Results

75% Faster PR Cycles and 99% PII Detection

How NearFleet Reclaimed 30 Hours a Week by Enabling 24/7 Asynchronous Reviews for Their Distributed Team

  • 30 Hours Reclaimed Per Week: The team saves roughly 30 hours every week previously spent on manual review cycles and timezone hand-offs.
  • 75% Faster Reviews: Total manual time per PR was slashed from 4 hours to 1 hour.
  • Asynchronous Velocity: Juniors receive instant feedback, allowing features to move from "submitted" to "merged" without waiting for a senior's workday to begin.

1. Scalability for distributed teams - By removing the "low-level" friction, NearFleet transformed their culture from one of waiting to one of building. Seniors now focus strictly on high-level architecture rather than policing syntax across time zones.

2. A safer code base - Because Optibot is trained on compliance (HIPAA/PII), it acts as a permanent security auditor. It caught a major leak in 15,000 lines of code that would have reached staging otherwise.

3. Behavioral change - The "blame" factor disappeared. Juniors now use Optibot "maliciously"—submitting PRs specifically to see what the AI catches so they can learn and fix issues privately before a human ever sees the code.

Optibot caught a PII leak across 15,000 lines of code... it had slipped through QA, but Optibot made sure it was caught before it rolled out to staging. Those moments make it clear this is a second pair of eyes you can trust.

Simon Balkau

Senior DevOps Engineering Manager, Nearfleet

My team is really liking it. It takes the blame off. Juniors can learn from the mistakes Optibot catches before a senior even sees the code. It has become an integral part of how we interact as a team.

Simon Balkau

Senior DevOps Engineering Manager, Nearfleet

The Impact in Numbers

Before and after metrics for Nearfleet’s team using Optimal AI

Real numbers verified by the leaders using the tech

Metric

Before

After

Improvement

Review Time per PR

Before Insights

3-4 Hours

After Insights

~1 Hour

75% Reduction

Senior Weekly PR Load

Before Insights

~30-40 Hours

After Insights

~10 Hours

30 Hours Saved

Timezone Friction

Before Insights

Up to 24-hour delays

After Insights

Instant (24/7)

Eliminated Waiting

Security/PII Catch

Before Insights

Manual/QA dependent

After Insights

Automated Scanning

Caught 15k line leak

Reviewer Morale

Before Insights

Burnout; 12hr review days

After Insights

"Faster and Calmer"

Significant Shift

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