Real Businesses, Real Results

These aren't polished marketing stories. They're actual implementations we've worked on with companies trying to solve specific problems.

We've spent the last few years helping businesses figure out where automation actually makes sense—and where it doesn't. Some of these projects took months. Others happened in weeks. But they all started with someone asking, "Can this actually work for us?"

How Different Teams Approached Automation

Each situation was different. Here's what happened when these businesses decided to try something new.

Manufacturing facility implementing automated quality control systems
Belding Manufacturing Industrial Equipment

Reducing Quality Control Bottlenecks

Their inspection process was eating up hours every day. Not because people were slow—the manual checks just took that long. We built an AI vision system that could spot defects faster than their team could mark them with tape.

  • Inspection time dropped from 45 minutes to about 8 minutes per unit
  • Started catching issues earlier in production
  • Team could focus on fixing problems instead of just finding them
  • Fewer customer complaints about missed defects
Office workspace with automated document processing workflow
Hartwick Logistics Supply Chain

Making Sense of Supplier Documentation

They were drowning in invoices, packing slips, and customs forms—all in different formats. Someone had to manually enter everything into their system. It was tedious work and mistakes happened pretty often.

  • Document processing moved from manual entry to automated extraction
  • Reduced data entry errors significantly
  • Their admin team could handle other responsibilities
  • Faster invoice reconciliation at month-end

What Actually Happens During Implementation

This is how a typical project unfolds. Not every implementation follows this exact path, but most hit similar milestones.

1

Discovery and Assessment

We spend time watching how things actually work in your business. Not how you think they work or how the manual says they should work—how they really happen day-to-day. This usually reveals a few surprises.

2-3 weeks
2

Proof of Concept

Before building anything major, we test the idea on a small scale. Can the AI actually recognize what it needs to? Does the automation handle edge cases? This is where we find out if the concept holds up under real conditions.

3-4 weeks
3

System Development

Once we know it works, we build the full system. This involves a lot of back-and-forth. Your team knows what they need better than we do, so we adjust as we go based on their feedback.

6-10 weeks
4

Training and Rollout

Getting people comfortable with new systems takes time. We run training sessions and stay close during the first few weeks of live operation. There are always little adjustments needed once real work starts flowing through.

2-3 weeks
5

Monitoring and Refinement

The system runs, but we keep watching performance metrics. Sometimes the AI needs retraining as your business changes. Sometimes workflows need tweaking. This phase never really ends—it just becomes routine maintenance.

Ongoing

Wondering If Automation Could Work for You?

The best way to find out is to talk through your specific situation. We can usually tell within a conversation or two whether automation makes sense for what you're trying to accomplish.

Schedule a Conversation Learn More About Our Approach