Manufacturing AI

AI-powered bottleneck detection and continuous improvement for manufacturing

Kaizon is an AI agent that monitors your production, identifies bottlenecks, and drives improvement initiatives autonomously. No dashboards to check. No consultants to hire. Just measurable gains, every week.

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98%
of manufacturers are exploring AI, but few know where to start
35%
annual growth in AI manufacturing market through 2030
24/7
autonomous monitoring, no human intervention required
How It Works

Connect your production data, get a ranked fix list, track it to result

Step 01
📊

Connect your production data

Drop in a CSV or enter records by hand — cycle times, defect rates, downtime, throughput. Whatever your MES, ERP, or shift log already captures, Kaizon reads it. No new instrumentation required.

Step 02
🎯

Kaizon flags waste and prioritizes fixes

The AI scans your data across shifts, stations, and machines to surface where time, material, and throughput are bleeding. You get your top 3 improvement opportunities, each with an estimated impact and a concrete next action.

Step 03
📈

Track every initiative to result

Every analysis is stored in your history with its bottlenecks, status, and impact estimate. Re-run after the fix lands — see the delta. Continuous improvement that compounds, instead of dying on a whiteboard.

See It In Action

The full workflow — from data to decisions

Data Entry
Analysis name...
Manual Entry
Upload CSV
Station / Machine
Cycle Time
Value
Unit
Cycle Time Welding Station A · 45 sec Morning
Defect Rate Assembly Line B · 3.2% Afternoon
Downtime Paint Booth C · 28 min Night
Run AI Analysis →
AI Analysis Results
Welding Station Cycle Time
#1
HIGH ~12% throughput gain
→ Upgrade electrode tips and calibrate torch pressure
Assembly Line Defect Rate
#2
MEDIUM ~8% defect reduction
→ Implement torque verification check at station 7
Paint Booth Downtime
#3
LOW ~5% uptime gain
→ Schedule preventive maintenance on cure oven
Analysis History
Q2 Line Performance
May 13, 2026 · 3 bottlenecks
Completed
Shift A Audit — April
Apr 29, 2026 · 3 bottlenecks
Completed
March Bottleneck Scan
Mar 18, 2026 · 2 bottlenecks
Completed
Weekly Ops Review
Mar 5, 2026
Pending
Built for Manufacturing Teams

Production intelligence, not another dashboard

📊
100+
data points analyzed per record — not just cycle time, but shift patterns, defect correlations, and throughput anomalies
Seconds
from data submission to ranked bottleneck report — no consultant engagement, no multi-week study
💰
Free
to try. Full analysis with real recommendations. No credit card, no onboarding call, no sales pitch
The Shift

From reactive firefighting to autonomous production optimization

Before Kaizon

  • Hire consultants for 6-month Kaizen events
  • Improvements die after the consultant leaves
  • Data sits in spreadsheets nobody opens
  • Problems found when it's already too late
  • Knowledge walks out with experienced operators

With Kaizon

  • Continuous improvement runs every single day
  • AI never forgets, never takes vacation
  • Data becomes decisions automatically
  • Issues caught before they hit your bottom line
  • Institutional knowledge lives in the system
Frequently asked

The questions we hear before a first call

What does Kaizon cost?

Low monthly subscription, tiered by line/shift count, with a free trial tier that runs the full analyzer against your real production data so the ROI conversation is grounded in your numbers — not a slide deck. Cheaper than a single 6-week consultant engagement, and the implementation cost is zero: no sensors to install, no MES integration work in the trial tier.

Where does our production data live?

In Postgres (Neon) inside the customer's account boundary. The AI analysis receives only aggregated/shifted inputs — no raw ERP dump, no PII on operators. Cycle-time distributions, scrap-rate histograms, and OEE rollups by shift are not retained for model training, and you can delete any analysis at any time from the /history page.

How much onboarding effort is this?

Your first analysis runs from a CSV export you already have — MES shift log, downtime log, scrap log. Usually about a 1-hour upload plus a 5-minute row-mapping session. Not a multi-week integration project: no PLC tapping, no new sensors, no on-prem install. The slice a small/mid-size manufacturer needs — cycle time, defect rate, downtime, changeover — is already in the data your line is generating.

What ROI timeline should we expect?

Your first improvement opportunity shows up within the first analysis (minutes, not months). The typical first measurable gain — shorter changeover, scrap-rate drop, unplanned downtime cut — lands within a single shift cycle of acting on the recommendation. Because Kaizon is continuous monitoring rather than a one-off project, the second and third wins compound weekly instead of waiting for the next month-six review.

How is this different from hiring a lean consultant?

A consultant runs a 6-week Kaizen event, hands over a report, and leaves. Kaizon monitors every shift, 24/7, and catches regressions the day they appear. The AI never forgets, never takes vacation, never context-switches to the next client's event. Continuous improvement as an installed capability, not a project deliverable that dies on a whiteboard.

Kaizen was a philosophy.
Kaizon is the machine.

Built for the factories that know they need continuous improvement but don't have the headcount to sustain it. The AI operations manager that never clocks out.

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