Pilot plant
One plant. Streaming ingest, baseline anomaly detection, shop-floor dashboard.
Multi-plant manufacturer. Predictive-maintenance platform reduced unplanned downtime ~30% in eight months.
Predictive-maintenance platform reduced unplanned downtime ~30% in eight months.
i
This is a representative engagement pattern, not a specific named client. Numbers are typical of the work we ship in this category. We share named references on a private intro call, with the client’s explicit permission.
Engagement · 8 monthsIndustrialAI in production
Illustrative
−28%
Unplanned downtime
$2M+
Annualised savings
40+
Plants live
Challenge
A multi-plant manufacturer was bleeding money to unplanned downtime. Sensor data was already being collected, nobody was acting on it.
Approach
- Streaming data lake aggregating signals across 47 plants, with a pragmatic schema.
- Anomaly-detection models tuned per asset class, with a refreshingly boring operator UI.
- Roll-out plant-by-plant, with operator champions and a 'do not surprise the floor' rule.
Outcome
-28% unplanned downtime in eight months, $2.1M annualised savings, all 47 plants live.
Brief us on your engagementHow we ran it
The shape of the engagement.
Model tuning
Per-asset-class anomaly detection, calibrated to the floor, validated by operators.
Operator UI
Boring on purpose: high contrast, large hit targets, clear escalation, zero surprises.
47-plant rollout
Plant-by-plant rollout with on-site training, operator champions, and zero shop-floor disruption.
Services involved
Capabilities we deployed.
Stack we shipped with
The tools that did the work.
AWS IoT
Apache Kafka
Snowflake
TimescaleDB
scikit-learn
PyTorch
Grafana
Datadog
By the numbers
Multi-plant manufacturer · the result.
Metrics agreed in week one, reviewed weekly with the sponsor and reported quarterly to the exec team.
- Real metric, not vanity. Reviewed weekly.
- Multiple capabilities, one accountable team.
- Stack chosen for fit, not familiarity.
-28%
Unplanned downtime
$2.1M
Annualised savings
47
Plants live
0
Shop-floor incidents during rollout
"A streaming data lake, anomaly-detection models, and a refreshingly boring operator UI, installed plant-by-plant with zero disruption."
More work
Other engagements worth a look.
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