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AgricultureAustralia10 weeks
Atlas Grain
Saving $1.2M a year with predictive maintenance
$1.2M
Annualized savings
−63%
Unplanned downtime
14d
Mean detection lead time
The challenge
Six processing plants relied on calendar-based maintenance, leading to unplanned downtime that cost an average of $48k per incident.
What we shipped
Sensor ingestion pipeline + anomaly detection model with a mobile alerts app for field engineers, plus exec-level reliability dashboards.
- Discovery sprint with executive sponsor + frontline operators
- Architecture review and security threat model
- Production build with daily client demos
- Eval suite + observability + on-call rotation
Outcomes
$1.2M
Annualized savings
−63%
Unplanned downtime
14d
Mean detection lead time
Numbers above are sourced from the client's BI warehouse and independently reviewed at quarterly business reviews.
Ready when you are
Get a fixed-fee proposal in 48 hours.
Tell us about the problem. Within two business days you'll get a scoped SOW, a delivery date we'll commit to, and the senior names who'll work on it. No procurement gauntlet.
- 48 hoursFrom intro call to signed SOW
- 11 daysMedian time to public launch
- 0 lock-inCode lives in your repos, your cloud
- 5% creditFor every day we miss our delivery date