MANUFACTURING · IoT · Edge AI · Digital Twins

    The machine tells you first

    Predictive maintenance across twelve plants, four continents.

    GLOBAL AUTO MANUFACTURER · 12 PLANTS // 28 WEEKS // BOLT GROUP

    $12MAnnual maintenance savings
    Built with
    Apache Kafka
    TensorFlow
    PyTorch
    NVIDIA Jetson
    Kubernetes
    InfluxDB
    Grafana
    Microsoft Azure
    The situation

    A global automaker was losing $50 million a year to unplanned equipment failures. Traditional scheduled maintenance was either too frequent — wasting 30% of the budget on healthy machines — or too late, causing cascading line shutdowns. Ten thousand sensors were generating data. Nobody was listening.

    Why it mattered
    $50MAnnual unplanned-failure loss
    30%Maintenance budget on healthy machines
    10,000+Sensors generating untapped data
    CascadingLine shutdowns from late detection
    client
    Global Auto Manufacturer · 12 plants
    duration
    28 weeks
    services
    IoT, Edge AI, Digital Twins
    sector
    Manufacturing & Industrial
    The approach

    Four moves, built to compound.

    1. 01

      Edge sensor network

      Edge nodes at each plant collect and pre-process vibration, temperature, pressure, and acoustic data from 10,000+ sensors in real time.

    2. 02

      Failure prediction

      Deep learning models trained on 5 years of failure data identify degradation patterns 48–72 hours before failure occurs.

    3. 03

      Prioritized alerts

      Alerts factor failure probability, production impact, spare parts availability, and crew scheduling into a single ranked feed.

    4. 04

      Digital twins

      3D digital twins of critical equipment with live health scores, anomaly visualization, and maintenance recommendations.

    Delivery discipline
    • Principal-ledSenior engineers and architects on the keyboard from week one. No staffing pyramid, no handoffs to juniors mid-engagement.
    • Production-firstEvery artefact ships behind a load balancer. We measure success in throughput, latency, and uptime — not slides.
    • Outcome-boundScope, milestones, and acceptance criteria locked at kickoff. We commit to the metric that moves your P&L.
    Technology
    1. 01Apache Kafka
    2. 02TensorFlow
    3. 03PyTorch
    4. 04NVIDIA Jetson
    5. 05Kubernetes
    6. 06InfluxDB
    7. 07Grafana
    8. 08Azure
    28 WEEKS · IOT · EDGE AI · DIGITAL TWINS · SHIPPED
    The outcome

    What shipped. In production.

    0%
    Less downtime
    Unplanned production loss
    $0M
    Annual savings
    Avoided emergency repairs
    0%
    Prediction accuracy
    Critical equipment
    48–72h
    Lead time
    Before failure event
    0
    Plants live
    Across four continents
    28wk
    Delivery
    End-to-end deployment
    The insight
    "Every prevented failure makes the model smarter, which makes the next failure less likely. Predictive maintenance is the rare operational lever with compounding returns."
    BOLT GROUP // PARTNER'S NOTE // BOLT GROUP // PARTNER'S NOTE // MANUFACTURING
    How we engage

    Three shapes. One delivery standard.

    A / Fixed-scope build

    Defined outcome. Fixed price.

    We scope, build, and ship a discrete production system end-to-end. Best when the brief is sharp and the deadline is real.

    B / Retained capacity

    Embedded pod. Monthly cadence.

    A senior pod plugs into your team for a multi-quarter horizon. Roadmap evolves; the engineers stay constant.

    C / Advisory & audit

    Senior eyes. Surgical scope.

    Architecture review, model audit, or technical due diligence. Days to weeks. Written recommendations, not slideware.

    Start the conversation

    Let's build what's next.

    No SDR queue. No discovery deck. Pick a slot or send a note — Dean replies within four business hours.