Bruviti
Implementation guide

Build Installed-Base Asset Tracking That Cuts Time to Root Cause 65%

Incomplete serial number records and missing configuration data cost appliance OEMs millions in lost service contract revenue.

In Brief

Bruviti deployment data shows AI-driven installed-base tracking cuts time to root cause 65% and pushes per-prediction updates under 10 seconds. Build the asset graph once, connect appliance telemetry, and your service team locates the failing unit and its fault history in seconds instead of digging through spreadsheets.

Why Asset Tracking Matters

Incomplete Asset Records

Missing serial numbers and installation dates prevent proactive outreach. Legacy equipment registered with phone support lacks model details, firmware versions, or warranty status.

40%Assets Missing Serial Data

Configuration Drift

Installed firmware versions diverge from records. Connected appliances update automatically, but backend systems show stale data, breaking troubleshooting accuracy.

35%Configuration Mismatch Rate

Lost Contract Renewals

Service contract expiration dates aren't tracked consistently. Sales teams lack visibility into renewal candidates, leaving revenue on the table as warranties lapse unnoticed.

22%Contract Attachment Rate

API-First Asset Registry Architecture

Bruviti's headless asset registry ingests product registration data, IoT telemetry, and service history via REST endpoints. Python SDKs parse serial number formats, normalize model identifiers, and detect configuration changes without requiring proprietary client libraries. TypeScript bindings integrate with existing CRM and ERP systems using standard OAuth 2.0 authentication.

The platform tracks firmware versions, replacement part installations, and warranty milestones in a normalized schema. Developers write custom lifecycle rules using Python—flagging appliances approaching end-of-support, identifying upsell candidates based on usage patterns, or triggering proactive maintenance alerts when telemetry indicates impending failures. Data stays in your infrastructure; the platform provides the intelligence layer without data lock-in.

Technical Benefits

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    Asset accuracy improves by 65% within 90 days of API deployment.
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    Configuration drift detection reduces troubleshooting errors by 40% across all models.
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    Contract attachment rate increases 18 points through automated renewal identification.

See It In Action

Use case

Digital Twin Quality Monitoring

Track refrigerator compressor performance and HVAC cycle times in virtual models, enabling proactive maintenance before customer-facing failures occur.

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Use case

Connected Data Fault Detection

Analyze IoT streams from dishwashers and washing machines to identify anomalies like valve leaks or motor bearing wear before catastrophic failures.

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Use case

Failure Pattern Recognition

Identify recurring failure modes across the installed base—like ice maker valve defects or control board failures—to drive engineering improvements.

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Appliance Manufacturer Implementation

Appliance-Specific Asset Tracking

Appliance manufacturers face unique tracking challenges: decades-long product lifespans, consumer-owned installations without IT oversight, and a mix of connected and legacy equipment. The asset registry must handle serial number formats spanning 30+ years of products, normalize model identifiers that changed with acquisitions, and reconcile IoT telemetry streams with phone-based registration data.

Connected refrigerators, HVAC systems, and water heaters transmit real-time usage data, but 60% of the installed base remains offline. The platform bridges this gap by enriching sparse registration records with inferred data—estimating installation dates from warranty activation, predicting usage patterns from geographic location and household size, and flagging renewal candidates based on typical replacement cycles for each product category.

Implementation Strategy

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    Start with connected appliances to establish telemetry baseline before expanding to legacy products.
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    Integrate with warranty registration systems first to capture serial numbers at point of sale.
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    Track contract attachment rate and configuration accuracy quarterly to justify continued investment.

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Frequently Asked Questions

What APIs do I use to ingest appliance registration data?

The platform provides REST endpoints for bulk asset imports via CSV or streaming ingestion via webhook. Python SDK includes parsers for common serial number formats and model identifier schemas. OAuth 2.0 authentication integrates with existing identity providers, and rate limits scale to handle seasonal registration spikes during holiday purchasing periods.

How do I detect configuration drift for connected appliances?

Subscribe to configuration change webhooks that fire when IoT telemetry reports firmware updates or part replacements. The Python SDK includes a comparison function that diffs reported state against expected state, returning a list of discrepancies. You define tolerance thresholds—minor version updates may not require record updates, but major firmware changes or component swaps should trigger immediate sync.

Can I write custom lifecycle rules without vendor lock-in?

Yes. The platform exposes a rules engine where you write Python functions that evaluate asset records. Define conditions like "flag refrigerators older than 8 years with no service contract" or "alert when HVAC systems approach end-of-support dates." Rules run in your infrastructure using open-source libraries; no proprietary runtime required. Export rules as portable Python modules to avoid lock-in.

How do I track service contract renewals across the installed base?

The asset registry stores contract start dates, durations, and renewal terms. Query the API for assets with contracts expiring in the next 90 days, filtered by product category or geography. Integrate with your CRM to automatically create renewal opportunities. The platform calculates lifetime value metrics by correlating service history with contract status, helping prioritize high-value accounts.

What data stays in my infrastructure vs. the platform?

Raw asset records—serial numbers, installation addresses, customer PII—remain in your database. The platform ingests anonymized identifiers and telemetry streams, returning enriched metadata like predicted failure dates or upsell scores. You control data residency and can run the intelligence layer on-premises. API responses never include PII unless explicitly requested via authenticated endpoints.