Silver Data Layer · IoT Query
Turn raw telematics data into
decisions you can act on
Your fleet collects millions of data points. Silver Data Layer transforms them into contextual insights that reduce fuel costs, improve safety, and deliver ROI in 3-9 months—without vendor lock-in or manual data wrangling.
72% of fleet leaders cite contextual analytics as the missing link between telematics collection and board-level KPIs
Need Raw Data Access?
Bronze LayerFor advanced troubleshooting, custom analytics, or building your own data pipelines, explore the Bronze Layer—direct access to every GPS point, sensor reading, and device message exactly as generated.
Explore Bronze Data LayerYou have the data. You're missing the story.
Fleets and telematics providers face the same challenge: raw data doesn't explain what happened or what to do next.
For Telematics Providers & Integrators
Integration friction drains engineering time
Every telematics integration becomes a custom ETL project. Raw APIs return inconsistent formats, missing context, and require constant normalization.
Impact: Your team spends weeks on data wrangling instead of building features that differentiate your platform.
Scalability bottlenecks as fleets grow
Ad-hoc data pipelines break under load. Query performance degrades. You're forced to rebuild infrastructure instead of serving customers.
Impact: Growth stalls because your data layer can't keep pace with customer demand.
Vendor lock-in limits flexibility
Legacy platforms force you into their ecosystem. Connecting to customer BI tools, ERP systems, or custom workflows requires workarounds.
Impact: You can't deliver the integrations customers need, and switching costs keep you trapped.
For Fleet Operators & Managers
Data overload without answers
Your fleet captures millions of GPS points and sensor readings daily, but you can't answer basic questions: 'Why was delivery late?' 'Which driver wastes the most fuel?'
Impact: Raw data doesn't explain what happened or what to do next. Every investigation requires hours of manual correlation.
Hidden costs drain your budget
85% of fleets collect comprehensive telematics data but analyze less than 30%. Idle time, inefficient routes, and preventable breakdowns go unnoticed.
Impact: You're missing $45,000+ per year in optimization opportunities—money that's leaking from fuel, maintenance, and operational inefficiency.
Safety incidents you could have prevented
You see alerts after incidents occur, but without context, you can't identify patterns or coach drivers proactively.
Impact: Accidents happen that better data could have prevented. Insurance premiums rise. Compliance violations pile up.
85%
of fleets collect comprehensive data but analyze less than 30%
$45k+
average annual savings missed per fleet due to unutilized insights
78%
of fleet managers struggle to quantify telematics benefits
Silver Data Layer: Context-ready telematics data
Sits between raw telematics (Bronze) and business dashboards (Gold). Automatically cleanses, normalizes, and enriches GPS, sensor, and event streams into business-ready entities.
Automatic context from raw signals
What It Does
Converts raw GPS, sensor, and event streams into business-ready entities: trips, stops, geofence visits, idle events, driver behavior. No manual correlation needed.
How It Works
Real-time stream processing with configurable business rules. Hardware-agnostic architecture handles any device protocol, late-arriving data, deduplication, and outlier filtering.
Proven outcome: Fleets see idle time drop 20% when they shift from raw data exports to contextualized reports.
Risk detection with full audit trail
What It Does
Correlates driving behavior, vehicle health, and location context to catch risk patterns early. Enables proactive coaching with audit-ready timelines.
How It Works
Versioned business rules for harsh events, geofence violations, HOS compliance. Full traceability from insight back to source data with configurable thresholds.
Proven outcome: Integrated context helps fleets reduce accidents and achieve 5-10% insurance premium reductions.
Open architecture, zero lock-in
What It Does
Works with your existing stack. Customize thresholds to match your operations—whether you run trucks, vans, or heavy equipment.
How It Works
Open SQL access, REST APIs, webhooks. Compatible with Power BI, Tableau, Grafana, and custom applications. Deploy on your cloud or ours.
Proven outcome: TSPs deliver white-labeled analytics to hundreds of customers without rebuilding pipelines for each one.
Bronze → Silver → Gold: The data journey
How raw telematics becomes actionable intelligence
Bronze: Raw ingestion
GPS pings, CAN bus data, sensor readings arrive with noise, mixed units, and inconsistent formats. Works with virtually any device protocol.
Silver: Contextual curation
Automatic transformation into trips, stops, geofence visits, idle events, driver behavior, normalized sensor values. Real-time processing with configurable rules.
Gold: Analytics consumption
BI dashboards, AI models, mobile apps consume consistent, trusted definitions. Open SQL, REST APIs, webhooks.
From device to insight in four steps
Connect any telematics source
Works with your existing GPS devices, OEM systems, or IoT sensors. Protocol-agnostic architecture connects via MQTT, REST APIs, and direct platform integrations. No rip-and-replace required.
Automatic transformation with context
Silver layer cleanses, normalizes, and enriches data in real-time. Converts raw signals into structured trips, stops, geofence visits, idle events, and driver behavior with configurable business logic.
Derive actionable KPIs instantly
Computes metrics like utilization rates, fuel efficiency per trip, dwell times, and safety scores—automatically linked to drivers, assets, and locations. Maintains full audit trail with versioned business rules.
Deliver to your tools
Push contextualized data to dashboards, mobile apps, or customer portals via open SQL interface, REST APIs, or webhook integrations. No middleware required.
Real scenarios, real outcomes
Logistics: Cut fuel costs, improve delivery
Context
A 50-vehicle delivery fleet was drowning in GPS data but couldn't identify why fuel costs kept rising.
Solution
Used trip records with dwell analytics to identify recurring idle spikes at specific docks on Mondays and Fridays. Adjusted schedules and driver coaching.
Outcome
Reduced idle fuel waste by 20% and improved on-time rates by 15%—saving $25,000 annually.
Construction: Maximize asset utilization
Context
Equipment manager needed to track utilization across 30 job sites but manual logs were unreliable.
Solution
Monitored geofence discipline and engine-hour utilization per site. Compared productive vs. idle hours for each excavator and crane.
Outcome
Prevented unauthorized moves and identified underused machinery, reducing idle costs by $12,000+ per vehicle annually.
Rental: Enforce contracts, predict maintenance
Context
Rental fleet operator struggled to enforce contract terms and predict maintenance needs across 200 vehicles.
Solution
Monitored harsh events, distance caps, and service anomalies. Correlated fault codes with driving patterns to schedule proactive inspections.
Outcome
Delivered auditable usage summaries to customers and reduced unplanned maintenance incidents by 18%.
TSPs: Scale analytics without custom ETL
Context
Telematics service provider was building custom data pipelines for each fleet customer—couldn't scale beyond 20 clients.
Solution
Used Silver layer as data foundation. Configured business rules per customer, delivered white-labeled dashboards via their brand.
Outcome
Now serves 200+ fleets without custom pipelines—reduced engineering overhead by 60% while improving retention.
Proven results from real fleets
3-9 months
Typical ROI payback period
Most fleets achieve ROI through fuel savings, reduced maintenance, and operational efficiency (FMCSA data)
20%
Average idle time reduction
When fleets use contextualized reports instead of raw data exports
3-5 hours
Weekly time saved per analyst
When trip, idle, and dwell definitions are standardized vs. rebuilt in spreadsheets
Silver Layer vs. Legacy Approaches
Stop wasting time on manual data prep. Get instant, contextual insights.
Data preparation
Legacy Approach
Manual Excel exports, hours of correlation, error-prone joins across systems
Silver Layer
Automatic transformation, real-time processing, zero manual prep required
Save 3-5 hours per analyst weekly
Insight depth
Legacy Approach
Raw GPS coordinates without narrative—can't answer 'why' questions
Silver Layer
Structured trips, events, timelines with full operational context
Answer 'Why was delivery late?' in seconds, not hours
Integration
Legacy Approach
Vendor lock-in, limited APIs, custom ETL for each system connection
Silver Layer
Open SQL, REST APIs, webhooks—works with your existing stack
Connect to any BI tool without vendor constraints
Scale
Legacy Approach
Ad-hoc pipelines break as fleet grows, performance degrades over time
Silver Layer
Built for scale—handles millions of data points daily with consistent performance
Grow from 10 to 10,000 vehicles without infrastructure rebuilds
ROI that pays for itself in months
Most fleets achieve ROI in 3-9 months through fuel savings, reduced maintenance, and operational efficiency.
Fuel & Idle Optimization
5-15%
fuel savings in 6 months (FMCSA data)
Contextualized idle reports identify wasteful patterns, directly reducing fuel costs.
Predictive Maintenance
$200-400
saved per vehicle annually
Normalized fault-code streams enable proactive maintenance, preventing costly breakdowns.
Insurance & Safety
5-10%
insurance premium reduction
Data-driven safety programs demonstrate risk management and qualify for discounts.
Frequently Asked Questions
Turn telematics data into competitive advantage
Whether you're a fleet operator seeking ROI or a telematics provider building scalable analytics—Silver Data Layer transforms raw data into decisions you can act on.
Ready to transform your telematics data?
Tell us about your analytics needs and we'll show you how Silver layer delivers ROI in months, not years.
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