Evaluate with stronger evidence
Connect the claim to what happened in the field.
Telematics + Warranty Decision Intelligence
Turn Telematics Data into Better Warranty, Quality, and Repair Decisions
Connect what your products are telling you with the decisions your teams need to make. Use telematics and IoT data to evaluate claims, detect emerging quality issues, and guide technicians to the right repair.
For OEM warranty, claims, quality, and service leaders.
PRODUCT SIGNALS → SERVICE CONTEXT
Signal. Evidence. Decision.Sensor history + repair context + policy
Answer • Decide • Act.Automotive & EVHeavy equipmentIndustrial & connected products
Find the pattern earlier
Connect individual events to emerging fleet issues.
Act before costs escalate
Connect the right diagnosis to the right intervention.
From connected data to connected decisions
Your product has a history.
Put it to work on every decision.
A fault code is a starting point. Warranty Decision Intelligence adds the repair evidence, product knowledge, and policy context needed to determine what should happen next.
01 / Connect
Bring the evidence together
- Telematics & IoTSensor readings, DTCs, event history, operating hours
- Repair evidenceRepair orders, diagnostics, images, video, log files
- Product & business contextVIN or serial number, software, service history, warranty terms
02 / Interpret & decide
Warranty Decision Intelligence
- Establish contextMatch assets, align timelines, assess data quality
- Evaluate the evidenceInterpret patterns, compare peers, apply policy
- Recommend the next actionExplain the reasoning, confidence, and missing information
Answer • Decide • Act.
03 / Act
Move work toward resolution
- Warranty teamsApprove, request evidence, or route for review
- Quality & engineeringOpen investigations and prioritize affected populations
- Service & parts teamsPlan diagnostics, schedule service, guide repair and returns
↶ Close the loop: confirmed repairs, inspection findings, and post-repair performance inform future decisions.
Connect authorized data from your existing telematics or IoT platform. Available decisions depend on signal coverage, integration scope, validated models, and your configured approval policies.
Six decisions that matter
Turn available signals into
practical warranty outcomes.
With the right data feeds and decision models, Circuitry.ai can help teams move from reviewing events to resolving the work those events create.
Corroborate the claim
Compare the complaint, cause, and correction with fault events, operating conditions, mileage or hours, and service history. Surface supporting evidence, inconsistencies, and gaps for the claim reviewer.
Intervene before a larger repair
Identify deterioration patterns and prioritize inspection or maintenance. Use urgency, asset criticality, parts availability, and customer schedules to coordinate an authorized service action.
Detect emerging quality issues
Look for repeated fault sequences across models, build periods, component variants, regions, or software versions. Rank investigation candidates by severity, affected population, and potential cost.
Guide the right diagnosis
Give technicians the event timeline, likely causes, relevant service information, and recommended tests. Help distinguish component, wiring, sensor, calibration, and software issues before replacing parts.
Choose the right parts-return action
Use digital evidence, failure patterns, supplier terms, and inspection value to recommend physical return, targeted testing, additional evidence, or an authorized no-return disposition.
Verify the repair and learn
Compare post-repair behavior with the original symptom and track recurrence. Link confirmed causes and inspection findings to claims, quality investigations, and supplier-recovery evidence.
A more complete claim story
See what happened.
Understand what it means.
Telematics becomes another piece of repair evidence, alongside diagnostics, photographs, video, technician notes, and log files. The value comes from interpreting those sources together.
- Reconstruct the sequence. Align the reported symptom with conditions before, during, and after the event.
- Assess the source. Check timestamps, sensor validity, sampling gaps, and whether the data represents the claimed asset.
- Explain the recommendation. Show supporting evidence, conflicting information, and the next review or repair step.
Missing telemetry does not prove that a fault did not occur. A sensor alert alone does not establish coverage, causation, or grounds to deny a claim.
Intermittent cooling complaintIllustrative scenario
Reconstructed event sequence
- Normal operation at low load
Available telemetry provides a baseline for the same asset.
- Temperature rises under load
Fan-command and speed signals diverge while a related fault is logged.
- Workshop test does not reproduce it
Idle testing differs from the conditions captured in the field.
Evidence gap: confirm the event conditions and complete the OEM diagnostic procedure.
A hypothesis to investigate
Test the control path before replacing the assembly.
The event history supports an intermittent symptom under load. The command/speed mismatch points to a diagnostic path; it does not establish the failed component.
- Signal validity and wiring
Verify sensor readings, connections, power, and control signals.
- Service bulletins and software
Review applicable procedures and approved updates for the asset configuration.
Decision status: more evidence required. Confidence depends on signal quality and test results.
Governed next steps
Give each team a clear action.
- Complete the directed tests
Use approved procedures to test under relevant operating conditions.
- Review the completed evidence
Evaluate coverage, causal findings, and repair reasonableness together.
- Look for recurrence
Monitor comparable assets and post-repair behavior; escalate a supported pattern.
Make the intermittent visible
The workshop sees a moment.
Telemetry can reveal the conditions.
Illustrative sensor behaviorIntermittent event
Digital evidence sufficient?Support an authorized remote diagnosis or no-return decision.
Physical evidence needed?Request the part with a focused inspection plan.
Conceptual example. Return requirements remain governed by OEM policy, supplier terms, and applicable retention requirements.
Reduce No Trouble Found
Preserve the evidence
before replacing the part.
A component that passes a bench test may have failed intermittently, or may never have been the cause. Sensor history helps teams ask better questions before replacement and return.
- Capture the conditions. Retain load, temperature, vibration, voltage, and fault sequences when available.
- Test the alternatives. Check wiring, connectors, sensors, configuration, and software alongside the suspected component.
- Guide the repair. Combine the event evidence with the OEM diagnostic procedure and known repair information.
- Make returns purposeful. Select parts that need physical inspection and send the associated event history and test instructions.
- Confirm the result. Monitor for recurrence and feed inspection findings back into future decisions.
What your data can support
Start with the signals you have.
Build toward the decisions you need.
| Available data | What AI can help interpret | Decision it can support |
|---|---|---|
| DTCs, event logs & freeze frames | Fault sequences, recurrence, and conditions around a reported event | Claim corroboration, directed diagnosis, and additional evidence requests |
| Temperature, pressure, vibration & electrical signals | Abnormal behavior and deterioration relative to validated baselines | Condition-based maintenance, targeted testing, and impending-failure alerts |
| Mileage, hours, load & duty cycle | Usage context and exposure across comparable assets | Policy review, service timing, and fairer quality comparisons |
| Software versions & update history | Changes in fault behavior by release and product configuration | Software investigation, approved update eligibility, and repair guidance |
| EV battery & charging data | Temperature, cell imbalance, charging patterns, and degradation indicators | Battery diagnostics, component-level investigation, and coverage assessment |
| Build data, component identity & repair records | Concentrations by model, plant, batch, supplier, or previous repair | Affected-population analysis, quality prioritization, and supplier investigation |
| Post-repair signals & inspection findings | Whether symptoms recur and whether the suspected cause was confirmed | Repair verification, NTF learning, return disposition, and recovery evidence |
Capabilities are scoped to the data actually available. Predictive alerts need validated time-series or failure models; generative AI helps explain findings and retrieve relevant knowledge.
From one asset to an emerging issue
Give quality teams an earlier, clearer signal.
- Compare affected and unaffected assets with similar age, usage, and operating conditions.
- Normalize incident rates by connected population or exposure, so fleet growth does not masquerade as a quality problem.
- Rank hypotheses by evidence, severity, scale, and potential cost; route them to an accountable owner.
- Track countermeasures and recurrence to learn whether the corrective action worked.
Measure decisions and outcomes
Make the value visible
from the first use case.
Begin with one product family, recurring fault, or claim population. Establish the baseline, compare AI-assisted decisions with expert review, and track outcomes through resolution.
Claim quality & effort
Evidence completeness
Reviewer agreement
Review time and rework
Quality detection
Time to a validated issue
Alert precision
Detection-to-correction time
Repair effectiveness
First-time fix rate
Repeat repairs
Unplanned downtime
Parts & cost
NTF rate on inspected parts
Return and inspection cost
Warranty cost per unit
Bring a problem. Map the decision.
In your demo, identify the available signals, the evidence gaps, and the warranty or repair decision worth improving first.
Enterprise control, built into the journey
Your data. Your policies.
Your decision authority.
Fit your existing environment
Scope connections to your telematics platform, data lake, warranty system, DMS, service tools, and quality processes. Use batch history or event feeds according to the decision’s needs.
Keep the reasoning reviewable
Retain source evidence, timestamps, policy references, and decision history. Escalate uncertain, conflicting, or high-impact cases to the right expert.
Govern data and action
Apply authorized access, customer data segregation, retention controls, and approval rules. Expand automation as evidence quality and measured performance support it.
Questions OEM leaders ask
Start with a useful scope.
Do we need continuous, real-time telemetry?
No. Historical files, event-triggered records, and periodic feeds can support evidence review and trend analysis. Time-sensitive intervention requires sufficiently timely data. The initial use case determines the right integration and latency.
Does a telematics alert automatically decide a warranty claim?
No. It contributes evidence. A claim decision also needs the applicable warranty terms, repair findings, and policy controls. Missing data or an unexplained alert should prompt an evidence request or review, not an unsupported denial.
Can this work with our existing IoT platform?
The solution can be scoped around authorized APIs, event feeds, or data exports from your existing platform. Asset identifiers, signal definitions, timestamps, access rights, and history coverage are assessed during solution design.
Can telemetry eliminate all No Trouble Found cases?
No. Some faults are not instrumented, may not be captured, or still require physical inspection. The goal is to preserve useful field context, improve diagnostic choices, and make parts returns more targeted.
How do we validate impending-failure predictions?
Evaluate models against confirmed failures and service outcomes for the relevant product population. Measure false alerts, missed failures, and useful lead time before enabling operational actions, then monitor performance as products and usage change.
See Warranty Decision Intelligence in action
Make your connected data count.
Request a demo to explore how telematics and IoT evidence can improve warranty, quality, and repair decisions for your products.
- Walk through a claim with connected evidence
- Explore emerging-issue and repair scenarios
- Map a practical starting point for your OEM
Answer • Decide • Act.
Request your WDI demo
Tell us where connected data could make the biggest difference.
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