Put behavior in context
Bring related signals together to understand how a vehicle behaves under real operating conditions.
Automotive & robotics Platform operational, onboarding now
Fleet Intelligence for Connected Devices
TelemetryLab turns operating data from connected vehicles and robotic fleets into diagnostic, prognostic, and operational intelligence. Monitor behavior remotely, investigate emerging issues, and bring the evidence into one connected workflow.
The problem
Telemetry / IntelligenceYour fleet produces the data. The hard part is the diagnosis.
Engineering teams need to understand what changed, which units are affected, and what to check next. That takes a connected view of vehicle behavior, operating conditions, and service history.
Build the evidence
Connect events and operating history to the investigation, so teams can review likely causes and the evidence behind them.
Focus the next action
Identify the vehicles and components that need attention, and give engineering and service teams a useful starting point.
The approach
One closed loop.
One clear view of your fleet.
Bring collection, detection, diagnostics, prognostics, and action into one connected view. Follow an emerging issue from its first signs through investigation, inspection, and follow-up.
Inside the system
Collect
Capture the meaningful fraction of the signal
Selective, event-based collection at the edge. On supported edge devices, collection widens when an investigation needs another signal, then scopes back down, with no firmware release.
Detect
Identify abnormal behavior across signals
Established machine-learning and statistical models learn how each vehicle normally behaves and flag the deviations that matter across related signals.
Diagnose
Assemble evidence, investigate likely causes
Related signals, events and service history come together in one investigation, with the likely causes and the evidence behind each.
Predict
Assess developing component risk
Risk models learn from each component’s history. A forecast reaches your team only when a validated model and enough evidence stand behind it.
Act
Guide inspection and follow-up
Findings reach the teams that act on them: what to inspect, which units are affected, and whether the fix worked.
Business outcomes
Safety / Warranty / Recalls / Suppliers / Service / Owners / Data trustOutcomes your business
is measured on.
Each module gives safety, quality, service and engineering teams a clearer basis for action, built on the data your vehicles already produce.
Safety & incident analysis
See the safety signal before it becomes an incident.
Examine abnormal braking, steering, thermal, electrical and driver-assist behavior in context, and give safety engineers the timeline of what happened and what is still developing.
- Build an event timeline from retained telemetry before and during an incident.
- Read every recorded safety event against the conditions the vehicle was operating in.
- See how driver-assist features are actually used on each vehicle, where qualified measurements are available.
Warranty & field quality
Catch the failure pattern while it is still a handful of vehicles.
Connect recurring component behavior with service and claim history, so quality and warranty teams see an emerging pattern before it becomes a claims curve.
- Set each recurring issue beside the vehicle’s software version, operating conditions and service history.
- Review the operating evidence around each repair or claim instead of treating it in isolation.
- Catch the inexpensive part that is drifting before it takes an expensive system with it.
A cooling pump that is wearing out can put a whole battery pack at risk. Find the small fault early, and the repair stays small.
Recall investigation & scope
Put evidence behind every recall-scope decision.
Understand whether an emerging issue is isolated or shared across a vehicle group, and build the evidence for deciding which units need a closer look. Recall and repair decisions stay with the responsible teams.
- Compare affected and comparable vehicles by configuration, software version or component records.
- Connect field patterns with service history to define the affected population.
- Verify the fix afterwards with repair or software-change records and comparable telemetry.
Supplier recovery
Trace a failure to the part, the batch and the supplier.
Bring the available build, component and supplier records into the same investigation as the operating data, so a recovery discussion starts from evidence, not opinion.
- Resolve vehicles to build, part and batch records where they are available.
- Keep the part, batch and supplier record attached to every failure under review.
- Hand the supplier an evidence package it can check for itself.
Service & uptime
Give technicians an evidence-backed starting point.
Bring operating history, fault context and related events together before the vehicle reaches the workshop, so the first visit can be the right one and vehicles stay in service.
- Know what to inspect before the vehicle arrives.
- Review recurring faults alongside mileage, duty cycle and previous service.
- Put the vehicles that need attention first, using recorded component behavior and service history.
- Keep the fault, the investigation, the repair and the follow-up together, so the next technician picks up where the last one left off.
Owner & driver insight
Give drivers the health report their car never had.
The intelligence that informs engineering can also feed the maker’s own app, so an owner can see how the vehicle is doing and what will need attention, long before a warning light.
- A running health view built from the status data the vehicle already produces.
- Advance notice of what needs attention, and why, ahead of the next service visit.
- A reason for owners to stay engaged with the brand between visits.
Data trust & evidence
Know what each finding rests on.
Every finding is tied to the measurements behind it: which vehicle, which signals, when, and what was not available. Teams can judge the evidence before they act on it.
- Each measurement keeps its source, vehicle and time.
- Signal coverage is part of the evidence, including what was missing.
- Findings point back to the observations that support them.
Coverage is established against the signals, history, and records available for your fleet.
TelemetryLab research
All researchWe publish what we find.
Analysis / Vehicle safety
The Unread Safety Signal
A field catalog of the safety signals a vehicle already broadcasts on its data bus: what each detects, how early, and the cost of leaving them unread.
Read the paper
Machine data access
The Codebook Lock
A deep-sea vessel's engine broadcasts its operating state in plain readable values, and the data still stays locked. Where the lock actually sits, three tiers of lawful access, and what extraction yields.
Read the paper
Analysis / Recall intelligence
The Recall Signal Gap
A data analysis of the U.S. recall record: how wide the recall-to-repair gap is, how much of it vehicle signal can reach, and what closing it is worth.
Read the paperGet in touch
See what it finds
in your fleet.
The platform is operational, and we are onboarding our first production customer. You work directly with the engineers who built it. If your fleet produces more signal than your teams can act on, let's talk.
Your data stays in your own dedicated environment. Our software and models run there to produce the findings, and we do not move your data out of it.
hello@telemetrylab.ai