A component is not the system.
Individually credible twins can behave differently once connected.
INDEPENDENT EVIDENCE FOR INDUSTRIAL AUTONOMY
Bring the twin
back to reality.
A proposed assurance platform to connect model credibility, integrated-system validation and real-world performance—through one traceable evidence story.
Bounded assurance. Not a blanket safety certificate.
THE EVIDENCE LOOP
SIMULATIONPHYSICAL TESTFIELD SIGNAL
Configuration-bound · continuously reviewable01THE GAP
A twin can be precise
and still be wrong
where it matters.
Most autonomy evidence is assembled in pieces: component models, integration tests, simulation campaigns and field logs. TwinEvidence is designed to make their relationship visible—and challengeable.
See the evidence modelA simulation is not the plant.
Matching traces do not prove performance in untested conditions.
A launch report can go stale.
Software, sensors, layout and use evolve after commissioning.
02THE PLATFORM
Not one certificate.
An evidence lifecycle.
An independent evidence layer across the people who build, integrate, operate and review an autonomous system.
01
MODEL & SIMULATIONEstablish twin credibility
Make purpose, provenance, calibration, uncertainty and known omissions visible before a model is used to support a decision.
02
INTEGRATIONAssure the assembled system
Connect component claims to the integrated configuration, interfaces, safety functions, scenarios and controlled physical tests.
03
FIELD PERFORMANCEKeep evidence alive in operations
Track what changed, where observed behavior departs from its reference, and when the prior assurance needs to be reopened.
One versioned claim–argument–evidence case. Clear scope, uncertainty, exclusions and reassessment triggers.
Follow the lifecycle
OBSERVE / COMPARE / REASSESS
Reference Observed
Concept visualization · not operational data
03SIM-TO-REAL, IN USE
The discrepancy
is evidence too.
Monitor the distance between what a validated model expects and what the system does—by configuration, operating condition and evidence quality.
Compare like with likeStratify residuals by operating domain and exposure.
Keep the context attachedPreserve model, software and site configuration with each result.
Trigger review, not controlA trend or gap opens a reassessment; it does not actuate equipment.
!
A growing gap is a reason to investigate—not a universal safety score or automatic risk verdict.
04HOW IT WORKS
A loop that keeps
its memory.
Claims are versioned and bounded. Evidence stays connected through design, integration, physical validation and monitored operation.
01
PHASE 01
Define the claim
Name the asset, intended task, configuration and operating design domain. State what is inside—and outside—the decision.
02
PHASE 02
Build the evidence case
Link model credibility, system integration, scenario coverage, test results, assumptions and unresolved limitations.
03
PHASE 03
Challenge in the physical world
Compare predicted and observed performance against pre-agreed measures, uncertainty and representative test conditions.
PHASE 04
Monitor, learn, reassess
Carry the configuration baseline into operations. A gap, incident or material change becomes a traceable review—not a hidden score.
05RISK & INSURANCE
A PERMISSIONED EVIDENCE PATHFrom operating
traces to a better
risk conversation.
An authorized, tamper-evident record can help an insurer review how risk changes over time—and reconstruct what happened around a loss.
Evidence for risk engineering
Exposure, residual trends, safeguards, near misses, changes and open actions—in context.
A verifiable event record
Preserve relevant traces, configuration, warnings, provenance and evidence gaps for investigation.
The operator authorizes access. The insurer decides pricing, coverage, causation and settlement. TwinEvidence does not automate those decisions.
EVENT RECORDIntegrity is not truth
01Source · context · custody · limitations
IMPORTANT DISTINCTION
Tamper-evident means changes can be detected after capture. It cannot prove a sensor was accurate, a record complete, the system caused a loss, or that a claim is covered.
06TRUST, BY DESIGN
Clear evidence.
Clear boundaries.
Trust grows when the platform is precise about what it can establish—and what it cannot.
Scoped opinion, not blanket certification
Every conclusion is tied to a named system, configuration, use and operating domain.
Read-only evidence layer
No control writes, safety overrides or dependence for safe operation.
Data stays governed
Purpose-bound access, selective disclosure and on-premises options for sensitive evidence.
People stay accountable
Operators accept residual risk; independent reviewers challenge evidence; insurers make their decisions.
THE PROMISE
Make the case reviewable. Keep the limits in view.
07START WITH A WEDGE
Small enough
to prove.
The first pilot should solve one real decision for one bounded autonomy use case—not promise a universal standard on day one.
Choose one system
For example, an indoor autonomous vehicle in a clearly defined zone and task.
Agree the evidence
Pair model and integration claims with controlled physical tests and explicit limits.
Follow it in service
Check whether monitoring and change triggers improve real review decisions.
Invite risk partners
Explore insurer evidence only after data rights, decision purpose and reliance are agreed.
08QUESTIONS, ANSWERED
Confidence without
overclaim.
A new evidence layer has to be clear about its limits from the start.
Is TwinEvidence a safety certificate for the whole system?
No. The concept is a bounded evidence and independent-assurance layer. Any opinion would name the system version, intended use, operating domain, evidence basis, conditions and validity period. It would not be a blanket warranty or permission to operate.
Does it replace the operator’s safety case or regulatory assessment?
No. The operator and responsible manufacturer retain their legal and operational responsibilities. TwinEvidence is intended to organize and challenge supporting evidence; it does not replace an applicable conformity route, safety lifecycle, regulator or residual-risk decision.
What does a growing sim-to-real gap mean?
It is a signal to investigate, not an automatic verdict. The interpretation depends on the measure, uncertainty, ODD, data quality, severity and whether the twin was expected to predict that quantity. A gap may require a restriction, test, model update or reassessment.
Can insurers use the evidence to set premiums or settle claims automatically?
That is not the proposed product boundary. With policyholder authorization, TwinEvidence could provide a permissioned risk profile or preserve a claim-event evidence package. Underwriting, premium, coverage, causation, liability and settlement decisions remain with the insurer and its established governance.