Autonomous Systems Evidence Assurance
Review supplied autonomous-system evidence without giving the assessment service control over a live vehicle or machine.
Who this is for
Autonomy validation leads, robotics engineering teams and vehicle-program reviewers using offline, replay or shadow evidence to decide what deserves higher-cost validation next.
The problem you already have
A replay can look harmless until state, action and safety evidence are reviewed together
Direct safe-robotics technical lineage supports bounded review of physical-system state, action and safety relationships. For this product, that means replay, scenario or shadow evidence can be screened for inconsistent or unsafe transitions before a team spends more on live-system validation.
One questionable autonomy event should not force an immediate live-machine test
Offline and shadow evidence gives validation teams a lower-risk place to separate reproducible safety concerns from incomplete or unsupported cases. The assessment keeps each finding tied to the supplied scenario and evidence rather than treating a raw replay log as a decision-ready conclusion.
Evidence assurance must stay separate from control of the machine
Live vehicle credentials, actuator or steering authority, controller modification, road-release authority and safety certification remain outside the service. The assessment is intentionally positioned before higher-cost or live validation, with all actuation decisions remaining customer-owned.
Real-World Operational Scenario: The Replay That Looked Safe Until One State Transition Broke the Evidence Chain
Scenario: An offline vehicle or robotics replay completes without an obvious failure, but one transition between sensed state, planned action and resulting state is inconsistent with the rest of the supplied evidence.
The autonomy team needs to know whether the event is a reproducible safety concern, an evidence gap, or an unsupported case that should be held before a higher-cost validation campaign.
WITHOUT this gate: raw replay logs can be promoted directly into live testing, or a subtle inconsistent transition can disappear inside a large scenario package.
WITH this gate: supplied state, action, transition and safety evidence are reviewed together, with inconsistent, incomplete and unsupported cases separated for human follow-up. The result does not command or modify the live machine.
What BivectorAI Provides
Replay / Shadow Consistency Review
Reviews whether the supplied replay, scenario or shadow evidence forms a coherent state-action sequence for the agreed autonomy question.
Unsafe-Transition Screening
Surfaces bounded transitions or evidence relationships that merit deeper safety review before higher-cost or live validation.
Evidence-Gap & Unsupported-Scope Classification
Separates supported safety findings from incomplete evidence, inconsistent scenarios or requests outside the current assessment boundary.
Customer-Owned Actuation Boundary
Returns evidence-linked findings while vehicle credentials, actuator authority, controller modification, road-release decisions and safety certification remain outside scope.
Prove the Gate Before Broader Integration
Back-test the autonomy evidence gate against frozen offline, replay or shadow cases with known expert disposition.
Freeze the accepted state/action fields, transition relationships, safety-consistency rules, evidence-gap conditions, unsupported-scope rules and review thresholds before revealing the reference disposition. Broader integration is justified only if the same bounded contract reproducibly separates stronger evidence from inconsistent, unsafe-transition, incomplete or unsupported cases. This is a proposed validation methodology, not road-release approval, safety certification or live-system authority.
What you provide
A bounded replay, scenario or supplied system-state package appropriate to the agreed autonomy evaluation.
What BivectorAI actually hands you
Offline / shadow evaluation findings
A bounded finding tied to the exact replay, scenario or supplied system-state package.
Evidence-linked safety & consistency findings
A concise record of supported transition, consistency or review-required conditions in the supplied evidence.
Unsupported-scope rejection
An explicit fail-closed result where the requested autonomy question exceeds the supported evidence boundary.
Bounded input-linked review artifact
A retained artifact tying the returned findings, limitations and human-owned next steps to the exact supplied case.
What we will never ask you for
Autonomy assurance becomes a different product the moment an assessment service can command the machine. This surface is intentionally kept on the evidence side of that line.
- Live vehicle credentials.
- Actuator or steering authority.
- Controller modification authority.
- Safety certification or road-release authority.
How it actually runs
Start with a bounded evaluation
Fixed scope / quoted per engagement. Inputs, outputs, evidence boundary and acceptance criteria are agreed before work begins.
We do not open with an annual license. Start with the bounded engagement. If it does not establish that the capability is useful and supportable for the agreed problem, there is no reason to move into a broader commercial commitment.
Bounded autonomous-system evidence evaluations are supported within a broader customer-facing assessment scope. Public claims are limited to offline, replay or shadow evidence assurance; no live actuation, road authority or safety certification is provided.