Reality, compared.
Quantify trajectory divergence. Preserve the units, frames and conditions behind every result.
Physical AI
V&V Engine
Test robotic and world-model behavior. Expose the failure boundary. Build an auditable case for deployment.
INDEPENDENT ASSURANCE / BEFORE AND AFTER DEPLOYMENT
V / TRACE 0248
SYNTHETIC REPLAY
SYNTHETIC REPLAY
END-EFFECTOR PATH
x 0.502 y 0.680 z 0.220
TASK SPACE / METERS
x 0.502 y 0.680 z 0.220
TASK SPACE / METERS
VERIFICATION STREAMNOMINAL / PASS
TRACKING ERROR2.0mm
EVIDENCE GATES04/ 04 passing
RUN TIME0.00s / demonstration
For the teams putting intelligence
into the physical world.
RoboticsAutonomous systemsEmbodied models
One evidence layerA capable model.
Is it a dependable system?
Between a successful demonstration and a defensible deployment lies the evidence that matters.
Behavior, bounded.
Scope the proof. Guard the runtime. Keep missing evidence from becoming a silent pass.
Intelligence, monitored.
Inspect perception conflicts, distribution shift and recursive-data degradation separately.
Evidence, preserved.
Trace each decision to its inputs, policy version and reviewer. Export a verifiable record.
01 / FAILURE LABDon't trust the demo.
Don't trust the demo.
Try to break it.
A small change in the world can become a big change in behavior. The evidence should make that impossible to miss.
INJECT A CONDITION
REFERENCE BEHAVIOR120 SAMPLES / 6s
TRACKING ERRORmm / time
GATE EVALUATION4 / 4
Trajectory divergence< 50 mm
3.0 mmSensor agreement> 80%
98%Unsupported perception< 8%
0%Workspace containmentTask envelope
In boundsSUPERVISORY DECISIONCONTINUE
All supplied observations remain inside the demonstration envelope.
EVIDENCE RECORD
traceev-nominal-0248
integritycomputing
originSYNTHETIC
02 / THE EVIDENCE PIPELINEOne system.
One system.
A chain of accountable decisions.
From the first scenario to the final review. Every claim has a source. Every handoff preserves the context.
INPUT CONTRACT
Make the conditions explicit.
Start with a trajectory, a task and an embodiment. Preserve the coordinate frame and the source of every observation.
Simulate
SCENARIO / ARM-REACH-0248
Intended trajectory + observed behaviorEXAMPLE / v1
03 / AUDITABLE BY DESIGNA result is only as strong
A result is only as strong
as the evidence behind it.
No disconnected scorecards. A traceable record of what was tested, what failed, and what remains unproven.
The evidence ledger
EXAMPLERUN / SCENARIOVERDICT
Traceable. Reproducible. Reviewable.
Versioned inputs and gate profiles. Independent review. Hash-linked records in the engineering backend.
BROWSER PREVIEW / SYNTHETIC RECORDS
PRODUCTION ATTESTATION REQUIRES AN ISSUING INSTANCE
PRODUCTION ATTESTATION REQUIRES AN ISSUING INSTANCE
verificationASSURANCE DOSSIER
EXAMPLE / NOT CERTIFICATION
EXAMPLE / NOT CERTIFICATION
EV-0248 / TASK-SPACE POLICY
PASSVerification record
Trajectory divergence3.0 mmPASS
Sensor agreement98%PASS
Unsupported perception0%PASS
Workspace containmentIn boundsPASS
EVIDENCE MAPPING / SCOPE REVIEW REQUIRED
EU Machinery Regulation 2023/1230
ISO industrial robot safety 10218:2025
EU AI Act 2024/1689
Engineering evidence supports assessment. It does not establish legal conformity or replace a qualified safety assessor.
Read the official machinery guidanceMAPPINGS, NOT CERTIFICATIONS
The capability is accelerating.
So is the responsibility.
Physical AI doesn't get a lower bar because the technology is new. Its evidence layer needs to catch up.
EU MACHINERY REGULATION20.01.2027
The mandatory application date for Regulation (EU) 2023/1230.
European Commission sourceOne policy. Many physical realities.
Generalist models cross tasks and embodiments. Verification must preserve the differences that matter.
Open X-Embodiment researchThe release is not the finish line.
New environments, updated policies and changing data create new failure boundaries. Assurance is a lifecycle.
Trust needs independent evidence.
Buyers, engineers and assessors need the same answer to a basic question: what, exactly, has been demonstrated?
04 / THE COMPANY WE ARE BUILDINGResearch-led.
Research-led.
Built toward the field.
An independent verification layer for the teams turning embodied intelligence into deployed systems.
AKFOUNDER / BUILDER
Adari Karthikeya
Building an independent verification layer at the intersection of physical-AI evaluation, software engineering and independent assurance.
[REPLACE] VERIFIED BIO / PUBLIC PROFILEWorking engineering foundation
Trajectory evaluation, scoped verification, provenance and governance workflows.
Design-partner validation next
Seeking a reference robot, representative traces and an agreed validation question.
Pilot evidence
[REPLACE] Confirmed partner, agreed scope and independently reviewed results. No pilot traction claimed.
Does this screening certify my robot?
No. This product organizes and evaluates engineering evidence. Product-specific safety qualification and conformity assessment remain with qualified independent professionals.
Is this a real robot running in the browser?
No. The website uses a deterministic synthetic trace and explicitly labeled failure examples. It is a product demonstration, not live hardware evidence.
Where does verification stop?
At the boundary of the evidence. Small neural components can receive scoped bounds; trajectory checks, perception corroboration and runtime supervision remain separate. No entire-VLA safety guarantee is claimed.
The next deployment
deserves better evidence.
One robot. One hard failure mode. One evidence package worth putting in front of an assessor.