Skip to content Skip to footer
Menu Close
Close
Get in Touch

AI needs to be trained and validated on realistic data - yet real-world data is scarce, expensive, and slow to collect and annotate Introducing MIMIC Transforming real-world multimodal recordings into repeatable, audit-ready validation evidence Recorded Data MIMIC Reconstruction Physical AI Data and Validation Infrastructure Platform Create variants at scale in real time with multimodal (camera, lidar and radar) scene reconstruction Recorded Data MIMIC Reconstruction Real-world object reconstruction for unlimited testing in autonomous system Recorded Data MIMIC Reconstruction Data with real-world fidelity, closing the simulation gap in open and closed loop scenario testing Recorded Data MIMIC Reconstruction Accurately reproduce any sensor output to support auditability and stakeholder review Recorded Data MIMIC Reconstruction

Assured Autonomy & Validation
with Trust-Quantified Test Assets

Turn scarce sensor logs into repeatable accurate real-world reconstructions, coverage-driven scenario variants, and defensible evidence ready for V&V and release gates.

From Limited Data Captures to Millions,
High-Fidelity Scenario Sets

As AI systems demand ever-larger datasets for training and validation, traditional real-world collection is proving too slow and costly.
Qvyon’s MIMIC™ platform expands limited sensor inputs into millions of diverse, high-fidelity real-world scenarios, instantly and across all sensing modalities.

  • Real-world fidelity for safety-critical model validation 
  • Sensor-agnostic across camera, radar, LiDAR, and fusion
  • Accelerated, cost-efficient scenario generation at scale

The real constraint in Physical AI is producing credible, repeatable, and auditable evidence that the systems work in diverse real-world scenarios

Critical Data is scarce

Collecting rare and edge-case scenarios requires years of effort. 

Fidelity is inconsistent

Synthetic content lacks the reality-grounded detail for credible training and validation

Operational tempo is unforgiving

The cycle from collection usable 3D test assets is too long for rapid iteration

Repeatability and traceability are weak

Lack of versioned regression assets and provenance to defend results across stakeholders

MIMIC™
Reality-Grounded Neural Reconstruction for Physical AI

Turns a small set of real, high-value sensor logs into sensor-consistent 3D/4D reconstructions, generates coverage-driven scenario variants, and outputs versioned test assets with evidence package (provenance, fidelity, uncertainty) that can be used as release gates for training, validation and regression

Why Customers Chose MIMIC

  • Reality-anchored: assets are derived from real sensor data
  • Coverage-driven: systematically closes validation gaps
  • Trust-quantified: built-in provenance plus fidelity/uncertainty signals
  • Regression-ready: fast iteration on software-defined systems.

Let’s Talk About Your Most Critical Scenarios 

Tell us about your sensor setup, validation targets, and where your coverage falls short. MIMIC™ can help you close those gaps, faster, more affordably, and with greater confidence in every outcome. 

    Qvyon All Rights Reserved.