In this blog, we will explore how high-quality data training defines the reliability of AI systems. We’ll look at...
Read MoreProduct Verification & Validation for Physical AI
Bring safe, reliable Physical AI products to market faster.
Digital Divide Data (DDD) provides scalable, human-in-the-loop verification and validation services for robots, smart devices, autonomous systems, and other embodied AI, from early prototypes to production releases.
End-to-end test design & execution
Real-world scenario validation
Safety, reliability & compliance focused
Backed by certified QA specialists, trained annotators, and 24/7 global operations.
What We Verify and Validate
From perception to action, we verify and validate the full Physical AI stack.
Perception & Sensing
- Object, scene, and environment understanding
- 2D/3D detection, tracking, and pose estimation
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- Sensor fusion (camera, LiDAR, depth, IMU, etc.)
- OCR and label reading in real-world conditions
- Robustness to lighting, occlusion, clutter, and motion
Decision & Planning
- Policy and planning behavior in realistic scenarios
- Navigation and path-planning success (wayfinding, obstacle avoidance)
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- Task planning and sequencing (pick-and-place, sorting, inspection)
- Handling of ambiguous or conflicting inputs
- Failsafe and fallback behavior under degraded performance
Action & Human Interaction
- Task success rates for physical actions
- Interaction quality with operators/end users
- Gesture, voice, and UI/UX responsiveness
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- Multi-step task completion and recovery from human error
- Safety margins in proximity to people and fragile objects
System & Operations Readiness
- Regression testing across firmware and model versions
- Stability under long-running or repetitive workloads
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- Cross-environment performance (labs, warehouses, homes, field sites)
- Compatibility with production workflows and data pipelines
- KPI monitoring and feedback loops for continuous improvement
Our Product V&V Services
Performance Evaluation
We build custom performance evaluation pipelines for high-stakes AI models, measuring accuracy, resilience, and operational reliability. Our teams combine structured testing, domain-specific edge cases, and AI/ML diagnostics to ensure your system behaves consistently across real-world, degraded, and stress-induced scenarios.
Product Validation
We design and execute comprehensive validation workflows that confirm your AI models perform as intended across diverse users, environments, and operating conditions. Our teams validate full-stack functionality, end-to-end workflows, and interaction safety to ensure readiness for deployment and regulatory acceptance.
Safety Case Analysis
We create structured, evidence-backed safety cases that demonstrate your system is safe, well-tested, and compliant with domain-specific standards. Our analysts integrate hazard reviews, V&V evidence, mitigations, and safety arguments into clear, auditable packages that accelerate internal approvals and certification.
Industries We Support
Autonomous Driving
Scenario-based testing, behavior validation, and safety-case evidence for ADAS verification and validation across diverse ODDs.
Defense Tech
Mission-critical V&V for defense tech platforms, human-machine interfaces, autonomy modules, and safety-driven software systems.
Healthcare
Verification, validation, and safety documentation for medical devices, digital health tools, diagnostics, and clinical AI.
Robotics
Performance evaluation, reliability testing, and interaction-safety validation for industrial, service, and autonomous robots.
Why Choose DDD?
Deep experience in AI + QA
- Scaled data operations, labeling, and annotation
- Specialized teams for computer vision, robotics, and multimodal AI
Human-in-the-loop, ethically at scale
- High-precision managed teams in emerging markets
- Inclusive hiring with transparent, consistent processes
Built for co-creation
- Embedded in your product, engineering, and safety workflows
- From fast pilots to fully managed V&V, integrated with your tools and APIs
Global coverage, always-on delivery
- Follow-the-sun teams and multilingual testing
- Region-specific scenarios with secure infrastructure and strong data protection
How We Engage
Blogs
Explore the latest techniques and thought leadership shaping the future of Physical AI.
Building Robust Safety Evaluation Pipelines for GenAI
This blog explores how to build robust safety evaluation pipelines for Gen AI. Examines the key dimensions of safety,...
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Bias in Generative AI: How Can We Make AI Models Truly Unbiased?
This blog explores how bias manifests in generative AI systems, why it matters at both technical and societal levels,...
Read MoreEmpower Safe, Reliable Physical AI
Whether you’re bringing your first Physical AI product to market or scaling a mature platform, DDD can help you move faster without compromising safety, quality, or user trust.
Frequently Asked Questions
What do you mean by “Physical AI”?
Physical AI systems are AI-powered devices that act in the real world, such as robots, autonomous machines, inspection systems, and smart devices that see, decide, and move in physical environments.
What’s the difference between verification and validation?
- Verification – Did we build it right?
Checks your system against specs and requirements. - Validation – Did we build the right thing?
Tests behavior, safety, and usefulness in real-world scenarios.
DDD does both, so you see where the system passes, fails, and needs work.
What parts of the system can DDD test?
We can cover:
- Perception & sensing (vision, OCR, sensor fusion)
- Decision & planning (navigation, task planning, fallback)
- Action & interaction (task success, human interaction)
- System readiness (regression, stability, multi-environment)
Scope is tailored to your product and stage.
Do you need physical access to our robots/devices?
Not always. We support:
- Remote testing with simulations, APIs, logs, and recorded data
- On-device/on-site testing using your protocols and environments (directly or via local partners)
We’ll choose the right mix based on your security and setup.
What do you need from us to start?
Usually:
- A short product overview and use cases
- Requirements/safety constraints, if available
- Access to test environments (sim, API, devices)
- Any existing test plans or bug trackers
We then propose a focused pilot and test strategy.
How do you report results?
You’ll get:
- Key metrics (e.g., success rate, reliability, incidents)
- Defect logs with repro steps and evidence
- Scenario insights so you know what to fix first
We can plug into your tools (e.g., Jira, TestRail, internal platforms).
We combine human-in-the-loop (HITL) expertise with secure, scalable operations to deliver high-quality data for AI, ML,
and digital innovation.
Can you support continuous releases?
Yes. We act as an ongoing V&V operations partner:
- Regression testing for new firmware/model releases
- New scenarios as you expand markets and features
- Regular data and test-suite updates
How do you handle security and pricing?
- Security: Secure infrastructure, access controls, NDAs, and alignment with your internal policies.
- Pricing: Based on scope, complexity, and engagement model (pilot vs. ongoing). We define this after a short scoping call.