Application of Neural Analysis in VIEWAPP Inspections
Digital inspections have become a critical element in insurance, banking, leasing, classifieds, and the public sector — they form the basis for subsequent management decisions. Today, the quality of data and the speed of decision-making directly depend on how accurately the system detects anomalies, prevents fraud, and helps experts work without overload.
Neural analysis in VIEWAPP is the foundation of this reliability: artificial intelligence verifies every photo, every coordinate, and every step of the process, transforming a regular inspection into a controlled, verifiable, and protected procedure.
We intentionally do not disclose all the details and technical mechanisms behind our algorithms. Only the most basic descriptions are available publicly — enough to understand the principles, but not enough to reproduce or bypass the protection. This is a critical part of our strategy, ensuring that malicious actors cannot adapt their schemes to the system.
Neural networks for detecting fake photos
One of the main risks in digital inspections is fake images: screen photos, reused old materials, or edited files. VIEWAPP applies several layers of protection to every image.
The system checks control sums (MD5, SHA). If a file has been altered or substituted, the expert receives an instant alert.
The next layer is a neural network trained on thousands of real and screen-captured images. It recognizes specific indicators of fakes: moiré patterns, matrix stripes, display glow, and screen distortions. This combination of classical algorithms and deep learning results in an almost zero probability that a screenshot will pass as a genuine photo.
Photo quality as a parameter of reliability
Even an honest photo can be useless if it’s blurry or taken from the wrong angle. Built-in quality detectors analyze sharpness, shadows, perspective, and color anomalies. The result is a consistent, expert-ready dataset suitable for evaluation and further automation.
Neural GPS analytics and protection against geo-fraud
Manipulating coordinates is one of the hidden fraud vectors. VIEWAPP applies algorithms that verify not only the correctness of GPS points but also the logic of the route.
The system detects:
- fake or repeating coordinates,
- impossible movement angles,
- speed jumps inconsistent with real motion,
- missing or artificially “shifted” points.
A dedicated neural network then classifies the trajectory as normal or anomalous. This makes it possible to immediately filter out attempts of remote data substitution.
Automatic annotation and object condition analysis
For vehicles, real estate, and other assets, VIEWAPP uses computer vision to detect damages, required angles, VIN numbers, and other parameters.
These outputs are presented in an annotation interface, where the expert confirms or corrects the system’s findings. This hybrid “AI + human” approach ensures high accuracy while preserving full control and transparency.
Continuous learning: the system becomes more accurate each month
Every inspection result, every expert correction, and every new example forms an updated training dataset. VIEWAPP uses modern machine learning frameworks — PyTorch and TensorFlow — and regularly retrains its models.
The cycle includes:
- Data recognition and error detection.
- Result analysis.
- Annotation of new samples.
- Model updates.
This ensures stable growth in accuracy as the system adapts to new scenarios, devices, and shooting conditions.
AI in property and auto assessment
A separate module automatically determines the value of real estate, interior finishes, or movable assets shown in photos. The neural network identifies the object, type of finish, estimated repair cost, and produces a structured dataset for valuation.
For vehicles, the system detects damages, body elements, required repair work, and prepares data for integrations with Audatex and SilverDat — reducing the process to an average of five minutes per vehicle.
Technology that sets a new standard
Neural analysis in VIEWAPP is not an isolated feature — it is an architectural principle. It ensures:
• data reliability,
• stable protection against fraud,
• reduced workload for experts,
• minimized user errors,
• fast and unambiguous results.
This combination of technologies makes VIEWAPP a universal platform. And this universality applies not only to inspection scenarios for any type of object — the same approach is embedded in our neural modules. They learn on diverse data, adapt to specific tasks, and scale without redesigning processes.
As a result, VIEWAPP works equally effectively across industries while maintaining its core principle: data must be collected correctly, verified technically, and protected from manipulation.