About
ReliVision is Relimetrics' flagship industrial AI inspection platform designed to transform quality control and automation in manufacturing. Unlike traditional machine vision solutions that require specialized AI knowledge for deployment and maintenance, ReliVision is built for operators and engineers with no coding background. Users can annotate defects, train and compare AI models, monitor performance, and retrain systems on demand—all through an intuitive graphical interface. The platform addresses key limitations of legacy industrial AI: inability to handle high production variability, difficulty of maintenance, and lack of scalability across facilities. ReliVision continuously learns from shop-floor feedback, adapts to changing production conditions, and enables real-time sharing of data and AI models across multiple plants and inspection points. A standout feature is its on-premise generative AI module, which creates realistic synthetic defect variations from limited validated samples, allowing inspection models to be prepared and updated ahead of product or process changes—keeping all data local and secure. Key capabilities include a collaborative data curation module with graphical annotation tools, a pre-built AI model library, full control over training parameters, GenAI-powered synthetic data generation, and shop-floor feedback-driven continuous learning. The hardware-agnostic architecture integrates with diverse industrial camera and sensor setups, making it suitable for a wide range of manufacturing sectors including electronics, automotive, and consumer goods.
Key Features
- No-Code AI Model Training: Operators and engineers without AI expertise can build, train, test, and retrain custom visual inspection models using a guided graphical interface with single-click training.
- Collaborative Data Curation: Intuitive annotation tools let teams mark defects and objects, define labels, merge annotations, and manage training dataset quality—all in one place with industry-standard import/export.
- On-Premise Generative AI for Synthetic Data: Generates realistic synthetic defect variations from limited real samples to prepare and update inspection models before production changes occur, with all data kept local and secure.
- Shop-Floor Feedback-Driven Learning: Turns shop-floor operators into AI trainers by capturing real-time production feedback to continuously improve and adapt AI models to changing manufacturing conditions.
- Multi-Plant Model Sharing: Enables real-time sharing of training data and AI models across multiple plants and inspection points, ensuring consistent quality standards and accelerating deployment at scale.
Use Cases
- Automated visual defect detection on manufacturing production lines without requiring an on-site AI specialist.
- Cross-plant quality standardization by sharing trained AI inspection models and annotated datasets across multiple facilities in real time.
- Rapid adaptation of inspection models when new product variants or packaging changes are introduced, using synthetic data generation to minimize downtime.
- Empowering shop-floor operators to continuously improve AI model accuracy by flagging incorrect detections as real-time training feedback.
- Replacing legacy rule-based machine vision systems with adaptive AI inspection that handles high production variability in automotive, electronics, or consumer goods manufacturing.
Pros
- Truly No-Code for Industrial Teams: Designed specifically so operators and engineers without AI backgrounds can independently manage the full AI inspection lifecycle, reducing reliance on specialized data scientists.
- On-Premise & Private by Design: Generative AI and all data processing run locally, making it suitable for manufacturers with strict data security and compliance requirements.
- Handles High Production Variability: Continuous shop-floor learning and synthetic data generation allow models to adapt to frequent product or process changes without starting from scratch.
- Hardware-Agnostic Architecture: Works with diverse industrial cameras and sensor setups, minimizing infrastructure lock-in and lowering the barrier to adoption across different facilities.
Cons
- Enterprise-Focused Pricing: Designed for industrial manufacturers, the platform is likely cost-prohibitive for small businesses or individual users, with licensing details not publicly disclosed.
- Steep Initial Setup for Complex Lines: While no-code for daily use, initial deployment across multiple plants and inspection points may still require significant planning and integration effort.
- Limited to Industrial Use Cases: The platform is purpose-built for manufacturing quality inspection and may not be suitable for general-purpose computer vision or non-industrial AI applications.
Frequently Asked Questions
Do I need AI or coding expertise to use ReliVision?
No. ReliVision is specifically designed so that engineers and shop-floor operators without AI or coding knowledge can build, train, deploy, and maintain AI inspection applications entirely on their own.
Is my production data kept private and secure?
Yes. ReliVision's generative AI and all data processing run on-premise, meaning your production data never leaves your facility. This makes it suitable for manufacturers with strict data security and compliance requirements.
How does ReliVision handle changes in my production line or product variants?
ReliVision uses shop-floor feedback-driven learning to continuously retrain and adapt models to new conditions. Its on-premise GenAI module also generates synthetic defect variations from limited samples, allowing models to be updated ahead of planned production changes.
Can ReliVision be used across multiple plants or facilities?
Yes. The platform enables real-time sharing of training data and AI models across multiple plants and inspection points, making it designed for enterprise-scale adoption and consistent quality control organization-wide.
What cameras and hardware does ReliVision support?
ReliVision is hardware-agnostic, meaning it is compatible with a wide range of industrial cameras and sensor setups. It does not lock users into specific hardware vendors, giving manufacturers flexibility in their infrastructure choices.
