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Description
Arvist AI is an innovative computer vision platform designed to aid warehouses globally in enhancing shipment quality, bolstering worker safety, and ensuring compliance, all by leveraging AI technology that seamlessly integrates with existing security cameras. Its camera-agnostic feature enables it to work with any visual input device, making it highly adaptable and capable of scaling efficiently across various warehouse locations. By automating the inspection process, Arvist significantly lowers OS&D claims and reduces the costs associated with inspection labor, all while providing valuable visual documentation for resolving disputes. The platform streamlines quality control tasks by identifying labeling mistakes, confirming expiration dates, and detecting incorrect or damaged shipments. Additionally, Arvist AI improves safety and compliance by actively monitoring regulations related to bonded warehouses and customs, preventing collisions involving forklifts and vehicles, ensuring food safety standards are met, and verifying employee adherence to ergonomic practices and PPE guidelines. With a rapid installation process, Arvist offers essential operational visibility and increased safety from the outset, while also adapting to the unique requirements of each operation through its ongoing learning capabilities. This adaptability ensures that warehouses can continuously optimize their processes and maintain high standards in a changing environment.
Description
Effectively managing areas that are regulated by Good Manufacturing Practices (GMP) necessitates a comprehensive strategy that focuses on the key elements of facility management, personnel oversight, and microbial control. DeepEyes’ video-based AI solutions excel in identifying compliance-related discrepancies and potential contamination risks, effectively bridging the gaps that even thorough training and diligent supervision may not fully address. These intelligent systems automate the surveillance process, providing real-time alerts for any deviations from established GMP protocols, which ensures ongoing quality assurance that aligns seamlessly with the manufacturing workflow. While operator training is important, it cannot completely eliminate the possibility of mistakes or oversights, making continual monitoring essential to safeguard against product loss, waste management challenges, operational downtime, and safety hazards. Ultimately, integrating advanced AI technology into GMP-regulated environments enhances overall operational security and efficiency.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Arvist AI
Founded
2021
Country
United States
Website
arvist.ai/
Vendor Details
Company Name
DeepEyes
Founded
2018
Country
Germany
Website
www.deepeyes.co
Product Features
Computer Vision
Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration
Product Features
Computer Vision
Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration
Quality Management
Audit Management
Complaint Management
Compliance Management
Corrective and Preventive Actions (CAPA)
Defect Tracking
Document Control
Equipment Management
ISO Standards Management
Maintenance Management
Risk Management
Supplier Quality Control
Training Management
