
Labs don't need another LIMS. They need a complete operating system for modern lab operations - and that's QBench, reshaping everything from order placement through sample processing to automated reporting.
Simple. Powerful. Adaptable. Where other LIMS force labs into rigid structures built on heavy custom code and vendor dependency, QBench moves with you. It bends. It adapts. Your processes evolve, and QBench evolves too.
It adapts to your secret sauce. Every lab has its own workflow, its own rhythm, and QBench respects that with unmatched configurability. You shape the workflows. You define the data fields. You stitch together the automations. QBench's former bench scientists work alongside you throughout, offering expert guidance and workflow suggestions.
It automates the tedious work. File parsers and a robust API connect QBench to the instruments and systems you already run, so data flows on its own. No manual entry. No transcription errors.
It unifies everything in one platform. Real-time inventory. A dedicated portal giving clients instant access to results. Built-in analytics. A QMS module that keeps you audit-ready, always.
QBench helps labs work smarter - cloud-based, secure, and always evolving, like the science it supports.
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Codemagic’s macOS build environments facilitate the smooth creation of hybrid applications, bolstered by an extensive array of preinstalled software. You can efficiently configure your Cordova Android and iOS application builds and workflows through a single codemagic.yaml file. To maintain the performance of your Android and iOS applications, Codemagic provides automated testing on simulators, emulators, and actual devices, ensuring you receive prompt feedback on your build outcomes. Integration with the Apple Developer Portal streamlines iOS code signing, enabling seamless deployment to App Store Connect and Google Play. Similarly, you can also set up your React Native app builds and workflows in one straightforward codemagic.yaml file. With multiple versions of Xcode, Android SDK, and npm preinstalled, Codemagic’s macOS build machines are designed for effortless Android and iOS builds. Moreover, Codemagic simplifies the automation of testing for your React Native applications across a variety of testing platforms. This comprehensive approach not only boosts productivity but also enhances the overall development experience.
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Google Cloud Vision AI
Harness the power of AutoML Vision or leverage pre-trained Vision API models to extract meaningful insights from images stored in the cloud or at the network's edge, allowing for emotion detection, text interpretation, and much more. Google Cloud presents two advanced computer vision solutions that utilize machine learning to provide top-notch prediction accuracy for image analysis. You can streamline the creation of bespoke machine learning models by simply uploading your images, using AutoML Vision's intuitive graphical interface to train these models, and fine-tuning them for optimal performance in terms of accuracy, latency, and size. Once perfected, these models can be seamlessly exported for use in cloud applications or on various edge devices. Additionally, Google Cloud’s Vision API grants access to robust pre-trained machine learning models via REST and RPC APIs. You can easily assign labels to images, categorize them into millions of pre-existing classifications, identify objects and faces, interpret both printed and handwritten text, and enhance your image catalog with rich metadata for deeper insights. This combination of tools not only simplifies the image analysis process but also empowers businesses to make data-driven decisions more effectively.
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VisionTrack
VisionTrack is an innovative video telematics platform that utilizes artificial intelligence to merge interconnected cameras, live fleet tracking, and sophisticated analytics, aiming to enhance road safety, assess driver conduct, and minimize operational risks for organizations. By integrating smart dashcams, mobile digital video recorders (MDVRs), and AI-powered video evaluation, it efficiently captures and transmits vital footage and vehicle information immediately following accidents, near misses, or instances of reckless driving, providing fleet managers with comprehensive context necessary for incident verification and efficient claims processing. The award-winning IoT platform, Autonomise.ai, further processes and analyzes real-time data from an extensive array of connected devices, yielding actionable insights that improve driver performance, protect against fraudulent claims, uphold duty of care, and ensure adherence to safety regulations. As a result, organizations can significantly boost their operational efficiency and safety protocols, leading to overall improvements in fleet management.
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