Ticket Manage
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Digital Twin based Asset Management
Plant Audit | Digital Twin based CMMS | Snap-On Advanced Analytics | Forecasting | ROC
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Start a projectOutlived no dwelling denoting in peculiar as he believed. Behaviour excellent mid.
Outlived no dwelling denoting in peculiar as he believed. Behaviour excellent mid.
Outlived no dwelling denoting in peculiar as he believed. Behaviour excellent mid.
At the Core of our Asset Management is Digital Twin AI. We build personalized, digital replicas of everything sensored in your Solar and / or Storage plants. This means hundreds of Data Digital Twins, which in RealTime help you move from reactive to proactive management, built right into our platform to help you effectively optimize your assets while monitoring them.
Improve Generation by 2-4%/ O&M Efficiency by 15% | Personalized Plant Audit | CMMS for Centralized Data, RealTime Monitoring, Reporting, Visualization with Built-In Predictive Analytics | ‘Snap-On’ Digital Twin based Advanced Analytics | Forecast Generation | Your ROC Team
Maximizes capacity and availability, streamlines OEM claims, and provides a BMS System Plant Audit and real-time outage alerts via a CMMS. It includes an extensible platform for automated reports, warranty compliance, OEM LD, and advanced analytics. It easily integrates with existing platforms via API, improving business efficiency.
Apply our actionable intelligence to your data, to maximize financial returns – from every plant under your watch.
360° Personalized Plant Performance Assessment. 5-Day Time to Value. Directly Actionable Revenue Prioritized Tickets address Long-term/Ongoing and Short-term/Pop-up Issues.
1 – Source of Truth for Full Portfolio Visibility. True, Data Driven Decision Making. Improve Generation by 2 – 4% / O&M Costs by 15% while Monitoring.
Our Advanced Analytics seamlessly Snap-On any Monitoring System. ALL the Smart Analytics, integral to our Digital Twin based CMMS.
Intra-Day. Day (s) Ahead. Week (s) Ahead, with > 98.4% accuracy. Optimized database tailored to every required location, with ensemble of multiple weather providers.
We help you remotely track, assess, and resolve issues – enabling you to Optimize Operations
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Sometimes furnished collected add for resources attention. Norland an by minuter solicitude inhabits projection.
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We worked with Quadrical to build a data platform, consolidating our plant data onto a common schema. Quadrical built out the schema with Al capabilities to help 0&M teams to identify and rectify anomalies, prioritised by revenue impact. There are many players who claim capabilities and tools in Artificial Intelligence, but none have the true depth of technical abilities that Quadrical brings to the table.
As we onboarded 25 plants with Quadrical in 45 days, we’ve been impressed with their ability to fully own data quality and connectivity. With advanced Analytics-as-a-Service, we’re already seeing the benefits with insights available for our operations team to identify the plant performance issues and possible breakdowns proactively. I am now confident that this platform has the potential to transform the way we do our operations.
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Demo – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Plant Specs & Operations Details – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Plant Audit – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Proof of Concept – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Product Deployment – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Further intelligent improvement – The Quadrical team has been building Digital Twin Models for ~ 3 years – making them, by far, the most advanced in solar.
Plant Audit with Digital Twin AI, for Robust Metric and Benchmarking
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