Clir Portfolio

An AI based asset performance management (APM) platform for asset owners.

Clir Portfolio unifies portfolio-wide data to clearly surface performance drivers, explain variance, and identify actionable intelligence that increase portfolio value.

Turn insights into action

300+ GW operational data

Clir’s proprietary data includes 150+ GW of wind, 100+ GW of solar and 100+ BESS assets. Owners gain unparalleled market intelligence to help gain context and inform strategic decision making.

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Advanced software and AI

Built on a renewable energy–specific data model and advanced digital twins, Clir’s software applies machine learning, instance-based learning, and the latest large language models to extract insight, explain performance, and surface action across renewable portfolios. A continuously evolving technology stack ensures long-term adaptability and future-proof value for customers.

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Automate reporting using Clir’s AI across renewable energy assets.

Asset owners often struggle with manual, inconsistent reporting and limited visibility into what’s driving portfolio performance. This increases reliance on consultants and makes it harder to confidently explain results, allocate budgets, and manage risk.

Clir automates portfolio reporting using a renewables-specific data model and forensic performance intelligence, delivering clear, defensible insight that helps asset owners improve decision-making and increase portfolio value.

Reduce reliance on consultants and manual reporting.
Quickly identify underperforming assets and service issues.
Improve budget allocation and OPEX efficiency.
Increase confidence in board and investor reporting.
Minimize financial risk and uncertainty.

Monthly production against previous years chart

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Proactively monitor portfolio performance to improve asset value

Owners are overwhelmed by inconsistent and vast amounts of SCADA data and lack the tools to turn it into timely, actionable insight. Inconsistent data, slow root-cause analysis, and delayed issue detection lead to lost energy, higher OPEX, and pressure from leadership to explain underperformance after the fact.

Clir’s AI enables portfolio-wide performance monitoring turning messy SCADA data into clean standardized data to enable anomaly detection, and industry benchmarking. Clir helps teams know where to look, what to look for and how to fix issues quickly resulting in recovered lost energy and improved business outcomes.

Detect underperformance and anomalies before they become major issues.
Benchmark assets and units consistently across the portfolio to know where the real issues and opportunities are.
Improve availability and uptime with proactive monitoring.
Reduce time spent cleaning SCADA data and manual analysis.
Increase confidence when explaining performance to leadership.

Reconcile contractual availability with confidence

Asset owners often rely on OEM-provided contractual availability calculations that are slow to validate, difficult to trust, and misaligned with SCADA data. Manual log reviews are time-consuming and inconsistent, creating risk of inflated bonus payments, missed liquidated damage claims, and limited confidence when challenging service providers.

Clir’s AI enables contractual availability reconciliation by standardizing SCADA data, event logs, and contract logic into a transparent, auditable framework. Asset managers can interrogate availability calculations, identify mislabeled or missing data, and generate dispute-ready reports, giving teams confidence to independently validate OEM claims and protect portfolio value.

Independently validate OEM contractual availability calculations
Identify mislabeled downtime and data gaps that inflate CA figures
Reduce bonus overpayments and recover liquidated damages
Generate audit- and dispute-ready CA reports faster
Eliminate manual, contract-by-contract log reviews
Increase confidence when challenging service providers and reporting to leadership

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Reconcile Contractual Availability Chart

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Reconcile budgets with actual performance to restore financial confidence

Asset owners frequently miss budgets because forecasts are based on outdated pre-construction assumptions that no longer reflect how assets actually perform. This creates uncertainty in cash flow projections, weakens valuations, and erodes confidence with boards, investors, and lenders when targets are repeatedly missed.

Clir’s AI enables budget reconciliation using real operating data standardized across the portfolio. By reforecasting long-term energy yield based on historical performance, loss drivers, and scenario analysis, Clir delivers credible, explainable forecasts that align budgets, valuations, and expectations reducing surprises and strengthening financial decision-making.