Purpose of this article
Lumi is Scaler's built-in AI assistant that helps summarise, compare, and analyse sustainability data directly within the platform. This article explains how to write effective prompts, request refined outputs, and explore practical use cases for Lumi.
Understanding Lumi's access scope
Lumi operates entirely within Scaler — it analyses and summarises your organisation's existing Scaler data.
- It does not access external data sources or third-party content.
- Its responses are based on the data and metrics available to your user permissions.
- For missing or incomplete data, Lumi's insights may highlight data gaps or trends rather than exact values.
Writing effective prompts
Be specific
The more context you include, the better Lumi can tailor its response. When possible, include:
- Asset or portfolio name
- Time period (e.g. "FY2024" or "last quarter")
- Metric type (e.g.
total_ghg_emissions,energy_consumption)
Examples:
- "Summarise Portfolio Alpha's FY2024 energy use by asset."
- "Compare Scope 1 and Scope 2 emissions for Building A over the last three years."
Lumi automatically interprets data available in Scaler but performs best when you specify the exact scope of your query.
Request a specific output format
You can guide Lumi to present results in a preferred layout.
Examples:
- "List these findings as bullet points."
- "Show this in a 3-column table (asset, total GHG, change vs last year)."
- "Summarise this in a short paragraph for a report."
Structured output requests help Lumi match Scaler's reporting and communication standards.
Refine and follow up
You can ask Lumi to build on previous answers for deeper insights or clarifications.
Examples:
- "Break this down by building."
- "What's driving this trend?"
- "Can you compare these results against targets?"
- "Summarise just the top 5 contributors."
Lumi retains conversation context, allowing progressive refinement within the same session.
Best use cases for Lumi
Lumi performs best when used to summarise or analyse structured data already captured in Scaler. Below are common scenarios where users see the most value:
Category | Example use case |
Portfolio summaries | "Summarise total emissions, energy, and water use for each portfolio." |
Data gap analysis | "Identify missing data points across assets for the current reporting year." |
Benchmarks | "Compare energy intensity across portfolios and flag underperforming assets." |
Regulatory readiness checks | "Summarise how our disclosures align with CSRD, SFDR, and GRESB indicators." |
Tips for consistent results
- Ensure portfolio and asset data are fully up-to-date in the Data Collection Portal before querying Lumi.
- When reviewing multi-year trends, confirm the reporting period selected in the Analytics Portal matches your prompt timeframe.
- Use short, direct phrasing — Lumi interprets clear task-based questions most accurately.
Where to find Lumi
Lumi AI is available from the Home page in the left-hand navigation toolbar. It can also be opened via the Lumi icon at the bottom of the screen from anywhere in the platform.
Additional resources
- Finding help & support — Knowledge Base, Lumi, and contacting support
- Welcome to Scaler: How the platform works — Platform overview and data flow