Purpose of this article
Lumi is Scaler’s built-in AI assistant that helps summarize, compare, and analyze sustainability data directly within the Homepage and throughout 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 analyzes and summarizes your organization’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:
- “Summarize 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).”
- “Summarize 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?”
- “Summarize 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 summarize or analyze structured data already captured in Scaler. Below are common scenarios where users see the most value:
Category | Example Use Case |
Portfolio Summaries | “Summarize 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 | “Summarize 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 It
Navigation: Homepage (left-hand navigation)
Lumi AI is available on the Homepage. It can also be opened via the Lumi icon in the bottom left.