Across the enterprise, AI agents are changing how teams work with data. People are beginning to use AI agents to help them analyze large data sets, surface patterns, and complete tasks faster. In many cases, the expectation is no longer just to view data, but to interact with it: ask follow-up questions, refine assumptions, generate outputs, and move from curiosity to insight in the flow of work.
Carbon data is no exception.
As climate programs mature, sustainability, finance, and reporting teams need more than visibility into emissions totals. They need to understand what is driving changes in the data, compare performance across business units and time periods, test assumptions, investigate anomalies, and respond quickly to stakeholder questions. Those questions do not always fit neatly into a predefined dashboard or standard report.
That is why we are excited to introduce Persefoni Analytics Agent, a new agentic feature embedded in the Persefoni platform that gives teams a faster, more flexible way to interact with emissions data while staying anchored to the trusted system of record they already use for carbon accounting.
A new way to work with your emissions data
Analytics Agent helps customers ask questions, generate analysis, and uncover insights directly in the platform, using emissions data from their CO2e Activity Ledger – no exports needed.
Using plain-language prompts, teams can explore their footprint, generate tailored charts and tables, and pull in additional ledger attributes to support more specific analysis. Instead of being limited to default views, users can ask more targeted questions and quickly build the analysis needed for the moment.
For example, teams may want to investigate year-over-year changes, compare emissions across business units or facilities, examine activity-level drivers, or better understand what is contributing to movement in their footprint. Analytics Agent makes it easier to move from a question to a useful analytical output without needing to start from a static dashboard or manual spreadsheet workflow.
Key capabilities that help you take your data further
Analytics Agent is designed to help customers get more analytical value from the emissions data already managed in Persefoni.
Core capabilities include:
Ask your agent questions in plain language
Ask questions about your emissions data in natural language to quickly investigate trends, anomalies, or specific records. No need to manually filter dashboards or build pivot tables.
Tailored charts and tables
Generate visual outputs and structured views that support deeper, more custom analysis.
Refine analysis through follow-up prompts
Ask the agent to sort, reformat, compare, visualize, or explain results as your questions evolve.
Analyze ledger-level attributes
Pull in additional attributes from the CO2e Activity Ledger to create more specific cuts of the data.
Faster path to insight
Move from question to analysis in minutes (not weeks), making it easier to support dynamic business, reporting, and stakeholder needs.
Together, these capabilities put more analytical power directly in the hands of the teams working closest to emissions data.
Built with security, governance, and precision in mind
For AI-assisted analysis to be useful in carbon accounting, it needs to be grounded in trusted data and designed with the right controls from the start.
Persefoni Analytics Agent helps companies uncover insights from emissions data in the CO₂e Activity Ledger, using the same activity data, calculated emissions, and audit-supporting foundation already managed in the Persefoni platform.
Security was a core design priority from the beginning. Analytics Agent runs through Snowflake, where customer data already resides, helping keep data within the customer environment. The agent is only able to query the data it has permission to access, and customer data is not used to train models or other customers’ experiences.
Accuracy and precision are equally important. Analytics Agent draws from Persefoni-calculated emissions and ledger-level attributes, so outputs are grounded in platform data rather than generic AI responses. As with any AI-assisted workflow, results should be reviewed before use in formal reporting, especially where accuracy is critical.
To support quality over time, Persefoni also consistently tests the AI models across a growing set of scenarios, evaluating areas like response accuracy, speed, consistency, and performance before updates are deployed.
The result is a more powerful way to work with carbon data: one that helps teams explore beyond standard views, uncover decision-useful insights, and respond more quickly to the needs of the business while staying anchored to trusted emissions data.
Bringing the agentic AI experience into carbon accounting
Analytics Agent brings the agentic AI experience into carbon accounting: not as a standalone chatbot, but as a trusted analytical layer connected directly to the emissions data foundation.
By helping teams ask better questions, generate analysis faster, and explore emissions data more dynamically, Analytics Agent makes it easier to turn trusted carbon data into decision-useful insight.
Join our webinar on May 14 for a live walkthrough of Analytics Agent and see how Persefoni customers can prompt the agent to analyze emissions data, generate tailored charts and tables, and explore insights directly from the CO2e Activity Ledger.
To learn more about how Analytics Agent can support your organization’s carbon accounting needs, we’re happy to connect you with one of our climate experts.
Frequently Asked Questions (FAQs)
Does my data leave the Persefoni platform when I use Analytics Agent?
No. Analytics Agent runs on top of your existing data environment. Your emissions data remains within your controlled infrastructure (Snowflake), and queries are executed within that environment.
Is my data used to train AI models?
No. Your data is not used to train shared or external models. The agent interprets your data structure (tables, columns) to generate queries.
Can other customers access or query my data?
No. Access is restricted at the data layer. The agent can only query data within your environment and cannot access data from other customers.
How is this safer than using external AI tools?
Analytics Agent operates within your governed data environment and respects existing access controls. This avoids the risks associated with exporting sensitive data into external tools or “shadow AI” workflows.
How accurate are the results from Analytics Agent?
Outputs are grounded in your CO₂e Activity Ledger and the Agent uses the same underlying activity data and emissions calculations as the rest of the Persefoni platform. That means outputs reflect your system of record, not approximations or generic datasets.
How does Persefoni prevent regressions?
New updates are validated against existing test scenarios to confirm that previously working queries continue to return correct and consistent results. This helps maintain reliability as the product evolves.
Does the agent “estimate” emissions?
No. The agent does not generate new emissions calculations. It analyzes the emissions data already calculated within Persefoni using established methodologies.
What impacts the quality of insights?
The biggest factor is data granularity. The more detailed and well-structured your underlying data (e.g. supplier-level, activity-level), the more precise and useful the analysis will be.
Can I use this for executive reporting?
Yes. You can generate summary tables, charts, and concise insights that can be used to support leadership or board-level reporting.
