--- title: "Sustainability Intelligence | Spirefly" description: "Sustainability Intelligence brings the field's knowledge together with your own data, so a small team can move fast and defend every answer." url: "https://www.spirefly.com/act/sustainability-intelligence/" type: marketing license: proprietary --- # Magnify your impact with sustainability intelligence Bring the field's knowledge together with your own data and goals, so a small team can move with the confidence of a big one. ## The problem: more guidance than any team can navigate > “We keep producing more and more guidance, but our problem isn't a lack of information; it's the human capacity to navigate it.” > — Nadine McCormick, WBCSD **The field produces more frameworks every year** Frameworks, guidance documents, methodology updates, peer reports. Keeping up is a job in itself, and you are never quite sure whether the version you built on last quarter still holds. **Generic AI leaves the verifying to you** A general-purpose assistant answers in seconds, and then the checking starts: can I trust this source, is it current, does it apply to my sector? Verifying information from AI is time-consuming work. **Guidance in one tool, your data in another** A framework rule only becomes a decision once you check it against your own materials, suppliers, and jurisdictions. That context sits in your sustainability data, the guidance sits in a copilot or a PDF, and today you are the connection between the two. ## Three kinds of knowledge, in one system Sustainability Intelligence is what emerges when three kinds of knowledge work together. Each exists somewhere today, in a spreadsheet, a PDF, or someone's inbox. What is missing is the connection. **Your company** Your targets, your material topics, and the initiatives you already have in motion. **Sustainability expertise** Frameworks and their methodology, plus 1,000+ peer sustainability reports. **Your data** Your products, your suppliers, and your actual purchase volumes. Answering a real question needs all three at once, and that connection is what makes the work fast. ## How it works ### Your context, carried into every conversation Upload your sustainability report, describe your goals and industry. The system builds a company profile it carries into every conversation: your targets, your material topics, your current initiatives. It answers in your context, and gets proactive over time, surfacing what changed since last year and flagging a finding that connects to a goal you set months ago. ### What the field has learned, at hand Frameworks and their methodology (SBTN, TNFD, GHG Protocol, CSRD, EUDR), the implementation guides behind them, and 1,000+ peer sustainability reports across food, retail, fashion, and manufacturing. Reference a threshold and it cites the source. Design a nature policy and see how leading companies structured theirs. Every draft starts from what the field has already learned. ### Your footprint, down to the supplier The intelligence layer works on your products, your materials, your suppliers, and your actual purchase volumes. That is sensitive commercial data, so it stays in a private environment that is yours alone and is never used to train the model. You work with it in plain language. Ask a question and get the driver, the breakdown, and a chart of your own data back, with no formulas to write. ## Built to speed up your thinking **Review before you commit** When an output goes into a board deck, a filing, or a public commitment, human review is expected. You check specific claims against traceable sources. **Know where the boundary is** The knowledge base covers what frameworks require and how to apply them. For a specific legal question about a contract or jurisdiction you need a lawyer, and the system tells you when you are there. **Use gaps as a guide** If your footprint data is incomplete, the system surfaces where the gaps are and which ones matter most, so you know where better data would sharpen the picture. **Follow uncertainty signals** When a finding rests on a model estimate, the system says so. Explicit uncertainty markers tell you where to push for confirmation before going public. ## Active from your first measurement to your final disclosure **Understanding what a finding means to you** Ask what 82% of water use in high-risk basins means for a retailer like you, and get the answer in the same conversation. **Drafting a strategy, grounded in data and peer practice** It grounds your draft targets in framework requirements and peer practice, so they hold up to management. **Preparing for disclosure** It checks your language against framework requirements and flags where a claim outruns the data. ## What customers say > "With other AI tools I was really slow because I kept doubting the sources. With Spirefly it was much faster, because we don't have to be a little paranoid about whether the information is reliable. It saves a lot of mental energy." > — Julien Gautier, Norsys > "I presented my strategy to management with confidence. My strategy is now rooted in trusted sources and it's specific, actionable, and defensible." > — Zsuzsa Kozma, CSR Director ## Ready to see the intelligence layer? Book a demo and we'll show you how frameworks, methodology, and 1,000+ peer reports work in the Workbench. ## Frequently asked questions **What is sustainability intelligence?** Sustainability intelligence is software that answers what your sustainability data means and what to do about it. Spirefly's intelligence layer combines knowledge of your company, knowledge of the field (frameworks, methodology, and peer reports), and knowledge of your own footprint, so a small team can produce analysis it can cite and defend. **How is this different from just asking ChatGPT about my sustainability data?** Three differences matter in practice. The knowledge base is curated for sustainability, so answers are consistent and citable. The system works on your actual data. And everything it produces is traceable: you can see what data it drew on and what methodology it applied. When someone challenges a number in a board meeting, you have an answer. **What counts as teaching the system about my company, and how much work is that?** A single session. You upload your most recent sustainability report, or describe your goals verbally, confirm the key targets and material topics, and the system has what it needs. Later sessions build on the same profile, so you do not re-brief it. As your data accumulates across measurement cycles, the context gets richer and the proactive signals more specific. **We don't have a complete footprint yet. Can we still use Sustainability Intelligence?** Yes. The intelligence layer works with whatever data you have. Partial data produces analysis with flagged gaps, which is useful in itself: you see where the unknowns are and which gaps matter most. Many teams use it to decide where to prioritise data collection before their next measurement run. **What happens to our data, and is it used to train the model?** No. Your footprint figures, supplier information, and uploaded documents stay yours and are not used to train or improve the underlying model. You work in a private environment, and what the system learns about your company stays within your account. **Can the system help us compare ourselves to peers in our sector?** For qualitative benchmarking, yes, today. The knowledge base includes 1,000+ peer sustainability reports, so you can see how others structured their nature policies, what language they use in disclosures, and which commitments have become standard. Quantitative benchmarking against a sector average is still in development. **Can we export what the system produces?** Yes. Analyses, dashboards, and documents produced in the Workbench can be exported and shared.