An energy-transparent, future-proof retrieval engine for climate insights
What is ChatNetZero
Climate AI built for trust, and responsible use
ChatNetZero helps climate professionals use AI with more confidence by grounding answers in verified sources, reducing hallucination risk, and making energy use more transparent.
Why ChatNetZero exists
General-purpose AI tools create three common problems for climate users:
• Uncertainty about source quality
• Uncertainty about whether answers are trustworthy
• Uncertainty about whether AI is being used responsibly
ChatNetZero was built to address those concerns directly with climate-specific retrieval, validated datasets, and energy-aware workflow design.
A guardrail, not a replacement
ChatNetZero is not replacing general-purpose AI tools. It is built as a guardrail for climate professionals and researchers: a place to validate AI responses, spot potential greenwashing, and reduce hallucination risk.
Unlike generic LLMs that mostly quote numbers from written sources, ChatNetZero can calculate directly on validated climate datasets so users receive natively grounded climate analysis.
Climate-Aware Design
We’ve conducted a study to understand the variable energy consumption associated with large language model chatbots and domain-specific designs. Read our study, where we break down energy consumption in various parts of ChatNetZero and compare it to generic tools like ChatGPT and agentic-based designs.
How it Works
There are five key modules that enable ChatNetZero
Verified Sources
Answers based on data verified by the Net Zero Tracker and renowned experts
No Hallucination
State-of-the-art algorithm to rigorously check for and eliminate hallucination
Fine-Tuned Process
Less embellishment, more signal. Answers stay focused on facts rather than filler.
Energy-Aware Design
Wworkflow designed to reduce unnecessary compute and provide an estimated energy cost for every AI use.
Climate Analytics
Native calculation directly on validated climate datasets for advanced climate analysis
Example 1 of 4
Energy Transparent
Estimated energy consumption per query
For the first time among AI tools, we will report the estimated energy consumption for each user query using the approach developed in our research - The Energy Footprint of LLM-Based Environmental Analysis: LLMs and Domain Products. The goal is to make ChatNetZero a climate-and energy-responsible tool for researchers.
Each query will be reported with a detailed breakdown by step, providing a benchmark for designing more energy-efficient AI systems.
Energy consumption data are based on estimates as of January 2026, referencing the methodology from the How Hungry is AI paper
Sample breakdown
Running time (s)Est. energy (Wh)
Entity detect: 0.269 s0.001 Wh
Retrieve: 0.237 s0.001 Wh
Hallucination check: 10.765 s0.028 Wh
LLM inference: 4.074 s0.435 Wh
Entity detect
Retrieve
Hallucination check
LLM inference
Promoting energy-efficient AI design
We are constantly developing algorithmic and architectural best practices to balance performance and energy consumption across AI workflows.
Smart Router. Use a lightweight routing agent to identify the most efficient path for each query, avoiding unnecessary heavy AI reasoning when a faster grounded method can answer just as well.
Caching the thinking process. Save common question types and use cases as reusable reasoning templates, helping us achieve faster, higher-quality answers while using significantly less energy than general-purpose agents.
Algorithmic hallucination check. Use local, CPU-based checks to catch hallucinated content before it reaches the user, reducing the need for extra GPU-heavy verification steps.
Reuse source embedding. Climate documents and datasets are vetted by climate experts and then reused for querying, avoiding repeated source-fetching costs. New documents can also be added or removed individually, which is more energy-efficient than rebuilding a legacy RAG system from scratch.
Optimize response. Use concise, accurate language and avoid unnecessary embellishment so the system does not spend extra energy generating low-value text.
use cases
Fact-Checking
ChatNetZero allows for a range of stakeholders to hold those who pledge net-zero decarbonization goals accountable to their pledges. It will provide a transparent platform for scrutinizing net-zero commitments, thereby nurturing trust and diminishing the risk of greenwashing.
Education & Awareness
ChatNetZero provides a custom-tailored engagement opportunity not possible with existing GPT models for the public to interact with and ask questions about the overall net-zero landscape. Instructors at the secondary and post-secondary educational levels can use ChatNetZero in the classroom to teach students both about climate change and how AI works.
Research
Climate policy and other academic researchers will be able to extract specific information about various entities’ climate commitments and strategies, as well as information on specific net-zero indicators. Researchers could comb through the dataset and conduct their own analyses, but ChatNetZero delivers their answer in seconds, and cites the source if they want to dig deeper.
Benchmarking
Stakeholders can upload sustainability reports, press releases, and other climate policy documents for ChatNetZero to analyze. From these documents, ChatNetZero can benchmark an actor's net-zero pledges against other entities in our database, which includes 4,000+ country, subnational government, and business pledges.
Roadmap
We are building the ecosystem of trusted climate AI
Mapping the future of climate intelligence through specialized tools and scientific integrity.
Official Sources
Verified intelligence from official documents and trusted NGO data.
Report ScoutCity Scout
Climate-Specific AI
LLM applications fine-tuned for climate nuance and policy language.
Domain Workflows
Customized sustainability data extraction and tracking logic.
Research Foundation
Built on scientific integrity and peer-reviewed methodology.
Your Own Climate Chatbot
Use ChatNetZero as a benchmark and template for your own branded AI frontend
Built for organizations that need trusted climate AI
ChatNetZero is engineered on a modular framework specifically tailored for climate-related inquiries. We are building it not only as a public-facing tool, but also as a benchmark and implementation template for organizations that want to deploy their own branded climate AI frontend with grounded answers, domain-aware workflows, and transparent methodology.
Contact us now if you are considering this approach to your own AI use cases, knowledge bases, and audiences.
Send us your inquiry
Requesting a New Feature?
ChatNetZero is actively seeking partnerships with climate change experts and AI specialists to enhance our platform. Your expertise is invaluable to us; it's the cornerstone that enables us to push the boundaries in our mission to harness AI and Natural Language Processing (NLP) for addressing the world's most pressing environmental challenges.
Looking for Partnership on Use Cases?
We're eager to explore how ChatNetZero can address your specific challenges. Let's collaborate to brainstorm new use cases, aiming to leverage our technology for the benefit of communities worldwide.
Funding Opportunities?
Please contact us if you are interested in provide funding to support the initiative.
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