We Enable Companies To Be Self-sufficient In Sustainability: Aditi Balbir, Co-founder, EcoRatings
In an interview with ResponsibleUs, Aditi Balbir, Co-founder of EcoRatings, spoke about how generative AI and blockchain algorithms are providing real-time data on all the standards and frameworks needed to follow a sustainable path
EcoRatings is one of the first companies developing foundational generative AI for sustainability. It is a solution that spans industries, sustainability uses cases, frameworks, and geographies. It’s highly scalable, unlike EPRs, which are sector-specific or limited in scope. Do not be confused by the word "Rating" in the name—this solution is creating the foundation for ESG (Environmental, Social, and Governance) compliances, reports, ratings and any other use cases.
In an interview with ResponsibleUs, Aditi Balbir, Co-founder of EcoRatings, spoke about how generative AI and blockchain algorithms are providing real-time data on all the standards and frameworks needed to follow a sustainable path.
Excerpts:
What inspired the creation of EcoRatings AI?
When I was working in sustainability, there was a lot of complexity involved. There are different frameworks, different geographies, different compliances, and different sectors with varying needs. I figured out that there was a real need to simplify the sector and make it more open. What one company is doing isn’t shared with another company, individuals can’t find out about the brands or products they use daily, and countries can’t track companies effectively—so how will they track sustainability?
There were a lot of problems in this space, and we wanted to create something that could easily decode sustainability for companies first, because they are the key stakeholders in this effort.
When you are working on a large-scale project aimed at decoding sustainability across sectors, companies, and countries—even for individuals—we had to take a generative AI approach. A traditional ERP approach wouldn’t have worked, but generative AI provided a solution that could deliver sustainability insights across different industries and organisations.
What challenges did you face while developing the generative AI model for sustainability?
The first challenge was determining what kind of base model we could use. Should we use OpenAI? Should we use LAMA? No existing model was specifically designed for sustainability; they were all very generic in nature.
The second challenge was obtaining a relevant dataset to train the model effectively. We had to gather and curate data carefully to ensure it was applicable to sustainability and met our objectives.
I had a lot of data from my work in sustainability. We gathered relevant data and then learned how to train the LLM from scratch. Eventually, we realized that there was a real need to create our own model because of the inherent challenges in existing models like hallucinations, lack of direct API feeds etc.
From the first year, we decided to use our own infrastructure rather than relying on external ones. We are not a wrapper company—we haven’t built anything on top of an opensource model. Instead, we’ve used APIs to extract data and used our own infrastructure, with our own servers and GPUs.
The problem is that sustainability is a relatively new industry, but generative AI is even newer. We had to figure things out from both angles—what is relevant in sustainability and how to build generative AI solutions. Everything has been learned in-house, and we haven’t outsourced anything.
How does EcoRatings evaluate and rank companies on sustainability, ESG compliance, or ESG parameters?
As we are not a rating company. We are a generative AI company for sustainability. We provide a comprehensive sustainability solution. First, we help enterprises automate their data. We create a GenAI layer so that all their data becomes queryable. Companies can also use our LLM as an external database that allows them to see what their peers are doing, benchmark their data, etc.
Once the data is structured, we also help them automate various sustainability processes—from reporting compliances to ratings from other agencies, life cycle assessments, materiality assessments, ESDD (Environmental and Social Due Diligence), and climate risk analysis. Essentially, we assist companies in achieving any framework within the sustainability domain.
Additionally, we provide real-time monitoring and tracking, allowing companies to assess how their mitigation strategies are working. Many companies have pledged to be net zero by 2030 or 2050, and our tool helps track their progress. Our tool also provides real-time insights into potential issues and red flags, enabling companies to take proactive measures.
It's basically a very intelligent system, and we can do a lot more than this. We've now started creating agents that specialise in specific tasks that need cannot be calculated from internal data alone.
For example, when conducting a supplier assessment, you need to gather information from outside the organization. If you're an agricultural company—say, a rice company—you need to monitor not just internal processes but also your farms and agri assets. For this, we have developed an agent that analyzes satellite imagery.
Does this mean your sustaining model provides everything needed for ESG reporting?
Yes. Companies using our system can generate and submit ESG reports because they have all the required Scope 1, Scope 2, and Scope 3 emissions data. They can even automate the reporting process.
What sources and methodology do the platform use to ensure transparency?
First, every piece of data we provide includes its source and a direct link to the original document. This means that companies using our platform are audit-ready from day one.
Second, for transparency in supply chains, carbon credit issuance, and related areas, instead of relying on human auditors, we use blockchain technology. This ensures secure, verifiable, and tamper-proof data tracking.
Which industries do you cover, and how does the rating system adapt to sector-specific requirements?
Our platform is designed to be industry-agnostic, meaning it can support companies across various sectors. Our system helps companies streamline their sustainability efforts, align with regulatory requirements, and generate relevant ratings or compliance reports efficiently.
For example, if you want to get a rating, we have an algorithm that calculates your score based on your data. We provide insights on your current rating, the gaps you need to address to improve your score, and the templates you need to complete. All of this can be generated directly from our system. The entire process can be fully automated.
How does this platform compare to traditional ESG rating agencies?
The GenAI technologies are a new gen of tech that provide an advantage over traditional ERP companies. One key difference is that traditional ESG rating agencies rely on manual processes, whereas our system is entirely digital.
In traditional ESG assessments, companies must first gather their data manually and then input it into various forms. In contrast, our platform automates the reporting process, making data collection and submission much more efficient.
Can individual consumers use your platform?
No, not yet. Right now, our platform is strictly for businesses – we are a B2B play.
Your experience as a woman working on and developing EcoRatings?
I have been a woman entrepreneur for a long time, and with EcoRatings, I haven’t really faced many challenges because the economy and startup ecosystem have evolved significantly. Today, most startups have at least one woman in the founding team, and there are many women-led companies.
Back in 2012–2014, when I was a woman founder, the landscape was very different. There were only about 10 of us who were women founders in this space and received venture capital funding. While it was challenging, it also had its advantages—we were in the limelight simply because there were so few of us. Now, there are so many unicorns led by women and a growing number of women in startups. It’s a completely different ecosystem today.
More women are realising that entrepreneurship offers a far better career path than traditional jobs. In a job, you have restrictions, you’re confined to a single role, and work tends to be repetitive. But entrepreneurship comes naturally to women—we are already multitaskers, wearing multiple hats, and managing various responsibilities at once. This ability to juggle multiple roles and get results across different functions is a natural fit for running a business.
Entrepreneurship is also a continuous learning process, and I think women genuinely enjoy that. It allows flexibility—you can decide your own schedule, balance family and work, and shape your career in a way that suits you. Of course, entrepreneurs often end up working more than they would in a job, but the autonomy makes a big difference.
That’s why we are seeing more women entering entrepreneurship than ever before.
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