Notes from the Second GCA Impact Accelerator in New York City

Wadhwani AI was among the five Global Change Award winners attending the second GCA impact accelerator week in New York City in October 2022.
Wadhwani AI was among the five Global Change Award winners attending the second GCA impact accelerator week in New York City in October 2022.

In April 2022, the H&M Foundation selected Wadhwani AI’s CottonAce solution as one of the five winners of their Global Change Award (GCA) for 2022. The award recognises groundbreaking innovations from across the globe that are making a positive impact in the world of sustainability, textiles, and fashion. Through our AI-powered CottonAce smartphone app, our team at Wadhwani AI has helped thousands of cotton farmers across India deal with pest attacks through timely, accurate, and scientific pest management advisories. We are honoured to be a part of the prestigious GCA ecosystem.

The five organisations in the GCA 2022 cohort—Wadhwani AI, Rubi Labs, SaltyCo, Amino Tech, and Biorestore—will share in a million euro grant from the H&M Foundation. The winners have already participated in two impact accelerator programs this year, conducted by the H&M Foundation, Accenture, The Mills Fabrica, KTH, and other experts, aimed at helping organisations to unlock value, learn new go-to-market strategies, and gain collaboration opportunities with leading voices in the fashion, innovation, and strategy space.

After attending the first impact accelerator week in Stockholm in June 2022, I represented Wadhwani AI at the second accelerator last month in New York City. The accelerator week in New York City provided an opportunity to further refine our ideas, brainstorm about ways in which we can multiply the impact of our work, and collaborate with the GCA network to scale our solution.

Read on for my impressions from a highly productive week.

Day 1: Business Model Innovation

It was wonderful to reconnect with fellow winners of the GCA and our friends from the H&M Foundation, Accenture, and The Mills Fabrica at Accenture’s One Manhattan West office. While enjoying the exquisite view of the famous New York skyline from the 61st floor, we took part in business model innovation exercises, during which all the teams brainstormed about how our respective solutions can create more value for all stakeholders.

The highlight of Day 1 was the business canvas exercise conducted by Accenture. It helped us map our ecosystem and better understand how we can further increase the scale of our impact by meeting the needs of customers, suppliers, governments, and most importantly, the last-mile cotton farmers we intend to help through CottonAce.

Day 2: Expert Connections

The activities on Day 2 focused on learning from the experts. Caroline Brown and Julia Viner from Closed Loop Partners, a New York-based firm that invests in startups contributing to the circular economy, took us through the startup funding journey and gave tips on how to perfect our pitches.

This was followed by a carefully crafted 360-degree value framework exercise conducted by Sara Rahiminejad and My Ewrelius Ryde of Accenture. It was a self-reflection exercise designed to discover possible paths with our innovations, and helped us refine and readjust our priorities and strategies.

Later in the day, we heard from industry experts Jill Standish (Global Retail Lead, Accenture) and Cara Smyth (Responsible ESG Retail Lead, Accenture) about trends and updates in the sustainability space and how innovative startups, such as those in the GCA cohort, could integrate into the larger ecosystem.

The day ended with ‘speed dating’ sessions with experts Jill Standish, Cara Smyth, Frank Zambrelli, Anastasia Marceau, and Sara Johnson. With years of diverse experience across organisations and industries, they shared valuable insights with each GCA winner individually and offered opportunities to connect with various leaders and organisations in their network across the world.

Day 3: Factory and Store Visits

Day 3 was all about having our boots on the ground and gaining practical experience. After quick pitch training sessions conducted by The Mills Fabrica, our group headed to the Eileen Fisher Tiny Factory on the outskirts of New York to witness their gigantic operation of making circular garments a reality. Carmeen Gama (Director of Circular Designs, Eileen Fisher) took us through their incredible process of recycling textiles and contributing to a more sustainable world.

The Eileen Fisher Factory visit was followed by visits to retail stores around New York to get inspired by their stories of weaving together successful business models, sustainability, and technology.

Our CottonAce pitch garnered immense appreciation and interest, with a lot of brands, textile houses, and investment funds interested in knowing more and keen to connect us to their partners in India and abroad.

Day 4: The Planet Positive Perspectives Event

This was the marquee moment that all GCA-winning teams had prepared and waited for. The Planet Positive Perspectives event enabled GCA winning organisations to showcase their solutions and products to an audience of 150+ influential individuals representing some of the biggest brands and investors in the world. GCA winners got an opportunity to pitch their ideas to the esteemed audience and also demo their solutions. Our CottonAce pitch garnered immense appreciation and interest, with a lot of brands, textile houses, and investment funds interested in knowing more and keen to connect us to their partners in India and abroad. 

Throughout the rest of the day, we heard from experts through panels and keynotes. Senior executives from Accenture, Closed Loop Partners, Apparel Impact Institute, ISKO, and Atlante Capital, among others, enriched the audience with their industry insights.

Day 5: Production and Support

We started off our last day at New York University to meet Miguel Modestino, Director at the Sustainable Engineering Institute, and member of Sunthetics, a former GCA winner. It was fascinating to witness the work being done by the University’s startup labs and understand the ways in which the innovation ecosystem is supported by academia.

During the final session of the Accelerator Week, the teams gathered at the H&M Foundation office to acquire critical insights into H&M from Jenny Cao-Wu, Kajta Ahola, Joey Peritore, and Randi Marshall, who shared perspectives on sales, public policy, and data analytics.

Being a part of the GCA cohort has unlocked important learnings and provided us with a platform to interact with global experts across the board.

Key Takeaways

We need to do more. Faster.
GCA winners, past and present, validate that there are numerous startups striving towards making this planet more sustainable. The future is promising. However, with massive changes that climate change has brought about already, all of us have the responsibility to scale our solutions and create a profound impact.

It is possible to build large-scale planet-positive businesses that are profitable.
During our Eileen Fisher factory visit, we witnessed their garment restoration processes end-to-end and also understood their innovative business model which rakes in millions of dollars in revenue. Interactions with experts and visits to local stores in New York reaffirmed that revenue and sustainability can go hand-in-hand.

No dearth of funding for innovative solutions.
Top investors are eager to fund innovative ideas that involve leveraging advanced technologies to mitigate and reverse the effects of climate change. Big corporations in fashion such as H&M are leading the way through the Global Change Award, Green Investments, and various other initiatives, thereby contributing to a planet-positive world.

We are thrilled to be a part of the Global Change Award community and grateful to the H&M Foundation for conducting these impact accelerator weeks in Stockholm and New York City, along with their partners Accenture, KTH, and The Mills Fabrica. Being a part of the GCA cohort has unlocked important learnings and provided us with a platform to interact with global experts across the board.

If you have an innovative idea, you too could become a part of this community. The application cycle for the Global Change Awards 2023 is now open. If you are working on an idea that will help contribute to taking sustainability forward, please click here to apply before December 8, 2022.

ML Engineer


An ML Engineer at Wadhwani AI will be responsible for building robust machine learning solutions to problems of societal importance; usually under the guidance of senior ML scientists, and in collaboration with dedicated software engineers. To our partners, a Wadhwani AI solution is generally a decision making tool that requires some piece of data to engage. It will be your responsibility to ensure that the information provided using that piece of data is sound. This not only requires robust learned models, but pipelines over which those models can be built, tweaked, tested, and monitored. The following subsections provide details from the perspective of solution design:

Early stage of proof of concept (PoC)

  • Setup and structure code bases that support an interactive ML experimentation process, as well as quick initial deployments
  • Develop and maintain toolsets and processes for ensuring the reproducibility of results
  • Code reviews with other technical team members at various stages of the PoC
  • Develop, extend, adopt a reliable, colab-like environment for ML

Late PoC

This is early to mid-stage of AI product development

  • Develop ETL pipelines. These can also be shared and/or owned by data engineers
  • Setup and maintain feature stores, databases, and data catalogs. Ensuring data veracity and lineage of on-demand pulls
  • Develop and support model health metrics

Post PoC

Responsibilities during production deployment

  • Develop and support A/B testing. Setup continuous integration and development (CI/CD) processes and pipelines for models
  • Develop and support continuous model monitoring
  • Define and publish service-level agreements (SLAs) for model serving. Such agreements include model latency, throughput, and reliability
  • L1/L2/L3 support for model debugging
  • Develop and support model serving environments
  • Model compression and distillation

We realize this list is broad and extensive. While the ideal candidate has some exposure to each of these topics, we also envision great candidates being experts at some subset. If either of those cases happens to be you, please apply.


Master’s degree or above in a STEM field. Several years of experience getting their hands dirty applying their craft.


  • Expert level Python programmer
  • Hands-on experience with Python libraries
    • Popular neural network libraries
    • Popular data science libraries (Pandas, numpy)
  • Knowledge of systems-level programming. Under the hood knowledge of C or C++
  • Experience and knowledge of various tools that fit into the model building pipeline. There are several – you should be able to speak to the pluses and minuses of a variety of tools given some challenge within the ML development pipeline
  • Database concepts; SQL
  • Experience with cloud platforms is a plus

ML Scientist


As an ML Scientist at Wadhwani AI, you will be responsible for building robust machine learning solutions to problems of societal importance, usually under the guidance of senior ML scientists. You will participate in translating a problem in the social sector to a well-defined AI problem, in the development and execution of algorithms and solutions to the problem, in the successful and scaled deployment of the AI solution, and in defining appropriate metrics to evaluate the effectiveness of the deployed solution.

In order to apply machine learning for social good, you will need to understand user challenges and their context, curate and transform data, train and validate models, run simulations, and broadly derive insights from data. In doing so, you will work in cross-functional teams spanning ML modeling, engineering, product, and domain experts. You will also interface with social sector organizations as appropriate.  


Associate ML scientists will have a strong academic background in a quantitative field (see below) at the Bachelor’s or Master’s level, with project experience in applied machine learning. They will possess demonstrable skills in coding, data mining and analysis, and building and implementing ML or statistical models. Where needed, they will have to learn and adapt to the requirements imposed by real-life, scaled deployments. 

Candidates should have excellent communication skills and a willingness to adapt to the challenges of doing applied work for social good. 


  • B.Tech./B.E./B.S./M.Tech./M.E./M.S./M.Sc. or equivalent in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or a relevant quantitative field. Work experience beyond the terminal degree will determine the appropriate seniority level.
  • Solid software engineering skills across one or multiple languages including Python, C++, Java.
  • Interest in applying software engineering practices to ML projects.
  • Track record of project work in applied machine learning. Experience in applying AI models to concrete real-world problems is a plus.
  • Strong verbal and written communication skills in English.